ABSTRACT
Title of Document: ARE HOUSTON?S LAND USE
RELATIONSHIPS UNIQUE?
Christopher L. Dorney, Ph.D., 2021
Directed By: Professor Gerrit Knaap, Department of Urban
Studies and Planning
The city of Houston, Texas has been at the heart of a long-running debate in the
United States on government?s proper role in the land development process.  As the
only large American city that never adopted a city-wide zoning ordinance, Houston is
often cited as an example for why more or less government planning is needed.  Some
authors claim that Houston is an outlier when it comes to land use relationships, with
strange land use juxtapositions quite prevalent.  Other authors argue that zoning is
largely redundant to market forces and that Houston?s land use relationships are not
all that different from zoned cities.  The purpose of this study is to inform this
ongoing debate by undertaking a quantitative analysis of land use relationships across
large American cities to determine if Houston?s are distinctive.  The study develops
several metrics to quantify land use relationships and uses principal component
analysis to determine if Houston is an outlier.  The findings indicate that Houston?s
land use relationships are not substantially different from those of zoned cities.
ARE HOUSTON?S LAND USE RELATIONSHIPS UNIQUE?
By
Christopher L. Dorney
Dissertation submitted to the Faculty of the Graduate School of the
University of Maryland, College Park in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
2021
Advisory Committee:
Professor Gerrit Knaap, Chair
Research Professor Uri Avin
Professor Matt Bell
Associate Professor Mary Corbin-Sies
Professor Casey Dawkins
? Copyright by
Christopher L. Dorney
2021
Dedication
This dissertation is dedicated to my wife, Lydia Lyshevski, for her support
and patience in letting me see this work through to its full completion.
ii
Acknowledgments
I am indebted to Gregg Cornetski for his significant contributions to this
research. His tireless efforts helped translate the geospatial processes for calculating
the land use metrics that are a central part of this study into Python code that could be
used to run the analyses efficiently for many cities.  Without his coding contributions,
this work could not have been completed for the 50 cities analyzed and the insights
would have, in turn, been significantly more limited.  I would also like to
acknowledge Timothy Grose who also made some important contributions to the
coding effort.
iii
Table of Contents
Dedication .................................................................................................................ii
Acknowledgments ................................................................................................... iii
Table of Contents ..................................................................................................... iv
List of Tables........................................................................................................... vii
List of Figures ........................................................................................................viii
Chapter 1: Introduction .............................................................................................. 1
Chapter 2: Planning and Land Use Regulations in American Cities............................ 4
American Planning and Land Use Regulations: A Brief History ............................ 4
Planning and Land Use Regulations in Houston ................................................... 22
The Zoning Debate .......................................................................................... 22
Current Plans and Regulations ......................................................................... 27
Chapter 3: Review of the Literature ......................................................................... 55
Evidence that Zoning Follows the Market ............................................................ 56
Evidence that Zoning is Binding .......................................................................... 65
Gaps in the Literature .......................................................................................... 74
Chapter 4: Methodology .......................................................................................... 77
Research Question and Hypotheses ...................................................................... 77
Selection of Study Cities ...................................................................................... 80
Land Use Data ..................................................................................................... 84
Land Use Reclassification Schema....................................................................... 91
Land Use Metrics .............................................................................................. 104
Land Use Composition Metrics ...................................................................... 110
Land Use Relationship Metrics ...................................................................... 111
Transportation-Land Use Relationship Metrics .............................................. 116
Land Use Clustering Metrics .......................................................................... 119
Comparative Techniques ................................................................................... 120
Bar Charts ...................................................................................................... 120
Principle Component Analysis ....................................................................... 121
Chapter 5: Results and Analysis............................................................................. 127
Land Use Metrics by City .................................................................................. 127
Land Use Composition Metrics ...................................................................... 127
Land Use Relationship Metrics ...................................................................... 142
Transportation-Land Use Relationship Metrics .............................................. 174
iv
Land Use Clustering Metrics .......................................................................... 200
Summary ....................................................................................................... 206
Principal Component Analysis ........................................................................... 206
Chapter 6:  Conclusions and Next Steps ................................................................. 223
Conclusions ....................................................................................................... 223
Next Steps ......................................................................................................... 225
Appendix A: Land Use Maps ................................................................................. 230
Appendix B: Bar Charts Showing the Proportion of Shared Parcel Perimeter
Bordering on Each Land Use ................................................................................. 281
Appendix C: Bar Charts Showing the Normalized Proportion of Shared Parcel
Perimeter Bordering on Each Land Use ................................................................. 337
Appendix D: Bar Charts Showing the Proportion of Parcels in Each Land Use Class
Bordering Each Land Use ...................................................................................... 371
Appendix E: Bar Charts Showing the Normalized Proportion of Parcels in Each Land
Use Class Bordering Each Land Use ...................................................................... 427
Appendix F: Bar Charts Showing the Proportion of Parcels in Each Land Use Class
Bordering Only the Same Land Use ....................................................................... 483
Appendix G: Bar Charts Showing the Proportional Area of Land Uses Within 500
Feet of Each Land Use ........................................................................................... 489
Appendix H: Bar Charts Showing the Normalized Proportional Area of Land Uses
Within 500 Feet of Each Land Use ........................................................................ 551
Appendix I: Bar Charts Showing the Proportion of Parcels that Have Each Land Use
Within 500 Feet ..................................................................................................... 613
Appendix J: Bar Charts Showing the Normalized Proportion of Parcels that Have
Each Land Use Within 500 Feet ............................................................................ 669
v
Appendix K: Bar Charts Showing the Proportion of Parcels That Have Zero, One,
Two, Three, Four, Five, Six, Seven, Eight, or Nine Other Land Uses Within 500 Feet
 .............................................................................................................................. 725
Appendix L: Bar Charts Showing the Normalized Proportion of Parcels That Have
Zero, One, Two, Three, Four, Five, Six, Seven, Eight, or Nine Other Land Uses
Within 500 Feet ..................................................................................................... 772
Appendix M: Bar Charts Showing the Average Distance Between the Nearest Parcels
of Each Land Use Class ......................................................................................... 819
Appendix N: Bar Charts Showing the Normalized Average Distance Between the
Nearest Parcels of Each Land Use Class ................................................................ 875
Appendix O: Bar Charts Showing the Proportional Area of Each Land Use Class
Within 200 Feet of Non-Access Controlled Arterial Roadway Centerlines ............. 931
Appendix P: Bar Charts Showing the Proportional Area of Each Land Use Class
Within 200 Feet of Rail Lines ................................................................................ 937
Appendix Q: Bar Charts Showing the Proportional Area of Each Land Use Class
Within a Half Mile of a Limited Access Highway Exit .......................................... 943
Bibliography .......................................................................................................... 949
vi
List of Tables
Table 1: Data Sources and Dates for Parcel Level Land Use Information Used in this
Study ....................................................................................................................... 87
Table 2: Land Use Classification Schema Used in this Study ................................... 96
Table 3: Schema for Assigning A Land Use to Parcels Associated with Multiple Land
Uses ...................................................................................................................... 102
Table 4: Land Use Metrics ..................................................................................... 107
Table 5: Bar Chart Index, Proportion of Shared Parcel Perimeter Bordering on Each
Land Use ............................................................................................................... 281
Table 6: Bar Chart Index, Normalized Proportion of Shared Parcel Perimeter
Bordering on Each Land Use ................................................................................. 337
Table 7: Bar Chart Index, Proportion of Parcels in Each Land Use Class Bordering
Each Land Use ...................................................................................................... 371
Table 8: Bar Chart Index, Normalized Proportion of Parcels in Each Land Use Class
Bordering Each Land Use ...................................................................................... 427
Table 9: Bar Chart Index, Proportional Area of Land Uses Within 500 Feet of Each
Land Use ............................................................................................................... 489
Table 10: Bar Chart Index, Normalized Proportional Area of Land Uses Within 500
Feet of Each Land Use ........................................................................................... 551
Table 11: Bar Chart Index, Proportion of Parcels that Have Each Land Use Within
500 Feet................................................................................................................. 613
Table 12: Bar Chart Index, Normalized Proportion of Parcels that Have Each Land
Use Within 500 Feet .............................................................................................. 669
Table 13: Bar Chart Index, Proportion of Parcels That Have Zero, One, Two, Three,
Four, Five, Six, Seven, Eight, or Nine Other Land Uses Within 500 Feet ............... 725
Table 14: Bar Chart Index, Normalized Proportion of Parcels That Have Zero, One,
Two, Three, Four, Five, Six, Seven, Eight, or Nine Other Land Uses Within 500 Feet
 .............................................................................................................................. 772
Table 15: Bar Chart Index, Average Distance Between the Nearest Parcels of Each
Land Use Class ...................................................................................................... 819
Table 16: Bar Chart Index, Normalized Average Distance Between the Nearest
Parcels of Each Land Use Class ............................................................................. 875
vii
List of Figures
Figure 1: Year of Adoption of First Comprehensive Zoning Ordinance in America?s
50 Largest Cities ...................................................................................................... 11
Figure 2: Location Map of the Saint George Place TIRZ.......................................... 26
Figure 3: An Inner Loop Neighborhood Lacking Single-Family Covenant Protections
 ................................................................................................................................ 32
Figure 4: Rendering of the Proposed Ashby High Rise ............................................ 34
Figure 5: Site of the Proposed Ashby High Rise ...................................................... 34
Figure 6: Map of Airport Zoning in Houston ........................................................... 42
Figure 7: Map of Study City Locations Showing Regional Classification ................ 82
Figure 8: Map of Houston Area Study Cities ........................................................... 83
Figure 9: Example Outlier Map for Hypothetical Three-Dimensional Data Reduced to
Two Principal Components .................................................................................... 125
Figure 10: Classification of Observations on an Outlier Map ................................. 126
Figure 11: Proportion of Total Parcel Area Devoted to AG Uses in Each Study City
 .............................................................................................................................. 129
Figure 12: Proportion of Total Parcel Area Devoted to COM Uses in Each Study City
 .............................................................................................................................. 129
Figure 13: Proportion of Total Parcel Area Devoted to IND Uses in Each Study City
 .............................................................................................................................. 130
Figure 14: Proportion of Total Parcel Area Devoted to MMR Uses in Each Study City
 .............................................................................................................................. 130
Figure 15: Proportion of Total Parcel Area Devoted to MU Uses in Each Study City
 .............................................................................................................................. 131
Figure 16: Proportion of Total Parcel Area Devoted to MFR Uses in Each Study City
 .............................................................................................................................. 131
Figure 17: Proportion of Total Parcel Area Devoted to PUB Uses in Each Study City
 .............................................................................................................................. 132
Figure 18: Proportion of Total Parcel Area Devoted to SFDR Uses in Each Study City
 .............................................................................................................................. 132
Figure 19: Proportion of Total Parcel Area Devoted to TCU Uses in Each Study City
 .............................................................................................................................. 133
Figure 20: Proportion of Total Parcel Area Devoted to UNKN Uses in Each Study
City ....................................................................................................................... 133
Figure 21: Proportion of Total Parcel Area Devoted to VAC Uses in Each Study City
 .............................................................................................................................. 134
Figure 22: Average Size of AG Parcels in Each Study City.................................... 136
Figure 23: Average Size of COM Parcels in Each Study City ................................ 136
Figure 24: Average Size of IND Parcels in Each Study City .................................. 137
Figure 25: Average Size of MMR Parcels in Each Study City ................................ 137
Figure 26: Average Size of MU Parcels in Each Study City ................................... 138
Figure 27: Average Size of MFR Parcels in Each Study City ................................. 138
Figure 28: Average Size of PUB Parcels in Each Study City .................................. 139
Figure 29: Average Size of SFDR Parcels in Each Study City................................ 139
viii
Figure 30: Average Size of TCU Parcels in Each Study City ................................. 140
Figure 31: Average Size of UNKN Use Parcels in Each Study City ....................... 140
Figure 32: Average Size of VAC Parcels in Each Study City ................................. 141
Figure 33: Proportion of the Shared Parcel Perimeter Bordering AG Uses in Each
Study City ............................................................................................................. 145
Figure 34: Proportion of the Shared Parcel Perimeter Bordering COM Uses in Each
Study City ............................................................................................................. 145
Figure 35: Proportion of the Shared Parcel Perimeter Bordering IND Uses in Each
Study City ............................................................................................................. 146
Figure 36: Proportion of the Shared Parcel Perimeter Bordering MMR Uses in Each
Study City ............................................................................................................. 146
Figure 37: Proportion of the Shared Parcel Perimeter Bordering MU Uses in Each
Study City ............................................................................................................. 147
Figure 38: Proportion of the Shared Parcel Perimeter Bordering MFR Uses in Each
Study City ............................................................................................................. 147
Figure 39: Proportion of the Shared Parcel Perimeter Bordering PUB Uses in Each
Study City ............................................................................................................. 148
Figure 40: Proportion of the Shared Parcel Perimeter Bordering SFDR Uses in Each
Study City ............................................................................................................. 148
Figure 41: Proportion of the Shared Parcel Perimeter Bordering TCU Uses in Each
Study City ............................................................................................................. 149
Figure 42: Proportion of the Shared Parcel Perimeter Bordering UNKN Uses in Each
Study City ............................................................................................................. 149
Figure 43: Proportion of the Shared Parcel Perimeter Bordering VAC Uses in Each
Study City ............................................................................................................. 150
Figure 44: Proportion of AG Parcels Bordering Only Other AG Parcels (Normalized)
 .............................................................................................................................. 158
Figure 45: Proportion of COM Parcels Bordering Only Other COM Parcels
(Normalized) ......................................................................................................... 158
Figure 46: Proportion of IND Parcels Bordering Only Other IND Parcels
(Normalized) ......................................................................................................... 159
Figure 47: Proportion of MMR Parcels Bordering Only Other MMR Parcels
(Normalized) ......................................................................................................... 159
Figure 48: Proportion of MU Parcels Bordering Only Other MU Parcels (Normalized)
 .............................................................................................................................. 160
Figure 49: Proportion of MFR Parcels Bordering Only Other MFR Parcels
(Normalized) ......................................................................................................... 160
Figure 50: Proportion of PUB Parcels Bordering Only Other PUB Parcels
(Normalized) ......................................................................................................... 161
Figure 51: Proportion of SFDR Parcels Bordering Only Other SFDR Parcels
(Normalized) ......................................................................................................... 161
Figure 52: Proportion of TCU Parcels Bordering Only Other TCU Parcels
(Normalized) ......................................................................................................... 162
Figure 53: Proportion of UNKN Parcels Bordering Only Other UNKN Parcels
(Normalized) ......................................................................................................... 162
ix
Figure 54: Proportion of VAC Parcels Bordering Only Other VAC Parcels
(Normalized) ......................................................................................................... 163
Figure 55: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to AG
Uses (Normalized) ................................................................................................. 176
Figure 56: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to COM
Uses (Normalized) ................................................................................................. 176
Figure 57: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to IND
Uses (Normalized) ................................................................................................. 177
Figure 58: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MMR
Uses (Normalized) ................................................................................................. 177
Figure 59: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MU
Uses (Normalized) ................................................................................................. 178
Figure 60: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MFR
Uses (Normalized) ................................................................................................. 178
Figure 61: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to PUB
Uses (Normalized) ................................................................................................. 179
Figure 62: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to SFDR
Uses (Normalized) ................................................................................................. 179
Figure 63: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to TCU
Uses (Normalized) ................................................................................................. 180
Figure 64: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to UNKN
Uses (Normalized) ................................................................................................. 180
Figure 65: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to VAC
Uses (Normalized) ................................................................................................. 181
Figure 66: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to AG
Uses (Normalized) ................................................................................................. 183
Figure 67: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to COM
Uses (Normalized) ................................................................................................. 183
Figure 68: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to IND
Uses (Normalized) ................................................................................................. 184
Figure 69: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MMR
Uses (Normalized) ................................................................................................. 184
Figure 70: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MU
Uses (Normalized) ................................................................................................. 185
Figure 71: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MFR
Uses (Normalized) ................................................................................................. 185
Figure 72: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to PUB
Uses (Normalized) ................................................................................................. 186
Figure 73: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to SFDR
Uses (Normalized) ................................................................................................. 186
Figure 74: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to TCU
Uses (Normalized) ................................................................................................. 187
Figure 75: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
UNKN Uses (Normalized) ..................................................................................... 187
Figure 76: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to VAC
Uses (Normalized) ................................................................................................. 188
x
Figure 77: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to AG Uses (Normalized) ........................................................................ 190
Figure 78: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to COM Uses (Normalized) ..................................................................... 190
Figure 79: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to IND Uses (Normalized) ....................................................................... 191
Figure 80: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to MMR Uses (Normalized) .................................................................... 191
Figure 81: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to MU Uses (Normalized) ........................................................................ 192
Figure 82: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to MFR Uses (Normalized) ...................................................................... 192
Figure 83: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to PUB Uses (Normalized) ...................................................................... 193
Figure 84: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to SFDR Uses (Normalized) .................................................................... 193
Figure 85: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to TCU Uses (Normalized) ...................................................................... 194
Figure 86: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to UNKN Uses (Normalized) ................................................................... 194
Figure 87: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit
Devoted to VAC Uses (Normalized) ...................................................................... 195
Figure 88: Average Distance Between IND Parcels and the Nearest Rail Line ....... 197
Figure 89: Average Distance Between IND Parcels and the Nearest Rail Line
(Normalized) ......................................................................................................... 197
Figure 90: Average Distance Between IND Parcels and the Nearest Limited Access
Highway ................................................................................................................ 199
Figure 91: Average Distance Between IND Parcels and the Nearest Limited Access
Highway (Normalized) .......................................................................................... 199
Figure 92: Average Nearest Neighbor Index for AG Uses ...................................... 201
Figure 93: Average Nearest Neighbor Index for COM Uses................................... 201
Figure 94: Average Nearest Neighbor Index for IND Uses .................................... 202
Figure 95: Average Nearest Neighbor Index for MMR Uses .................................. 202
Figure 96: Average Nearest Neighbor Index for MU Uses ..................................... 203
Figure 97: Average Nearest Neighbor Index for MFR Uses ................................... 203
Figure 98: Average Nearest Neighbor Index for PUB Uses .................................... 204
Figure 99: Average Nearest Neighbor Index for SFDR Uses .................................. 204
Figure 100: Average Nearest Neighbor Index for TCU Uses .................................. 205
Figure 101: Average Nearest Neighbor Index for VAC Uses ................................. 205
Figure 102: Scree Plot of the Initial MacroPCA Run .............................................. 210
Figure 103: Scores for Principal Component One .................................................. 213
Figure 104: Scores for Principal Component Two .................................................. 213
Figure 105: Scores for Principal Component Three ................................................ 214
Figure 106: Scores for Principal Component Four ................................................. 214
Figure 107: Scores for Principal Component Five .................................................. 215
Figure 108: Scores for Principal Component Six .................................................... 215
xi
Figure 109: Scores for Principal Component Seven ............................................... 216
Figure 110: Scores for Principal Component Eight ................................................ 216
Figure 111: Scores for Principal Component Nine ................................................. 217
Figure 112: MacroPCA Outlier Map ...................................................................... 219
Figure 113: Land Use in Albuquerque ................................................................... 231
Figure 114: Land Use in Arlington ........................................................................ 232
Figure 115: Land Use in Atlanta ............................................................................ 233
Figure 116: Land Use in Austin ............................................................................. 234
Figure 117: Land Use in Baltimore ........................................................................ 235
Figure 118: Land Use in Boston ............................................................................ 236
Figure 119: Land Use in Charlotte ......................................................................... 237
Figure 120: Land Use in Chicago........................................................................... 238
Figure 121: Land Use in Cleveland ........................................................................ 239
Figure 122: Land Use in Colorado Springs ............................................................ 240
Figure 123: Land Use in Columbus........................................................................ 241
Figure 124: Land Use in Dallas.............................................................................. 242
Figure 125: Land Use in Denver ............................................................................ 243
Figure 126: Land Use in Detroit ............................................................................ 244
Figure 127: Land Use in El Paso ............................................................................ 245
Figure 128: Land Use in Fort Worth ...................................................................... 246
Figure 129: Land Use in Fresno ............................................................................. 247
Figure 130: Land Use in Houston .......................................................................... 248
Figure 131: Land Use in Houston's Zoned Suburbs ................................................ 249
Figure 132: Land Use in Indianapolis .................................................................... 250
Figure 133: Land Use in Jacksonville .................................................................... 251
Figure 134: Land Use in Kansas City ..................................................................... 252
Figure 135: Land Use in Las Vegas ....................................................................... 253
Figure 136: Land Use in Long Beach ..................................................................... 254
Figure 137: Land Use in Los Angeles .................................................................... 255
Figure 138: Land Use in Louisville ........................................................................ 256
Figure 139: Land Use in Memphis ......................................................................... 257
Figure 140: Land Use in Mesa ............................................................................... 258
Figure 141: Land Use in Miami ............................................................................. 259
Figure 142: Land Use in Milwaukee ...................................................................... 260
Figure 143: Land Use in Minneapolis .................................................................... 261
Figure 144: Land Use in Nashville ......................................................................... 262
Figure 145: Land Use in New York ....................................................................... 263
Figure 146: Land Use in Oakland .......................................................................... 264
Figure 147: Land Use in Oklahoma City ................................................................ 265
Figure 148: Land Use in Omaha ............................................................................ 266
Figure 149: Land Use in Philadelphia .................................................................... 267
Figure 150: Land Use in Phoenix ........................................................................... 268
Figure 151: Land Use in Portland .......................................................................... 269
Figure 152: Land Use in Raleigh ........................................................................... 270
Figure 153: Land Use in Sacramento ..................................................................... 271
Figure 154: Land Use in San Antonio .................................................................... 272
xii
Figure 155: Land Use in San Diego ....................................................................... 273
Figure 156: Land Use in San Francisco .................................................................. 274
Figure 157: Land Use in Seattle ............................................................................. 275
Figure 158: Land Use in Tucson ............................................................................ 276
Figure 159: Land Use in Tulsa ............................................................................... 277
Figure 160: Land Use in Virginia Beach ................................................................ 278
Figure 161: Land Use in Washington ..................................................................... 279
Figure 162: Land Use in Wichita ........................................................................... 280
Figure 163: Proportion of Shared AG Parcel Perimeter Bordering on AG Uses...... 282
Figure 164: Proportion of Shared AG Parcel Perimeter Bordering on COM Uses .. 282
Figure 165: Proportion of Shared AG Parcel Perimeter Bordering on IND Uses .... 283
Figure 166: Proportion of Shared AG Parcel Perimeter Bordering on MMR Uses .. 283
Figure 167: Proportion of Shared AG Parcel Perimeter Bordering on MU Uses ..... 284
Figure 168: Proportion of Shared AG Parcel Perimeter Bordering on MFR Uses ... 284
Figure 169: Proportion of Shared AG Parcel Perimeter Bordering on PUB Uses .... 285
Figure 170: Proportion of Shared AG Parcel Perimeter Bordering on SFDR Uses . 285
Figure 171: Proportion of Shared AG Parcel Perimeter Bordering on TCU Uses ... 286
Figure 172: Proportion of Shared AG Parcel Perimeter Bordering on UNKN Uses 286
Figure 173: Proportion of Shared AG Parcel Perimeter Bordering on VAC Uses ... 287
Figure 174: Proportion of Shared COM Parcel Perimeter Bordering on AG Uses .. 287
Figure 175: Proportion of Shared COM Parcel Perimeter Bordering on COM Uses288
Figure 176: Proportion of Shared COM Parcel Perimeter Bordering on IND Uses . 288
Figure 177: Proportion of Shared COM Parcel Perimeter Bordering on IND Uses . 289
Figure 178: Proportion of Shared COM Parcel Perimeter Bordering on MU Uses .. 289
Figure 179: Proportion of Shared COM Parcel Perimeter Bordering on MFR Uses 290
Figure 180: Proportion of Shared COM Parcel Perimeter Bordering on PUB Uses 290
Figure 181: Proportion of Shared COM Parcel Perimeter Bordering on SFDR Uses
 .............................................................................................................................. 291
Figure 182: Proportion of Shared COM Parcel Perimeter Bordering on TCU Uses 291
Figure 183: Proportion of Shared COM Parcel Perimeter Bordering on UNKN Uses
 .............................................................................................................................. 292
Figure 184: Proportion of Shared COM Parcel Perimeter Bordering on VAC Uses 292
Figure 185: Proportion of Shared IND Parcel Perimeter Bordering on AG Uses .... 293
Figure 186: Proportion of Shared IND Parcel Perimeter Bordering on COM Uses . 293
Figure 187: Proportion of Shared IND Parcel Perimeter Bordering on IND Uses ... 294
Figure 188: Proportion of Shared IND Parcel Perimeter Bordering on MMR Uses 294
Figure 189: Proportion of Shared IND Parcel Perimeter Bordering on MU Uses .... 295
Figure 190: Proportion of Shared IND Parcel Perimeter Bordering on MFR Uses .. 295
Figure 191: Proportion of Shared IND Parcel Perimeter Bordering on PUB Uses .. 296
Figure 192: Proportion of Shared IND Parcel Perimeter Bordering on SFDR Uses 296
Figure 193: Proportion of Shared IND Parcel Perimeter Bordering on TCU Uses .. 297
Figure 194: Proportion of Shared IND Parcel Perimeter Bordering on UNKN Uses
 .............................................................................................................................. 297
Figure 195: Proportion of Shared IND Parcel Perimeter Bordering on VAC Uses .. 298
Figure 196: Proportion of Shared MMR Parcel Perimeter Bordering on AG Uses .. 298
xiii
Figure 197: Proportion of Shared MMR Parcel Perimeter Bordering on COM Uses
 .............................................................................................................................. 299
Figure 198: Proportion of Shared MMR Parcel Perimeter Bordering on IND Uses 299
Figure 199: Proportion of Shared MMR Parcel Perimeter Bordering on MMR Uses
 .............................................................................................................................. 300
Figure 200: Proportion of Shared MMR Parcel Perimeter Bordering on MU Uses . 300
Figure 201: Proportion of Shared MMR Parcel Perimeter Bordering on MFR Uses301
Figure 202: Proportion of Shared MMR Parcel Perimeter Bordering on PUB Uses 301
Figure 203: Proportion of Shared MMR Parcel Perimeter Bordering on SFDR Uses
 .............................................................................................................................. 302
Figure 204: Proportion of Shared MMR Parcel Perimeter Bordering on TCU Uses 302
Figure 205: Proportion of Shared MMR Parcel Perimeter Bordering on UNKN Uses
 .............................................................................................................................. 303
Figure 206: Proportion of Shared MMR Parcel Perimeter Bordering on VAC Uses303
Figure 207: Proportion of Shared MU Parcel Perimeter Bordering on AG Uses ..... 304
Figure 208: Proportion of Shared MU Parcel Perimeter Bordering on COM Uses .. 304
Figure 209: Proportion of Shared MU Parcel Perimeter Bordering on IND Uses .... 305
Figure 210: Proportion of Shared MU Parcel Perimeter Bordering on MMR Uses . 305
Figure 211: Proportion of Shared MU Parcel Perimeter Bordering on MU Uses .... 306
Figure 212: Proportion of Shared MU Parcel Perimeter Bordering on MFR Uses .. 306
Figure 213: Proportion of Shared MU Parcel Perimeter Bordering on PUB Uses ... 307
Figure 214: Proportion of Shared MU Parcel Perimeter Bordering on SFDR Uses . 307
Figure 215: Proportion of Shared MU Parcel Perimeter Bordering on TCU Uses ... 308
Figure 216: Proportion of Shared MU Parcel Perimeter Bordering on UNKN Uses 308
Figure 217: Proportion of Shared MU Parcel Perimeter Bordering on VAC Uses .. 309
Figure 218: Proportion of Shared MFR Parcel Perimeter Bordering on AG Uses ... 309
Figure 219: Proportion of Shared MFR Parcel Perimeter Bordering on COM Uses 310
Figure 220: Proportion of Shared MFR Parcel Perimeter Bordering on IND Uses .. 310
Figure 221: Proportion of Shared MFR Parcel Perimeter Bordering on MMR Uses311
Figure 222: Proportion of Shared MFR Parcel Perimeter Bordering on MU Uses .. 311
Figure 223: Proportion of Shared MFR Parcel Perimeter Bordering on MFR Uses 312
Figure 224: Proportion of Shared MFR Parcel Perimeter Bordering on PUB Uses . 312
Figure 225: Proportion of Shared MFR Parcel Perimeter Bordering on SFDR Uses
 .............................................................................................................................. 313
Figure 226: Proportion of Shared MFR Parcel Perimeter Bordering on TCU Uses . 313
Figure 227: Proportion of Shared MFR Parcel Perimeter Bordering on UNKN Uses
 .............................................................................................................................. 314
Figure 228: Proportion of Shared MFR Parcel Perimeter Bordering on VAC Uses 314
Figure 229: Proportion of Shared PUB Parcel Perimeter Bordering on AG Uses .... 315
Figure 230: Proportion of Shared PUB Parcel Perimeter Bordering on COM Uses 315
Figure 231: Proportion of Shared PUB Parcel Perimeter Bordering on IND Uses .. 316
Figure 232: Proportion of Shared PUB Parcel Perimeter Bordering on MMR Uses 316
Figure 233: Proportion of Shared PUB Parcel Perimeter Bordering on MU Uses ... 317
Figure 234: Proportion of Shared PUB Parcel Perimeter Bordering on MFR Uses . 317
Figure 235: Proportion of Shared PUB Parcel Perimeter Bordering on PUB Uses .. 318
Figure 236: Proportion of Shared PUB Parcel Perimeter Bordering on SFDR Uses 318
xiv
Figure 237: Proportion of Shared PUB Parcel Perimeter Bordering on TCU Uses . 319
Figure 238: Proportion of Shared PUB Parcel Perimeter Bordering on UNKN Uses
 .............................................................................................................................. 319
Figure 239: Proportion of Shared PUB Parcel Perimeter Bordering on VAC Uses . 320
Figure 240: Proportion of Shared SFDR Parcel Perimeter Bordering on AG Uses . 320
Figure 241: Proportion of Shared SFDR Parcel Perimeter Bordering on COM Uses
 .............................................................................................................................. 321
Figure 242: Proportion of Shared SFDR Parcel Perimeter Bordering on IND Uses 321
Figure 243: Proportion of Shared SFDR Parcel Perimeter Bordering on MMR Uses
 .............................................................................................................................. 322
Figure 244: Proportion of Shared SFDR Parcel Perimeter Bordering on MU Uses . 322
Figure 245: Proportion of Shared SFDR Parcel Perimeter Bordering on MFR Uses
 .............................................................................................................................. 323
Figure 246: Proportion of Shared SFDR Parcel Perimeter Bordering on PUB Uses 323
Figure 247: Proportion of Shared SFDR Parcel Perimeter Bordering on SFDR Uses
 .............................................................................................................................. 324
Figure 248: Proportion of Shared SFDR Parcel Perimeter Bordering on TCU Uses 324
Figure 249: Proportion of Shared SFDR Parcel Perimeter Bordering on UNKN Uses
 .............................................................................................................................. 325
Figure 250: Proportion of Shared SFDR Parcel Perimeter Bordering on VAC Uses
 .............................................................................................................................. 325
Figure 251: Proportion of Shared TCU Parcel Perimeter Bordering on AG Uses ... 326
Figure 252: Proportion of Shared TCU Parcel Perimeter Bordering on COM Uses 326
Figure 253: Proportion of Shared TCU Parcel Perimeter Bordering on IND Uses .. 327
Figure 254: Proportion of Shared TCU Parcel Perimeter Bordering on MMR Uses 327
Figure 255: Proportion of Shared TCU Parcel Perimeter Bordering on MU Uses ... 328
Figure 256: Proportion of Shared TCU Parcel Perimeter Bordering on MFR Uses . 328
Figure 257: Proportion of Shared TCU Parcel Perimeter Bordering on PUB Uses . 329
Figure 258: Proportion of Shared TCU Parcel Perimeter Bordering on SFDR Uses 329
Figure 259: Proportion of Shared TCU Parcel Perimeter Bordering on TCU Uses . 330
Figure 260: Proportion of Shared TCU Parcel Perimeter Bordering on UNKN Uses
 .............................................................................................................................. 330
Figure 261: Proportion of Shared TCU Parcel Perimeter Bordering on VAC Uses . 331
Figure 262: Proportion of Shared VAC Parcel Perimeter Bordering on AG Uses ... 331
Figure 263: Proportion of Shared VAC Parcel Perimeter Bordering on COM Uses 332
Figure 264: Proportion of Shared VAC Parcel Perimeter Bordering on IND Uses .. 332
Figure 265: Proportion of Shared VAC Parcel Perimeter Bordering on MMR Uses333
Figure 266: Proportion of Shared VAC Parcel Perimeter Bordering on MU Uses .. 333
Figure 267: Proportion of Shared VAC Parcel Perimeter Bordering on MFR Uses 334
Figure 268: Proportion of Shared VAC Parcel Perimeter Bordering on PUB Uses . 334
Figure 269: Proportion of Shared VAC Parcel Perimeter Bordering on SFDR Uses
 .............................................................................................................................. 335
Figure 270: Proportion of Shared VAC Parcel Perimeter Bordering on TCU Uses . 335
Figure 271: Proportion of Shared VAC Parcel Perimeter Bordering on UNKN Uses
 .............................................................................................................................. 336
Figure 272: Proportion of Shared VAC Parcel Perimeter Bordering on VAC Uses 336
xv
Figure 273: Proportion of Shared AG Parcel Perimeter Bordering on AG Uses
(Normalized) ......................................................................................................... 338
Figure 274: Proportion of Shared AG/COM Parcel Perimeter Bordering on COM/AG
Uses (Normalized) ................................................................................................. 338
Figure 275: Proportion of Shared AG/IND Parcel Perimeter Bordering on IND/AG
Uses (Normalized) ................................................................................................. 339
Figure 276: Proportion of Shared AG/MMR Parcel Perimeter Bordering on
MMR/AG Uses (Normalized) ................................................................................ 339
Figure 277: Proportion of Shared AG/MU Parcel Perimeter Bordering on MU/AG
Uses (Normalized) ................................................................................................. 340
Figure 278: Proportion of Shared AG/MFR Parcel Perimeter Bordering on MFR/AG
Uses (Normalized) ................................................................................................. 340
Figure 279: Proportion of Shared AG/PUB Parcel Perimeter Bordering on PUB/AG
Uses (Normalized) ................................................................................................. 341
Figure 280: Proportion of Shared AG/SFDR Parcel Perimeter Bordering on
SFDR/AG Uses (Normalized)................................................................................ 341
Figure 281: Proportion of Shared AG/TCU Parcel Perimeter Bordering on TCU/AG
Uses (Normalized) ................................................................................................. 342
Figure 282: Proportion of Shared AG/UNKN Parcel Perimeter Bordering on
UNKN/AG Uses (Normalized) .............................................................................. 342
Figure 283: Proportion of Shared AG/VAC Parcel Perimeter Bordering on VAC/AG
Uses (Normalized) ................................................................................................. 343
Figure 284: Proportion of Shared COM Parcel Perimeter Bordering on COM Uses
(Normalized) ......................................................................................................... 343
Figure 285: Proportion of Shared COM/IND Parcel Perimeter Bordering on
IND/COM Uses (Normalized) ............................................................................... 344
Figure 286: Proportion of Shared COM/MMR Parcel Perimeter Bordering on
MMR/COM Uses (Normalized)............................................................................. 344
Figure 287: Proportion of Shared COM/MU Parcel Perimeter Bordering on
MU/COM Uses (Normalized) ................................................................................ 345
Figure 288: Proportion of Shared COM/MFR Parcel Perimeter Bordering on
MFR/COM Uses (Normalized) .............................................................................. 345
Figure 289: Proportion of Shared COM/PUB Parcel Perimeter Bordering on
PUB/COM Uses (Normalized) .............................................................................. 346
Figure 290: Proportion of Shared COM/SFDR Parcel Perimeter Bordering on
SFDR/COM Uses (Normalized) ............................................................................ 346
Figure 291: Proportion of Shared COM/TCU Parcel Perimeter Bordering on
TCU/COM Uses (Normalized) .............................................................................. 347
Figure 292: Proportion of Shared COM/UNKN Parcel Perimeter Bordering on
UNKN/COM Uses (Normalized) ........................................................................... 347
Figure 293: Proportion of Shared COM/VAC Parcel Perimeter Bordering on
VAC/COM Uses (Normalized) .............................................................................. 348
Figure 294: Proportion of Shared IND Parcel Perimeter Bordering on IND Uses
(Normalized) ......................................................................................................... 348
Figure 295: Proportion of Shared IND/MMR Parcel Perimeter Bordering on
MMR/IND Uses (Normalized)............................................................................... 349
xvi
Figure 296: Proportion of Shared IND/MU Parcel Perimeter Bordering on MU/IND
Uses (Normalized) ................................................................................................. 349
Figure 297: Proportion of Shared IND/MFR Parcel Perimeter Bordering on
MFR/IND Uses (Normalized) ................................................................................ 350
Figure 298: Proportion of Shared IND/PUB Parcel Perimeter Bordering on PUB/IND
Uses (Normalized) ................................................................................................. 350
Figure 299: Proportion of Shared IND/SFDR Parcel Perimeter Bordering on
SFDR/IND Uses (Normalized) .............................................................................. 351
Figure 300: Proportion of Shared IND/TCU Parcel Perimeter Bordering on TCU/IND
Uses (Normalized) ................................................................................................. 351
Figure 301: Proportion of Shared IND/UNKN Parcel Perimeter Bordering on
UNKN/IND Uses (Normalized) ............................................................................. 352
Figure 302: Proportion of Shared IND/VAC Parcel Perimeter Bordering on
VAC/IND Uses (Normalized) ................................................................................ 352
Figure 303: Proportion of Shared MMR Parcel Perimeter Bordering on MMR Uses
(Normalized) ......................................................................................................... 353
Figure 304: Proportion of Shared MMR/MU Parcel Perimeter Bordering on
MU/MMR Uses (Normalized) ............................................................................... 353
Figure 305: Proportion of Shared MMR/MFR Parcel Perimeter Bordering on
MFR/MMR Uses (Normalized) ............................................................................. 354
Figure 306: Proportion of Shared MMR/PUB Parcel Perimeter Bordering on
PUB/MMR Uses (Normalized) .............................................................................. 354
Figure 307: Proportion of Shared MMR/SFDR Parcel Perimeter Bordering on
SFDR/MMR Uses (Normalized) ............................................................................ 355
Figure 308: Proportion of Shared MMR/TCU Parcel Perimeter Bordering on
TCU/MMR Uses (Normalized) .............................................................................. 355
Figure 309: Proportion of Shared MMR/UNKN Parcel Perimeter Bordering on
UNIKN/MMR Uses (Normalized) ......................................................................... 356
Figure 310: Proportion of Shared MMR/VAC Parcel Perimeter Bordering on
VAC/MMR Uses (Normalized) ............................................................................. 356
Figure 311: Proportion of Shared MU Parcel Perimeter Bordering on MU Uses
(Normalized) ......................................................................................................... 357
Figure 312: Proportion of Shared MU/MFR Parcel Perimeter Bordering on MFR/MU
Uses (Normalized) ................................................................................................. 357
Figure 313: Proportion of Shared MU/PUB Parcel Perimeter Bordering on PUB/MU
Uses (Normalized) ................................................................................................. 358
Figure 314: Proportion of Shared MU/SFDR Parcel Perimeter Bordering on
SFDR/MU Uses (Normalized) ............................................................................... 358
Figure 315: Proportion of Shared MU/TCU Parcel Perimeter Bordering on TCU/MU
Uses (Normalized) ................................................................................................. 359
Figure 316: Proportion of Shared MU/UNKN Parcel Perimeter Bordering on
UNKN/MU Uses (Normalized) ............................................................................. 359
Figure 317: Proportion of Shared MU/VAC Parcel Perimeter Bordering on VAC/MU
Uses (Normalized) ................................................................................................. 360
Figure 318: Proportion of Shared MFR Parcel Perimeter Bordering on MFR Uses
(Normalized) ......................................................................................................... 360
xvii
Figure 319: Proportion of Shared MFR/PUB Parcel Perimeter Bordering on
PUB/MFR Uses (Normalized) ............................................................................... 361
Figure 320: Proportion of Shared MFR/SFDR Parcel Perimeter Bordering on
SFDR/MFR Uses (Normalized) ............................................................................. 361
Figure 321: Proportion of Shared MFR/TCU Parcel Perimeter Bordering on
TCU/MFR Uses (Normalized) ............................................................................... 362
Figure 322: Proportion of Shared MFR/UNKN Parcel Perimeter Bordering on
UNKN/MFR Uses (Normalized)............................................................................ 362
Figure 323: Proportion of Shared MFR/VAC Parcel Perimeter Bordering on
VAC/MFR Uses (Normalized) .............................................................................. 363
Figure 324: Proportion of Shared PUB Parcel Perimeter Bordering on PUB Uses
(Normalized) ......................................................................................................... 363
Figure 325: Proportion of Shared PUB/SFDR Parcel Perimeter Bordering on
SFDR/PUB Uses (Normalized) .............................................................................. 364
Figure 326: Proportion of Shared PUB/TCU Parcel Perimeter Bordering on
TCU/PUB Uses (Normalized)................................................................................ 364
Figure 327: Proportion of Shared PUB/UNKN Parcel Perimeter Bordering on
UNKN/PUB Uses (Normalized) ............................................................................ 365
Figure 328: Proportion of Shared PUB/VAC Parcel Perimeter Bordering on
VAC/PUB Uses (Normalized) ............................................................................... 365
Figure 329: Proportion of Shared SFDR Parcel Perimeter Bordering on SFDR Uses
(Normalized) ......................................................................................................... 366
Figure 330: Proportion of Shared SFDR/TCU Parcel Perimeter Bordering on
TCU/SFDR Uses (Normalized) ............................................................................. 366
Figure 331: Proportion of Shared SFDR/UNKN Parcel Perimeter Bordering on
UNKN/SFDR Uses (Normalized) .......................................................................... 367
Figure 332: Proportion of Shared SFDR/VAC Parcel Perimeter Bordering on
VAC/SFDR Uses (Normalized) ............................................................................. 367
Figure 333: Proportion of Shared TCU Parcel Perimeter Bordering on TCU Uses
(Normalized) ......................................................................................................... 368
Figure 334: Proportion of Shared TCU/UNKN Parcel Perimeter Bordering on
UNKN/TCU Uses (Normalized) ............................................................................ 368
Figure 335: Proportion of Shared TCU/VAC Parcel Perimeter Bordering on
VAC/TCU Uses (Normalized) ............................................................................... 369
Figure 336: Proportion of Shared VAC/UNKN Parcel Perimeter Bordering on
UNKN/VAC Uses (Normalized)............................................................................ 369
Figure 337: Proportion of Shared VAC Parcel Perimeter Bordering on VAC Uses
(Normalized) ......................................................................................................... 370
Figure 338: Proportion of AG Parcels Bordering AG Parcels ................................. 372
Figure 339: Proportion of COM Parcels Bordering AG Parcels .............................. 372
Figure 340: Proportion of IND Parcels Bordering AG Parcels................................ 373
Figure 341: Proportion of MMR Parcels Bordering AG Parcels ............................. 373
Figure 342: Proportion of MU Parcels Bordering AG Parcels ................................ 374
Figure 343: Proportion of MFR Parcels Bordering AG Parcels .............................. 374
Figure 344: Proportion of PUB Parcels Bordering AG Parcels ............................... 375
Figure 345: Proportion of SFDR Parcels Bordering AG Parcels ............................. 375
xviii
Figure 346: Proportion of TCU Parcels Bordering AG Parcels ............................... 376
Figure 347: Proportion of VAC Parcels Bordering AG Parcels .............................. 376
Figure 348: Proportion of AG Parcels Bordering COM Parcels .............................. 377
Figure 349: Proportion of COM Parcels Bordering COM Parcels .......................... 377
Figure 350: Proportion of IND Parcels Bordering COM Parcels ............................ 378
Figure 351: Proportion of MMR Parcels Bordering COM Parcels .......................... 378
Figure 352: Proportion of MU Parcels Bordering COM Parcels ............................. 379
Figure 353: Proportion of MFR Parcels Bordering COM Parcels ........................... 379
Figure 354: Proportion of PUB Parcels Bordering COM Parcels ............................ 380
Figure 355: Proportion of SFDR Parcels Bordering COM Parcels.......................... 380
Figure 356: Proportion of TCU Parcels Bordering COM Parcels ........................... 381
Figure 357: Proportion of VAC Parcels Bordering COM Parcels ........................... 381
Figure 358: Proportion of AG Parcels Bordering IND Parcels................................ 382
Figure 359: Proportion of COM Parcels Bordering IND Parcels ............................ 382
Figure 360: Proportion of IND Parcels Bordering IND Parcels .............................. 383
Figure 361: Proportion of MMR Parcels Bordering IND Parcels ............................ 383
Figure 362: Proportion of MU Parcels Bordering IND Parcels ............................... 384
Figure 363: Proportion of MFR Parcels Bordering IND Parcels ............................. 384
Figure 364: Proportion of PUB Parcels Bordering IND Parcels .............................. 385
Figure 365: Proportion of SFDR Parcels Bordering IND Parcels ........................... 385
Figure 366: Proportion of TCU Parcels Bordering IND Parcels ............................. 386
Figure 367: Proportion of VAC Parcels Bordering IND Parcels ............................. 386
Figure 368: Proportion of AG Parcels Bordering MMR Parcels ............................. 387
Figure 369: Proportion of COM Parcels Bordering MMR Parcels .......................... 387
Figure 370: Proportion of IND Parcels Bordering MMR Parcels ............................ 388
Figure 371: Proportion of MMR Parcels Bordering MMR Parcels ......................... 388
Figure 372: Proportion of MU Parcels Bordering MMR Parcels ............................ 389
Figure 373: Proportion of MFR Parcels Bordering MMR Parcels .......................... 389
Figure 374: Proportion of PUB Parcels Bordering MMR Parcels ........................... 390
Figure 375: Proportion of SFDR Parcels Bordering MMR Parcels ......................... 390
Figure 376: Proportion of TCU Parcels Bordering MMR Parcels ........................... 391
Figure 377: Proportion of VAC Parcels Bordering MMR Parcels .......................... 391
Figure 378: Proportion of AG Parcels Bordering MU Parcels ................................ 392
Figure 379: Proportion of COM Parcels Bordering MU Parcels ............................. 392
Figure 380: Proportion of IND Parcels Bordering MU Parcels ............................... 393
Figure 381: Proportion of MMR Parcels Bordering MU Parcels ............................ 393
Figure 382: Proportion of MU Parcels Bordering MU Parcels................................ 394
Figure 383: Proportion of MFR Parcels Bordering MU Parcels .............................. 394
Figure 384: Proportion of PUB Parcels Bordering MU Parcels .............................. 395
Figure 385: Proportion of SFDR Parcels Bordering MU Parcels ............................ 395
Figure 386: Proportion of TCU Parcels Bordering MU Parcels .............................. 396
Figure 387: Proportion of VAC Parcels Bordering MU Parcels .............................. 396
Figure 388: Proportion of AG Parcels Bordering MFR Parcels .............................. 397
Figure 389: Proportion of COM Parcels Bordering MFR Parcels ........................... 397
Figure 390: Proportion of IND Parcels Bordering MFR Parcels ............................. 398
Figure 391: Proportion of MMR Parcels Bordering MFR Parcels .......................... 398
xix
Figure 392: Proportion of MU Parcels Bordering MFR Parcels .............................. 399
Figure 393: Proportion of MFR Parcels Bordering MFR Parcels ............................ 399
Figure 394: Proportion of PUB Parcels Bordering MFR Parcels ............................ 400
Figure 395: Proportion of SFDR Parcels Bordering MFR Parcels .......................... 400
Figure 396: Proportion of TCU Parcels Bordering MFR Parcels ............................ 401
Figure 397: Proportion of VAC Parcels Bordering MFR Parcels ............................ 401
Figure 398: Proportion of AG Parcels Bordering PUB Parcels ............................... 402
Figure 399: Proportion of COM Parcels Bordering PUB Parcels ............................ 402
Figure 400: Proportion of IND Parcels Bordering PUB Parcels .............................. 403
Figure 401: Proportion of MMR Parcels Bordering PUB Parcels ........................... 403
Figure 402: Proportion of MU Parcels Bordering PUB Parcels .............................. 404
Figure 403: Proportion of MFR Parcels Bordering PUB Parcels ............................ 404
Figure 404: Proportion of PUB Parcels Bordering PUB Parcels ............................. 405
Figure 405: Proportion of SFDR Parcels Bordering PUB Parcels ........................... 405
Figure 406: Proportion of TCU Parcels Bordering PUB Parcels ............................. 406
Figure 407: Proportion of VAC Parcels Bordering PUB Parcels ............................ 406
Figure 408: Proportion of AG Parcels Bordering SFDR Parcels ............................. 407
Figure 409: Proportion of COM Parcels Bordering SFDR Parcels.......................... 407
Figure 410: Proportion of IND Parcels Bordering SFDR Parcels ........................... 408
Figure 411: Proportion of MMR Parcels Bordering SFDR Parcels ......................... 408
Figure 412: Proportion of MU Parcels Bordering SFDR Parcels ............................ 409
Figure 413: Proportion of MFR Parcels Bordering SFDR Parcels .......................... 409
Figure 414: Proportion of PUB Parcels Bordering SFDR Parcels ........................... 410
Figure 415: Proportion of SFDR Parcels Bordering SFDR Parcels ......................... 410
Figure 416: Proportion of TCU Parcels Bordering SFDR Parcels ........................... 411
Figure 417: Proportion of VAC Parcels Bordering SFDR Parcels .......................... 411
Figure 418: Proportion of AG Parcels Bordering TCU Parcels ............................... 412
Figure 419: Proportion of COM Parcels Bordering TCU Parcels ........................... 412
Figure 420: Proportion of IND Parcels Bordering TCU Parcels ............................. 413
Figure 421: Proportion of MMR Parcels Bordering TCU Parcels ........................... 413
Figure 422: Proportion of MU Parcels Bordering TCU Parcels .............................. 414
Figure 423: Proportion of MFR Parcels Bordering TCU Parcels ............................ 414
Figure 424: Proportion of PUB Parcels Bordering TCU Parcels ............................. 415
Figure 425: Proportion of SFDR Parcels Bordering TCU Parcels ........................... 415
Figure 426: Proportion of TCU Parcels Bordering TCU Parcels............................. 416
Figure 427: Proportion of VAC Parcels Bordering TCU Parcels ............................ 416
Figure 428: Proportion of AG Parcels Bordering UNKN Parcels ........................... 417
Figure 429: Proportion of COM Parcels Bordering UNKN Parcels ........................ 417
Figure 430: Proportion of IND Parcels Bordering UNKN Parcels .......................... 418
Figure 431: Proportion of MMR Parcels Bordering UNKN Parcels ....................... 418
Figure 432: Proportion of MU Parcels Bordering UNKN Parcels ........................... 419
Figure 433: Proportion of MFR Parcels Bordering UNKN Parcels ......................... 419
Figure 434: Proportion of PUB Parcels Bordering UNKN Parcels ......................... 420
Figure 435: Proportion of SFDR Parcels Bordering UNKN Parcels ....................... 420
Figure 436: Proportion of TCU Parcels Bordering UNKN Parcels ......................... 421
Figure 437: Proportion of VAC Parcels Bordering UNKN Parcels ......................... 421
xx
Figure 438: Proportion of AG Parcels Bordering VAC Parcels .............................. 422
Figure 439: Proportion of COM Parcels Bordering VAC Parcels ........................... 422
Figure 440: Proportion of IND Parcels Bordering VAC Parcels ............................. 423
Figure 441: Proportion of MMR Parcels Bordering VAC Parcels .......................... 423
Figure 442: Proportion of MU Parcels Bordering VAC Parcels .............................. 424
Figure 443: Proportion of MFR Parcels Bordering VAC Parcels ............................ 424
Figure 444: Proportion of PUB Parcels Bordering VAC Parcels ............................ 425
Figure 445: Proportion of SFDR Parcels Bordering VAC Parcels .......................... 425
Figure 446: Proportion of TCU Parcels Bordering VAC Parcels ............................ 426
Figure 447: Proportion of VAC Parcels Bordering VAC Parcels ............................ 426
Figure 448: Proportion of AG Parcels Bordering AG Parcels (Normalized) ........... 428
Figure 449: Proportion of COM Parcels Bordering AG Parcels (Normalized) ........ 428
Figure 450: Proportion of IND Parcels Bordering AG Parcels (Normalized) .......... 429
Figure 451: Proportion of MMR Parcels Bordering AG Parcels (Normalized) ....... 429
Figure 452: Proportion of MU Parcels Bordering AG Parcels (Normalized) .......... 430
Figure 453: Proportion of MFR Parcels Bordering AG Parcels (Normalized)......... 430
Figure 454: Proportion of PUB Parcels Bordering AG Parcels (Normalized) ......... 431
Figure 455: Proportion of SFDR Parcels Bordering AG Parcels (Normalized) ....... 431
Figure 456: Proportion of TCU Parcels Bordering AG Parcels (Normalized) ......... 432
Figure 457: Proportion of VAC Parcels Bordering AG Parcels (Normalized)......... 432
Figure 458: Proportion of AG Parcels Bordering COM Parcels (Normalized) ........ 433
Figure 459: Proportion of COM Parcels Bordering COM Parcels (Normalized) ..... 433
Figure 460: Proportion of IND Parcels Bordering COM Parcels (Normalized) ....... 434
Figure 461: Proportion of MMR Parcels Bordering COM Parcels (Normalized) .... 434
Figure 462: Proportion of MU Parcels Bordering COM Parcels (Normalized) ....... 435
Figure 463: Proportion of MFR Parcels Bordering COM Parcels (Normalized) ..... 435
Figure 464: Proportion of PUB Parcels Bordering COM Parcels (Normalized) ...... 436
Figure 465: Proportion of SFDR Parcels Bordering COM Parcels (Normalized) .... 436
Figure 466: Proportion of TCU Parcels Bordering COM Parcels (Normalized) ...... 437
Figure 467: Proportion of VAC Parcels Bordering COM Parcels (Normalized) ..... 437
Figure 468: Proportion of AG Parcels Bordering IND Parcels (Normalized) .......... 438
Figure 469: Proportion of COM Parcels Bordering IND Parcels (Normalized) ....... 438
Figure 470: Proportion of IND Parcels Bordering IND Parcels (Normalized)......... 439
Figure 471: Proportion of MMR Parcels Bordering IND Parcels (Normalized) ...... 439
Figure 472: Proportion of MU Parcels Bordering IND Parcels (Normalized) ......... 440
Figure 473: Proportion of MFR Parcels Bordering IND Parcels (Normalized) ....... 440
Figure 474: Proportion of PUB Parcels Bordering IND Parcels (Normalized) ........ 441
Figure 475: Proportion of SFDR Parcels Bordering IND Parcels (Normalized) ...... 441
Figure 476: Proportion of TCU Parcels Bordering IND Parcels (Normalized) ........ 442
Figure 477: Proportion of VAC Parcels Bordering IND Parcels (Normalized) ....... 442
Figure 478: Proportion of AG Parcels Bordering MMR Parcels (Normalized) ....... 443
Figure 479: Proportion of COM Parcels Bordering MMR Parcels (Normalized) .... 443
Figure 480: Proportion of IND Parcels Bordering MMR Parcels (Normalized) ...... 444
Figure 481: Proportion of MMR Parcels Bordering MMR Parcels (Normalized) ... 444
Figure 482: Proportion of MU Parcels Bordering MMR Parcels (Normalized) ....... 445
Figure 483: Proportion of MFR Parcels Bordering MMR Parcels (Normalized) ..... 445
xxi
Figure 484: Proportion of PUB Parcels Bordering MMR Parcels (Normalized) ..... 446
Figure 485: Proportion of SFDR Parcels Bordering MMR Parcels (Normalized) ... 446
Figure 486: Proportion of TCU Parcels Bordering MMR Parcels (Normalized) ..... 447
Figure 487: Proportion of VAC Parcels Bordering MMR Parcels (Normalized) ..... 447
Figure 488: Proportion of AG Parcels Bordering MU Parcels (Normalized) .......... 448
Figure 489: Proportion of COM Parcels Bordering MU Parcels (Normalized) ....... 448
Figure 490: Proportion of IND Parcels Bordering MU Parcels (Normalized) ......... 449
Figure 491: Proportion of MMR Parcels Bordering MU Parcels (Normalized) ....... 449
Figure 492: Proportion of MU Parcels Bordering MU Parcels (Normalized) .......... 450
Figure 493: Proportion of MFR Parcels Bordering MU Parcels (Normalized) ........ 450
Figure 494: Proportion of PUB Parcels Bordering MU Parcels (Normalized)......... 451
Figure 495: Proportion of SFDR Parcels Bordering MU Parcels (Normalized) ...... 451
Figure 496: Proportion of TCU Parcels Bordering MU Parcels (Normalized) ........ 452
Figure 497: Proportion of VAC Parcels Bordering MU Parcels (Normalized) ........ 452
Figure 498: Proportion of AG Parcels Bordering MFR Parcels (Normalized)......... 453
Figure 499: Proportion of COM Parcels Bordering MFR Parcels (Normalized) ..... 453
Figure 500: Proportion of IND Parcels Bordering MFR Parcels (Normalized) ....... 454
Figure 501: Proportion of MMR Parcels Bordering MFR Parcels (Normalized) ..... 454
Figure 502: Proportion of MU Parcels Bordering MFR Parcels (Normalized) ........ 455
Figure 503: Proportion of MFR Parcels Bordering MFR Parcels (Normalized) ...... 455
Figure 504: Proportion of PUB Parcels Bordering MFR Parcels (Normalized) ....... 456
Figure 505: Proportion of SFDR Parcels Bordering MFR Parcels (Normalized) .... 456
Figure 506: Proportion of TCU Parcels Bordering MFR Parcels (Normalized) ...... 457
Figure 507: Proportion of VAC Parcels Bordering MFR Parcels (Normalized) ...... 457
Figure 508: Proportion of AG Parcels Bordering PUB Parcels (Normalized) ......... 458
Figure 509: Proportion of COM Parcels Bordering PUB Parcels (Normalized) ...... 458
Figure 510: Proportion of IND Parcels Bordering PUB Parcels (Normalized) ........ 459
Figure 511: Proportion of MMR Parcels Bordering PUB Parcels (Normalized) ..... 459
Figure 512: Proportion of MU Parcels Bordering PUB Parcels (Normalized)......... 460
Figure 513: Proportion of MFR Parcels Bordering PUB Parcels (Normalized) ....... 460
Figure 514: Proportion of PUB Parcels Bordering PUB Parcels (Normalized) ....... 461
Figure 515: Proportion of SFDR Parcels Bordering PUB Parcels (Normalized) ..... 461
Figure 516: Proportion of TCU Parcels Bordering PUB Parcels (Normalized) ....... 462
Figure 517: Proportion of VAC Parcels Bordering PUB Parcels (Normalized) ....... 462
Figure 518: Proportion of AG Parcels Bordering SFDR Parcels (Normalized) ....... 463
Figure 519: Proportion of COM Parcels Bordering SFDR Parcels (Normalized) .... 463
Figure 520: Proportion of IND Parcels Bordering SFDR Parcels (Normalized) ...... 464
Figure 521: Proportion of MMR Parcels Bordering SFDR Parcels (Normalized) ... 464
Figure 522: Proportion of MU Parcels Bordering SFDR Parcels (Normalized) ...... 465
Figure 523: Proportion of MFR Parcels Bordering SFDR Parcels (Normalized) .... 465
Figure 524: Proportion of PUB Parcels Bordering SFDR Parcels (Normalized) ..... 466
Figure 525: Proportion of SFDR Parcels Bordering SFDR Parcels (Normalized) ... 466
Figure 526: Proportion of TCU Parcels Bordering SFDR Parcels (Normalized) ..... 467
Figure 527: Proportion of VAC Parcels Bordering SFDR Parcels (Normalized) .... 467
Figure 528: Proportion of AG Parcels Bordering TCU Parcels (Normalized) ......... 468
Figure 529: Proportion of COM Parcels Bordering TCU Parcels (Normalized) ...... 468
xxii
Figure 530: Proportion of IND Parcels Bordering TCU Parcels (Normalized) ........ 469
Figure 531: Proportion of MMR Parcels Bordering TCU Parcels (Normalized) ..... 469
Figure 532: Proportion of MU Parcels Bordering TCU Parcels (Normalized) ........ 470
Figure 533: Proportion of MFR Parcels Bordering TCU Parcels (Normalized) ...... 470
Figure 534: Proportion of PUB Parcels Bordering TCU Parcels (Normalized) ....... 471
Figure 535: Proportion of SFDR Parcels Bordering TCU Parcels (Normalized) ..... 471
Figure 536: Proportion of TCU Parcels Bordering TCU Parcels (Normalized) ....... 472
Figure 537: Proportion of VAC Parcels Bordering TCU Parcels (Normalized) ...... 472
Figure 538: Proportion of AG Parcels Bordering UNKN Parcels (Normalized)...... 473
Figure 539: Proportion of COM Parcels Bordering UNKN Parcels (Normalized) .. 473
Figure 540: Proportion of IND Parcels Bordering UNKN Parcels (Normalized) .... 474
Figure 541: Proportion of MMR Parcels Bordering UNKN Parcels (Normalized) .. 474
Figure 542: Proportion of MU Parcels Bordering UNKN Parcels (Normalized) ..... 475
Figure 543: Proportion of MFR Parcels Bordering UNKN Parcels (Normalized) ... 475
Figure 544: Proportion of PUB Parcels Bordering UNKN Parcels (Normalized) .... 476
Figure 545: Proportion of SFDR Parcels Bordering UNKN Parcels (Normalized) . 476
Figure 546: Proportion of TCU Parcels Bordering UNKN Parcels (Normalized) ... 477
Figure 547: Proportion of VAC Parcels Bordering UNKN Parcels (Normalized) ... 477
Figure 548: Proportion of AG Parcels Bordering VAC Parcels (Normalized)......... 478
Figure 549: Proportion of COM Parcels Bordering VAC Parcels (Normalized) ..... 478
Figure 550: Proportion of IND Parcels Bordering VAC Parcels (Normalized) ....... 479
Figure 551: Proportion of MMR Parcels Bordering VAC Parcels (Normalized) ..... 479
Figure 552: Proportion of MU Parcels Bordering VAC Parcels (Normalized) ........ 480
Figure 553: Proportion of MFR Parcels Bordering VAC Parcels (Normalized) ...... 480
Figure 554: Proportion of PUB Parcels Bordering VAC Parcels (Normalized) ....... 481
Figure 555: Proportion of SFDR Parcels Bordering VAC Parcels (Normalized) .... 481
Figure 556: Proportion of TCU Parcels Bordering VAC Parcels (Normalized) ...... 482
Figure 557: Proportion of VAC Parcels Bordering VAC Parcels (Normalized) ...... 482
Figure 558: Proportion of AG Parcels Bordering Only Other AG Parcels .............. 483
Figure 559: Proportion of COM Parcels Bordering Only Other COM Parcels ........ 484
Figure 560: Proportion of IND Parcels Bordering Only Other IND Parcels ............ 484
Figure 561: Proportion of MMR Parcels Bordering Only Other MMR Parcels ....... 485
Figure 562: Proportion of MU Parcels Bordering Only Other MU Parcels ............. 485
Figure 563: Proportion of MFR Parcels Bordering Only Other MFR Parcels ......... 486
Figure 564: Proportion of PUB Parcels Bordering Only Other PUB Parcels........... 486
Figure 565: Proportion of SFDR Parcels Bordering Only Other SFDR Parcels ...... 487
Figure 566: Proportion of TCU Parcels Bordering Only Other TCU Parcels .......... 487
Figure 567: Proportion of UNKN Parcels Bordering Only Other UNKN Parcels ... 488
Figure 568: Proportion of VAC Parcels Bordering Only Other VAC Parcels ......... 488
Figure 569: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to AG
Uses ...................................................................................................................... 490
Figure 570: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
COM Uses ............................................................................................................. 490
Figure 571: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
IND Uses ............................................................................................................... 491
xxiii
Figure 572: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
MMR Uses ............................................................................................................ 491
Figure 573: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to MU
Uses ...................................................................................................................... 492
Figure 574: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
MFR Uses ............................................................................................................. 492
Figure 575: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
PUB Uses .............................................................................................................. 493
Figure 576: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
SFDR Uses ............................................................................................................ 493
Figure 577: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
TCU Uses .............................................................................................................. 494
Figure 578: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
UNKN Uses .......................................................................................................... 494
Figure 579: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
VAC Uses ............................................................................................................. 495
Figure 580: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
AG Uses ................................................................................................................ 495
Figure 581: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
COM Uses ............................................................................................................. 496
Figure 582: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
IND Uses ............................................................................................................... 496
Figure 583: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
MMR Uses ............................................................................................................ 497
Figure 584: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
MU Uses ............................................................................................................... 497
Figure 585: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
MFR Uses ............................................................................................................. 498
Figure 586: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
PUB Uses .............................................................................................................. 498
Figure 587: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
SFDR Uses ............................................................................................................ 499
Figure 588: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
TCU Uses .............................................................................................................. 499
Figure 589: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
UNKN Uses .......................................................................................................... 500
Figure 590: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
VAC Uses ............................................................................................................. 500
Figure 591: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
AG Uses ................................................................................................................ 501
Figure 592: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
COM Uses ............................................................................................................. 501
Figure 593: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
IND Uses ............................................................................................................... 502
Figure 594: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
MMR Uses ............................................................................................................ 502
xxiv
Figure 595: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
MU Uses ............................................................................................................... 503
Figure 596: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
MFR Uses ............................................................................................................. 503
Figure 597: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
PUB Uses .............................................................................................................. 504
Figure 598: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
SFDR Uses ............................................................................................................ 504
Figure 599: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
TCU Uses .............................................................................................................. 505
Figure 600: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
UNKN Uses .......................................................................................................... 505
Figure 601: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
VAC Uses ............................................................................................................. 506
Figure 602: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
AG Uses ................................................................................................................ 506
Figure 603: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
COM Uses ............................................................................................................. 507
Figure 604: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
IND Uses ............................................................................................................... 507
Figure 605: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
MMR Uses ............................................................................................................ 508
Figure 606: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
MU Uses ............................................................................................................... 508
Figure 607: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
MFR Uses ............................................................................................................. 509
Figure 608: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
PUB Uses .............................................................................................................. 509
Figure 609: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
SFDR Uses ............................................................................................................ 510
Figure 610: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
TCU Uses .............................................................................................................. 510
Figure 611: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
UNKN Uses .......................................................................................................... 511
Figure 612: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
VAC Uses ............................................................................................................. 511
Figure 613: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to AG
Uses ...................................................................................................................... 512
Figure 614: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
COM Uses ............................................................................................................. 512
Figure 615: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
IND Uses ............................................................................................................... 513
Figure 616: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
MMR Uses ............................................................................................................ 513
Figure 617: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
MU Uses ............................................................................................................... 514
xxv
Figure 618: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
MFR Uses ............................................................................................................. 514
Figure 619: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
PUB Uses .............................................................................................................. 515
Figure 620: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
SFDR Uses ............................................................................................................ 515
Figure 621: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
TCU Uses .............................................................................................................. 516
Figure 622: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
UNKN Uses .......................................................................................................... 516
Figure 623: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
VAC Uses ............................................................................................................. 517
Figure 624: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
AG Uses ................................................................................................................ 517
Figure 625: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
COM Uses ............................................................................................................. 518
Figure 626: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
IND Uses ............................................................................................................... 518
Figure 627: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
MMR Uses ............................................................................................................ 519
Figure 628: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
MU Uses ............................................................................................................... 519
Figure 629: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
MFR Uses ............................................................................................................. 520
Figure 630: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
PUB Uses .............................................................................................................. 520
Figure 631: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
SFDR Uses ............................................................................................................ 521
Figure 632: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
TCU Uses .............................................................................................................. 521
Figure 633: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
UNKN Uses .......................................................................................................... 522
Figure 634: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
VAC Uses ............................................................................................................. 522
Figure 635: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
AG Uses ................................................................................................................ 523
Figure 636: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
COM Uses ............................................................................................................. 523
Figure 637: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
IND Uses ............................................................................................................... 524
Figure 638: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
MMR Uses ............................................................................................................ 524
Figure 639: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
MU Uses ............................................................................................................... 525
Figure 640: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
MFR Uses ............................................................................................................. 525
xxvi
Figure 641: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
PUB Uses .............................................................................................................. 526
Figure 642: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
SFDR Uses ............................................................................................................ 526
Figure 643: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
TCU Uses .............................................................................................................. 527
Figure 644: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
UNKN Uses .......................................................................................................... 527
Figure 645: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
VAC Uses ............................................................................................................. 528
Figure 646: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
AG Uses ................................................................................................................ 528
Figure 647: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
COM Uses ............................................................................................................. 529
Figure 648: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
IND Uses ............................................................................................................... 529
Figure 649: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
MMR Uses ............................................................................................................ 530
Figure 650: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
MU Uses ............................................................................................................... 530
Figure 651: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
MFR Uses ............................................................................................................. 531
Figure 652: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
PUB Uses .............................................................................................................. 531
Figure 653: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
SFDR Uses ............................................................................................................ 532
Figure 654: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
TCU Uses .............................................................................................................. 532
Figure 655: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
UNKN Uses .......................................................................................................... 533
Figure 656: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
VAC Uses ............................................................................................................. 533
Figure 657: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
AG Uses ................................................................................................................ 534
Figure 658: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
COM Uses ............................................................................................................. 534
Figure 659: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
IND Uses ............................................................................................................... 535
Figure 660: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
MMR Uses ............................................................................................................ 535
Figure 661: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
MU Uses ............................................................................................................... 536
Figure 662: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
MFR Uses ............................................................................................................. 536
Figure 663: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
PUB Uses .............................................................................................................. 537
xxvii
Figure 664: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
SFDR Uses ............................................................................................................ 537
Figure 665: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
TCU Uses .............................................................................................................. 538
Figure 666: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
UNKN Uses .......................................................................................................... 538
Figure 667: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
VAC Uses ............................................................................................................. 539
Figure 668: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
AG Uses ................................................................................................................ 539
Figure 669: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
COM Uses ............................................................................................................. 540
Figure 670: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
IND Uses ............................................................................................................... 540
Figure 671: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
MMR Uses ............................................................................................................ 541
Figure 672: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
MU Uses ............................................................................................................... 541
Figure 673: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
MFR Uses ............................................................................................................. 542
Figure 674: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
PUB Uses .............................................................................................................. 542
Figure 675: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
SFDR Uses ............................................................................................................ 543
Figure 676: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
TCU Uses .............................................................................................................. 543
Figure 677: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
UNKN Uses .......................................................................................................... 544
Figure 678: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
VAC Uses ............................................................................................................. 544
Figure 679: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
AG Uses ................................................................................................................ 545
Figure 680: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
COM Uses ............................................................................................................. 545
Figure 681: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
IND Uses ............................................................................................................... 546
Figure 682: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
MMR Uses ............................................................................................................ 546
Figure 683: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
MU Uses ............................................................................................................... 547
Figure 684: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
MFR Uses ............................................................................................................. 547
Figure 685: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
PUB Uses .............................................................................................................. 548
Figure 686: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
SFDR Uses ............................................................................................................ 548
xxviii
Figure 687: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
TCU Uses .............................................................................................................. 549
Figure 688: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
UNKN Uses .......................................................................................................... 549
Figure 689: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
VAC Uses ............................................................................................................. 550
Figure 690: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to AG
Uses (Normalized) ................................................................................................. 552
Figure 691: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 552
Figure 692: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 553
Figure 693: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 553
Figure 694: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to MU
Uses (Normalized) ................................................................................................. 554
Figure 695: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 554
Figure 696: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 555
Figure 697: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 555
Figure 698: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 556
Figure 699: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 556
Figure 700: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 557
Figure 701: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 557
Figure 702: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 558
Figure 703: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 558
Figure 704: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 559
Figure 705: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 559
Figure 706: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 560
Figure 707: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 560
Figure 708: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 561
Figure 709: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 561
xxix
Figure 710: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 562
Figure 711: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 562
Figure 712: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 563
Figure 713: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 563
Figure 714: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 564
Figure 715: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 564
Figure 716: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 565
Figure 717: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 565
Figure 718: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 566
Figure 719: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 566
Figure 720: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 567
Figure 721: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 567
Figure 722: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 568
Figure 723: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 568
Figure 724: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 569
Figure 725: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 569
Figure 726: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 570
Figure 727: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 570
Figure 728: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 571
Figure 729: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 571
Figure 730: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 572
Figure 731: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 572
Figure 732: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 573
xxx
Figure 733: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 573
Figure 734: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to AG
Uses (Normalized) ................................................................................................. 574
Figure 735: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 574
Figure 736: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 575
Figure 737: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 575
Figure 738: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 576
Figure 739: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 576
Figure 740: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 577
Figure 741: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 577
Figure 742: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 578
Figure 743: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 578
Figure 744: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 579
Figure 745: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 579
Figure 746: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 580
Figure 747: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 580
Figure 748: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 581
Figure 749: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 581
Figure 750: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 582
Figure 751: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 582
Figure 752: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 583
Figure 753: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 583
Figure 754: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 584
Figure 755: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 584
xxxi
Figure 756: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 585
Figure 757: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 585
Figure 758: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 586
Figure 759: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 586
Figure 760: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 587
Figure 761: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 587
Figure 762: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 588
Figure 763: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 588
Figure 764: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 589
Figure 765: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 589
Figure 766: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 590
Figure 767: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 590
Figure 768: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 591
Figure 769: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 591
Figure 770: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 592
Figure 771: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 592
Figure 772: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 593
Figure 773: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 593
Figure 774: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 594
Figure 775: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 594
Figure 776: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 595
Figure 777: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 595
Figure 778: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 596
xxxii
Figure 779: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 596
Figure 780: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 597
Figure 781: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 597
Figure 782: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 598
Figure 783: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 598
Figure 784: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 599
Figure 785: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 599
Figure 786: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 600
Figure 787: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 600
Figure 788: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 601
Figure 789: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 601
Figure 790: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 602
Figure 791: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 602
Figure 792: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 603
Figure 793: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 603
Figure 794: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 604
Figure 795: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 604
Figure 796: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 605
Figure 797: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 605
Figure 798: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 606
Figure 799: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 606
Figure 800: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
AG Uses (Normalized) .......................................................................................... 607
Figure 801: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
COM Uses (Normalized) ....................................................................................... 607
xxxiii
Figure 802: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
IND Uses (Normalized) ......................................................................................... 608
Figure 803: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
MMR Uses (Normalized) ...................................................................................... 608
Figure 804: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
MU Uses (Normalized) .......................................................................................... 609
Figure 805: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
MFR Uses (Normalized) ........................................................................................ 609
Figure 806: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
PUB Uses (Normalized) ........................................................................................ 610
Figure 807: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
SFDR Uses (Normalized) ...................................................................................... 610
Figure 808: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
TCU Uses (Normalized) ........................................................................................ 611
Figure 809: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
UNKN Uses (Normalized) ..................................................................................... 611
Figure 810: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to
VAC Uses (Normalized) ........................................................................................ 612
Figure 811: Proportion of AG Parcels Within 500 Feet of AG Parcels ................... 614
Figure 812: Proportion of COM Parcels Within 500 Feet of AG Parcels ................ 614
Figure 813: Proportion of IND Parcels Within 500 Feet of AG Parcels .................. 615
Figure 814: Proportion of MMR Parcels Within 500 Feet of AG Parcels ............... 615
Figure 815: Proportion of MU Parcels Within 500 Feet of AG Parcels................... 616
Figure 816: Proportion of MFR Parcels Within 500 Feet of AG Parcels ................. 616
Figure 817: Proportion of PUB Parcels Within 500 Feet of AG Parcels ................. 617
Figure 818: Proportion of SFDR Parcels Within 500 Feet of AG Parcels ............... 617
Figure 819: Proportion of TCU Parcels Within 500 Feet of AG Parcels ................. 618
Figure 820: Proportion of VAC Parcels Within 500 Feet of AG Parcels ................. 618
Figure 821: Proportion of AG Parcels Within 500 Feet of COM Parcels ................ 619
Figure 822: Proportion of COM Parcels Within 500 Feet of COM Parcels ............. 619
Figure 823: Proportion of IND Parcels Within 500 Feet of COM Parcels ............... 620
Figure 824: Proportion of MMR Parcels Within 500 Feet of COM Parcels ............ 620
Figure 825: Proportion of MU Parcels Within 500 Feet of COM Parcels ............... 621
Figure 826: Proportion of MFR Parcels Within 500 Feet of COM Parcels ............. 621
Figure 827: Proportion of PUB Parcels Within 500 Feet of COM Parcels .............. 622
Figure 828: Proportion of SFDR Parcels Within 500 Feet of COM Parcels ............ 622
Figure 829: Proportion of TCU Parcels Within 500 Feet of COM Parcels .............. 623
Figure 830: Proportion of VAC Parcels Within 500 Feet of COM Parcels ............. 623
Figure 831: Proportion of AG Parcels Within 500 Feet of IND Parcels .................. 624
Figure 832: Proportion of COM Parcels Within 500 Feet of IND Parcels ............... 624
Figure 833: Proportion of IND Parcels Within 500 Feet of IND Parcels ................. 625
Figure 834: Proportion of MMR Parcels Within 500 Feet of IND Parcels .............. 625
Figure 835: Proportion of MU Parcels Within 500 Feet of IND Parcels ................. 626
Figure 836: Proportion of MFR Parcels Within 500 Feet of IND Parcels ............... 626
Figure 837: Proportion of PUB Parcels Within 500 Feet of IND Parcels ................ 627
Figure 838: Proportion of SFDR Parcels Within 500 Feet of IND Parcels .............. 627
xxxiv
Figure 839: Proportion of TCU Parcels Within 500 Feet of IND Parcels ................ 628
Figure 840: Proportion of VAC Parcels Within 500 Feet of IND Parcels ............... 628
Figure 841: Proportion of AG Parcels Within 500 Feet of MMR Parcels ............... 629
Figure 842: Proportion of COM Parcels Within 500 Feet of MMR Parcels ............ 629
Figure 843: Proportion of IND Parcels Within 500 Feet of MMR Parcels .............. 630
Figure 844: Proportion of MMR Parcels Within 500 Feet of MMR Parcels............ 630
Figure 845: Proportion of MU Parcels Within 500 Feet of MMR Parcels ............... 631
Figure 846: Proportion of MFR Parcels Within 500 Feet of MMR Parcels ............. 631
Figure 847: Proportion of PUB Parcels Within 500 Feet of MMR Parcels ............. 632
Figure 848: Proportion of SFDR Parcels Within 500 Feet of MMR Parcels ........... 632
Figure 849: Proportion of TCU Parcels Within 500 Feet of MMR Parcels ............. 633
Figure 850: Proportion of VAC Parcels Within 500 Feet of MMR Parcels ............. 633
Figure 851: Proportion of AG Parcels Within 500 Feet of MU Parcels ................... 634
Figure 852: Proportion of COM Parcels Within 500 Feet of MU Parcels ............... 634
Figure 853: Proportion of IND Parcels Within 500 Feet of MU Parcels ................. 635
Figure 854: Proportion of MMR Parcels Within 500 Feet of MU Parcels ............... 635
Figure 855: Proportion of MU Parcels Within 500 Feet of MU Parcels .................. 636
Figure 856: Proportion of MFR Parcels Within 500 Feet of MU Parcels ................ 636
Figure 857: Proportion of PUB Parcels Within 500 Feet of MU Parcels ................. 637
Figure 858: Proportion of SFDR Parcels Within 500 Feet of MU Parcels .............. 637
Figure 859: Proportion of TCU Parcels Within 500 Feet of MU Parcels ................ 638
Figure 860: Proportion of VAC Parcels Within 500 Feet of MU Parcels ................ 638
Figure 861: Proportion of AG Parcels Within 500 Feet of MFR Parcels ................. 639
Figure 862: Proportion of COM Parcels Within 500 Feet of MFR Parcels ............. 639
Figure 863: Proportion of IND Parcels Within 500 Feet of MFR Parcels ............... 640
Figure 864: Proportion of MMR Parcels Within 500 Feet of MFR Parcels ............. 640
Figure 865: Proportion of MU Parcels Within 500 Feet of MFR Parcels ................ 641
Figure 866: Proportion of MFR Parcels Within 500 Feet of MFR Parcels .............. 641
Figure 867: Proportion of PUB Parcels Within 500 Feet of MFR Parcels ............... 642
Figure 868: Proportion of SFDR Parcels Within 500 Feet of MFR Parcels............. 642
Figure 869: Proportion of TCU Parcels Within 500 Feet of MFR Parcels .............. 643
Figure 870: Proportion of VAC Parcels Within 500 Feet of MFR Parcels .............. 643
Figure 871: Proportion of AG Parcels Within 500 Feet of PUB Parcels ................. 644
Figure 872: Proportion of COM Parcels Within 500 Feet of PUB Parcels .............. 644
Figure 873: Proportion of IND Parcels Within 500 Feet of PUB Parcels ................ 645
Figure 874: Proportion of MMR Parcels Within 500 Feet of PUB Parcels ............. 645
Figure 875: Proportion of MU Parcels Within 500 Feet of PUB Parcels ................. 646
Figure 876: Proportion of MFR Parcels Within 500 Feet of PUB Parcels ............... 646
Figure 877: Proportion of PUB Parcels Within 500 Feet of PUB Parcels ............... 647
Figure 878: Proportion of SFDR Parcels Within 500 Feet of PUB Parcels ............. 647
Figure 879: Proportion of TCU Parcels Within 500 Feet of PUB Parcels ............... 648
Figure 880: Proportion of VAC Parcels Within 500 Feet of PUB Parcels ............... 648
Figure 881: Proportion of AG Parcels Within 500 Feet of SFDR Parcels ............... 649
Figure 882: Proportion of COM Parcels Within 500 Feet of SFDR Parcels ............ 649
Figure 883: Proportion of IND Parcels Within 500 Feet of SFDR Parcels .............. 650
Figure 884: Proportion of MMR Parcels Within 500 Feet of SFDR Parcels ........... 650
xxxv
Figure 885: Proportion of MU Parcels Within 500 Feet of SFDR Parcels .............. 651
Figure 886: Proportion of MFR Parcels Within 500 Feet of SFDR Parcels ............. 651
Figure 887: Proportion of PUB Parcels Within 500 Feet of SFDR Parcels ............. 652
Figure 888: Proportion of SFDR Parcels Within 500 Feet of SFDR Parcels ........... 652
Figure 889: Proportion of TCU Parcels Within 500 Feet of SFDR Parcels ............. 653
Figure 890: Proportion of VAC Parcels Within 500 Feet of SFDR Parcels ............. 653
Figure 891: Proportion of AG Parcels Within 500 Feet of TCU Parcels ................. 654
Figure 892: Proportion of COM Parcels Within 500 Feet of TCU Parcels .............. 654
Figure 893: Proportion of IND Parcels Within 500 Feet of TCU Parcels ................ 655
Figure 894: Proportion of MMR Parcels Within 500 Feet of TCU Parcels ............. 655
Figure 895: Proportion of MU Parcels Within 500 Feet of TCU Parcels ................ 656
Figure 896: Proportion of MFR Parcels Within 500 Feet of TCU Parcels............... 656
Figure 897: Proportion of PUB Parcels Within 500 Feet of TCU Parcels ............... 657
Figure 898: Proportion of SFDR Parcels Within 500 Feet of TCU Parcels ............. 657
Figure 899: Proportion of TCU Parcels Within 500 Feet of TCU Parcels ............... 658
Figure 900: Proportion of VAC Parcels Within 500 Feet of TCU Parcels............... 658
Figure 901: Proportion of AG Parcels Within 500 Feet of UNKN Parcels .............. 659
Figure 902: Proportion of COM Parcels Within 500 Feet of UNKN Parcels........... 659
Figure 903: Proportion of IND Parcels Within 500 Feet of UNKN Parcels ............ 660
Figure 904: Proportion of MMR Parcels Within 500 Feet of UNKN Parcels .......... 660
Figure 905: Proportion of MU Parcels Within 500 Feet of UNKN Parcels ............. 661
Figure 906: Proportion of MFR Parcels Within 500 Feet of UNKN Parcels ........... 661
Figure 907: Proportion of PUB Parcels Within 500 Feet of UNKN Parcels ............ 662
Figure 908: Proportion of SFDR Parcels Within 500 Feet of UNKN Parcels .......... 662
Figure 909: Proportion of TCU Parcels Within 500 Feet of UNKN Parcels............ 663
Figure 910: Proportion of VAC Parcels Within 500 Feet of UNKN Parcels ........... 663
Figure 911: Proportion of AG Parcels Within 500 Feet of VAC Parcels ................. 664
Figure 912: Proportion of COM Parcels Within 500 Feet of VAC Parcels ............. 664
Figure 913: Proportion of IND Parcels Within 500 Feet of VAC Parcels ............... 665
Figure 914: Proportion of MMR Parcels Within 500 Feet of VAC Parcels ............. 665
Figure 915: Proportion of MU Parcels Within 500 Feet of VAC Parcels ................ 666
Figure 916: Proportion of MFR Parcels Within 500 Feet of VAC Parcels .............. 666
Figure 917: Proportion of PUB Parcels Within 500 Feet of VAC Parcels ............... 667
Figure 918: Proportion of SFDR Parcels Within 500 Feet of VAC Parcels............. 667
Figure 919: Proportion of TCU Parcels Within 500 Feet of VAC Parcels .............. 668
Figure 920: Proportion of VAC Parcels Within 500 Feet of VAC Parcels .............. 668
Figure 921: Proportion of AG Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 670
Figure 922: Proportion of COM Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 670
Figure 923: Proportion of IND Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 671
Figure 924: Proportion of MMR Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 671
Figure 925: Proportion of MU Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 672
xxxvi
Figure 926: Proportion of MFR Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 672
Figure 927: Proportion of PUB Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 673
Figure 928: Proportion of SFDR Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 673
Figure 929: Proportion of TCU Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 674
Figure 930: Proportion of VAC Parcels Within 500 Feet of AG Parcels (Normalized)
 .............................................................................................................................. 674
Figure 931: Proportion of AG Parcels Within 500 Feet of COM Parcels (Normalized)
 .............................................................................................................................. 675
Figure 932: Proportion of COM Parcels Within 500 Feet of COM Parcels
(Normalized) ......................................................................................................... 675
Figure 933: Proportion of IND Parcels Within 500 Feet of COM Parcels
(Normalized) ......................................................................................................... 676
Figure 934: Proportion of MMR Parcels Within 500 Feet of COM Parcels
(Normalized) ......................................................................................................... 676
Figure 935: Proportion of MU Parcels Within 500 Feet of COM Parcels (Normalized)
 .............................................................................................................................. 677
Figure 936: Proportion of MFR Parcels Within 500 Feet of COM Parcels
(Normalized) ......................................................................................................... 677
Figure 937: Proportion of PUB Parcels Within 500 Feet of COM Parcels
(Normalized) ......................................................................................................... 678
Figure 938: Proportion of SFDR Parcels Within 500 Feet of COM Parcels
(Normalized) ......................................................................................................... 678
Figure 939: Proportion of TCU Parcels Within 500 Feet of COM Parcels
(Normalized) ......................................................................................................... 679
Figure 940: Proportion of VAC Parcels Within 500 Feet of COM Parcels
(Normalized) ......................................................................................................... 679
Figure 941: Proportion of AG Parcels Within 500 Feet of IND Parcels (Normalized)
 .............................................................................................................................. 680
Figure 942: Proportion of COM Parcels Within 500 Feet of IND Parcels
(Normalized) ......................................................................................................... 680
Figure 943: Proportion of IND Parcels Within 500 Feet of IND Parcels (Normalized)
 .............................................................................................................................. 681
Figure 944: Proportion of MMR Parcels Within 500 Feet of IND Parcels
(Normalized) ......................................................................................................... 681
Figure 945: Proportion of MU Parcels Within 500 Feet of IND Parcels (Normalized)
 .............................................................................................................................. 682
Figure 946: Proportion of MFR Parcels Within 500 Feet of IND Parcels (Normalized)
 .............................................................................................................................. 682
Figure 947: Proportion of PUB Parcels Within 500 Feet of IND Parcels (Normalized)
 .............................................................................................................................. 683
Figure 948: Proportion of SFDR Parcels Within 500 Feet of IND Parcels
(Normalized) ......................................................................................................... 683
xxxvii
Figure 949: Proportion of TCU Parcels Within 500 Feet of IND Parcels (Normalized)
 .............................................................................................................................. 684
Figure 950: Proportion of VAC Parcels Within 500 Feet of IND Parcels (Normalized)
 .............................................................................................................................. 684
Figure 951: Proportion of AG Parcels Within 500 Feet of MMR Parcels (Normalized)
 .............................................................................................................................. 685
Figure 952: Proportion of COM Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 685
Figure 953: Proportion of IND Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 686
Figure 954: Proportion of MMR Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 686
Figure 955: Proportion of MU Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 687
Figure 956: Proportion of MFR Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 687
Figure 957: Proportion of PUB Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 688
Figure 958: Proportion of SFDR Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 688
Figure 959: Proportion of TCU Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 689
Figure 960: Proportion of VAC Parcels Within 500 Feet of MMR Parcels
(Normalized) ......................................................................................................... 689
Figure 961: Proportion of AG Parcels Within 500 Feet of MU Parcels (Normalized)
 .............................................................................................................................. 690
Figure 962: Proportion of COM Parcels Within 500 Feet of MU Parcels (Normalized)
 .............................................................................................................................. 690
Figure 963: Proportion of IND Parcels Within 500 Feet of MU Parcels (Normalized)
 .............................................................................................................................. 691
Figure 964: Proportion of MMR Parcels Within 500 Feet of MU Parcels
(Normalized) ......................................................................................................... 691
Figure 965: Proportion of MU Parcels Within 500 Feet of MU Parcels (Normalized)
 .............................................................................................................................. 692
Figure 966: Proportion of MFR Parcels Within 500 Feet of MU Parcels (Normalized)
 .............................................................................................................................. 692
Figure 967: Proportion of PUB Parcels Within 500 Feet of MU Parcels (Normalized)
 .............................................................................................................................. 693
Figure 968: Proportion of SFDR Parcels Within 500 Feet of MU Parcels
(Normalized) ......................................................................................................... 693
Figure 969: Proportion of TCU Parcels Within 500 Feet of MU Parcels (Normalized)
 .............................................................................................................................. 694
Figure 970: Proportion of VAC Parcels Within 500 Feet of MU Parcels (Normalized)
 .............................................................................................................................. 694
Figure 971: Proportion of AG Parcels Within 500 Feet of MFR Parcels (Normalized)
 .............................................................................................................................. 695
xxxviii
Figure 972: Proportion of COM Parcels Within 500 Feet of MFR Parcels
(Normalized) ......................................................................................................... 695
Figure 973: Proportion of IND Parcels Within 500 Feet of MFR Parcels (Normalized)
 .............................................................................................................................. 696
Figure 974: Proportion of MMR Parcels Within 500 Feet of MFR Parcels
(Normalized) ......................................................................................................... 696
Figure 975: Proportion of MU Parcels Within 500 Feet of MFR Parcels (Normalized)
 .............................................................................................................................. 697
Figure 976: Proportion of MFR Parcels Within 500 Feet of MFR Parcels
(Normalized) ......................................................................................................... 697
Figure 977: Proportion of PUB Parcels Within 500 Feet of MFR Parcels
(Normalized) ......................................................................................................... 698
Figure 978: Proportion of SFDR Parcels Within 500 Feet of MFR Parcels
(Normalized) ......................................................................................................... 698
Figure 979: Proportion of TCU Parcels Within 500 Feet of MFR Parcels
(Normalized) ......................................................................................................... 699
Figure 980: Proportion of VAC Parcels Within 500 Feet of MFR Parcels
(Normalized) ......................................................................................................... 699
Figure 981: Proportion of AG Parcels Within 500 Feet of PUB Parcels (Normalized)
 .............................................................................................................................. 700
Figure 982: Proportion of COM Parcels Within 500 Feet of PUB Parcels
(Normalized) ......................................................................................................... 700
Figure 983: Proportion of IND Parcels Within 500 Feet of PUB Parcels (Normalized)
 .............................................................................................................................. 701
Figure 984: Proportion of MMR Parcels Within 500 Feet of PUB Parcels
(Normalized) ......................................................................................................... 701
Figure 985: Proportion of MU Parcels Within 500 Feet of PUB Parcels (Normalized)
 .............................................................................................................................. 702
Figure 986: Proportion of MFR Parcels Within 500 Feet of PUB Parcels
(Normalized) ......................................................................................................... 702
Figure 987: Proportion of PUB Parcels Within 500 Feet of PUB Parcels (Normalized)
 .............................................................................................................................. 703
Figure 988: Proportion of SFDR Parcels Within 500 Feet of PUB Parcels
(Normalized) ......................................................................................................... 703
Figure 989: Proportion of TCU Parcels Within 500 Feet of PUB Parcels (Normalized)
 .............................................................................................................................. 704
Figure 990: Proportion of VAC Parcels Within 500 Feet of PUB Parcels
(Normalized) ......................................................................................................... 704
Figure 991: Proportion of AG Parcels Within 500 Feet of SFDR Parcels (Normalized)
 .............................................................................................................................. 705
Figure 992: Proportion of COM Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 705
Figure 993: Proportion of IND Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 706
Figure 994: Proportion of MMR Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 706
xxxix
Figure 995: Proportion of MU Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 707
Figure 996: Proportion of MFR Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 707
Figure 997: Proportion of PUB Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 708
Figure 998: Proportion of SFDR Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 708
Figure 999: Proportion of TCU Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 709
Figure 1000: Proportion of VAC Parcels Within 500 Feet of SFDR Parcels
(Normalized) ......................................................................................................... 709
Figure 1001: Proportion of AG Parcels Within 500 Feet of TCU Parcels (Normalized)
 .............................................................................................................................. 710
Figure 1002: Proportion of COM Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 710
Figure 1003: Proportion of IND Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 711
Figure 1004: Proportion of MMR Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 711
Figure 1005: Proportion of MU Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 712
Figure 1006: Proportion of MFR Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 712
Figure 1007: Proportion of PUB Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 713
Figure 1008: Proportion of SFDR Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 713
Figure 1009: Proportion of TCU Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 714
Figure 1010: Proportion of VAC Parcels Within 500 Feet of TCU Parcels
(Normalized) ......................................................................................................... 714
Figure 1011: Proportion of AG Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 715
Figure 1012: Proportion of COM Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 715
Figure 1013: Proportion of IND Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 716
Figure 1014: Proportion of MMR Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 716
Figure 1015: Proportion of MU Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 717
Figure 1016: Proportion of MFR Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 717
Figure 1017: Proportion of PUB Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 718
xl
Figure 1018: Proportion of SFDR Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 718
Figure 1019: Proportion of TCU Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 719
Figure 1020: Proportion of VAC Parcels Within 500 Feet of UNKN Parcels
(Normalized) ......................................................................................................... 719
Figure 1021: Proportion of AG Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 720
Figure 1022: Proportion of COM Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 720
Figure 1023: Proportion of IND Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 721
Figure 1024: Proportion of MMR Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 721
Figure 1025: Proportion of MU Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 722
Figure 1026: Proportion of MFR Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 722
Figure 1027: Proportion of PUB Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 723
Figure 1028: Proportion of SFDR Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 723
Figure 1029: Proportion of TCU Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 724
Figure 1030: Proportion of VAC Parcels Within 500 Feet of VAC Parcels
(Normalized) ......................................................................................................... 724
Figure 1031: Proportion of AG Parcels with Zero Other Land Uses Within 500 Feet
 .............................................................................................................................. 726
Figure 1032: Proportion of AG Parcels with One Other Land Use Within 500 Feet 726
Figure 1033: Proportion of AG Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 727
Figure 1034: Proportion of AG Parcels with Three Other Land Uses Within 500 Feet
 .............................................................................................................................. 727
Figure 1035: Proportion of AG Parcels with Four Other Land Uses Within 500 Feet
 .............................................................................................................................. 728
Figure 1036: Proportion of AG Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 728
Figure 1037: Proportion of AG Parcels with Six Other Land Uses Within 500 Feet729
Figure 1038: Proportion of AG Parcels with Seven Other Land Uses Within 500 Feet
 .............................................................................................................................. 729
Figure 1039: Proportion of AG Parcels with Eight Other Land Uses Within 500 Feet
 .............................................................................................................................. 730
Figure 1040: Proportion of COM Parcels with Zero Other Land Uses Within 500 Feet
 .............................................................................................................................. 730
Figure 1041: Proportion of COM Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 731
xli
Figure 1042: Proportion of COM Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 731
Figure 1043: Proportion of COM Parcels with Three Other Land Uses Within 500
Feet ....................................................................................................................... 732
Figure 1044: Proportion of COM Parcels with Four Other Land Uses Within 500 Feet
 .............................................................................................................................. 732
Figure 1045: Proportion of COM Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 733
Figure 1046: Proportion of COM Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 733
Figure 1047: Proportion of COM Parcels with Seven Other Land Uses Within 500
Feet ....................................................................................................................... 734
Figure 1048: Proportion of COM Parcels with Eight Other Land Uses Within 500
Feet ....................................................................................................................... 734
Figure 1049: Proportion of IND Parcels with Zero Other Land Uses Within 500 Feet
 .............................................................................................................................. 735
Figure 1050: Proportion of IND Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 735
Figure 1051: Proportion of IND Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 736
Figure 1052: Proportion of IND Parcels with Three Other Land Uses Within 500 Feet
 .............................................................................................................................. 736
Figure 1053: Proportion of IND Parcels with Four Other Land Uses Within 500 Feet
 .............................................................................................................................. 737
Figure 1054: Proportion of IND Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 737
Figure 1055: Proportion of IND Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 738
Figure 1056: Proportion of IND Parcels with Seven Other Land Uses Within 500 Feet
 .............................................................................................................................. 738
Figure 1057: Proportion of IND Parcels with Eight Other Land Uses Within 500 Feet
 .............................................................................................................................. 739
Figure 1058: Proportion of MMR Parcels with Zero Other Land Uses Within 500
Feet ....................................................................................................................... 739
Figure 1059: Proportion of MMR Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 740
Figure 1060: Proportion of MMR Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 740
Figure 1061: Proportion of MMR Parcels with Three Other Land Uses Within 500
Feet ....................................................................................................................... 741
Figure 1062: Proportion of MMR Parcels with Four Other Land Uses Within 500
Feet ....................................................................................................................... 741
Figure 1063: Proportion of MMR Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 742
Figure 1064: Proportion of MMR Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 742
xlii
Figure 1065: Proportion of MMR Parcels with Seven Other Land Uses Within 500
Feet ....................................................................................................................... 743
Figure 1066: Proportion of MMR Parcels with Eight Other Land Uses Within 500
Feet ....................................................................................................................... 743
Figure 1067: Proportion of MU Parcels with Zero Other Land Uses Within 500 Feet
 .............................................................................................................................. 744
Figure 1068: Proportion of MU Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 744
Figure 1069: Proportion of MU Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 745
Figure 1070: Proportion of MU Parcels with Three Other Land Uses Within 500 Feet
 .............................................................................................................................. 745
Figure 1071: Proportion of MU Parcels with Four Other Land Uses Within 500 Feet
 .............................................................................................................................. 746
Figure 1072: Proportion of MU Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 746
Figure 1073: Proportion of MU Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 747
Figure 1074: Proportion of MU Parcels with Seven Other Land Uses Within 500 Feet
 .............................................................................................................................. 747
Figure 1075: Proportion of MU Parcels with Eight Other Land Uses Within 500 Feet
 .............................................................................................................................. 748
Figure 1076: Proportion of MFR Parcels with Zero Other Land Uses Within 500 Feet
 .............................................................................................................................. 748
Figure 1077: Proportion of MFR Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 749
Figure 1078: Proportion of MFR Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 749
Figure 1079: Proportion of MFR Parcels with Three Other Land Uses Within 500
Feet ....................................................................................................................... 750
Figure 1080: Proportion of MFR Parcels with Four Other Land Uses Within 500 Feet
 .............................................................................................................................. 750
Figure 1081: Proportion of MFR Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 751
Figure 1082: Proportion of MFR Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 751
Figure 1083: Proportion of MFR Parcels with Seven Other Land Uses Within 500
Feet ....................................................................................................................... 752
Figure 1084: Proportion of MFR Parcels with Eight Other Land Uses Within 500 Feet
 .............................................................................................................................. 752
Figure 1085: Proportion of PUB Parcels with Zero Other Land Uses Within 500 Feet
 .............................................................................................................................. 753
Figure 1086: Proportion of PUB Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 753
Figure 1087: Proportion of PUB Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 754
xliii
Figure 1088: Proportion of PUB Parcels with Three Other Land Uses Within 500 Feet
 .............................................................................................................................. 754
Figure 1089: Proportion of PUB Parcels with Four Other Land Uses Within 500 Feet
 .............................................................................................................................. 755
Figure 1090: Proportion of PUB Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 755
Figure 1091: Proportion of PUB Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 756
Figure 1092: Proportion of PUB Parcels with Seven Other Land Uses Within 500
Feet ....................................................................................................................... 756
Figure 1093: Proportion of PUB Parcels with Eight Other Land Uses Within 500 Feet
 .............................................................................................................................. 757
Figure 1094: Proportion of PUB Parcels with Nine Other Land Uses Within 500 Feet
 .............................................................................................................................. 757
Figure 1095: Proportion of SFDR Parcels with Zero Other Land Uses Within 500
Feet ....................................................................................................................... 758
Figure 1096: Proportion of SFDR Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 758
Figure 1097: Proportion of SFDR Parcels with Two Other Land Uses Within 500
Feet ....................................................................................................................... 759
Figure 1098: Proportion of SFDR Parcels with Three Other Land Uses Within 500
Feet ....................................................................................................................... 759
Figure 1099: Proportion of SFDR Parcels with Four Other Land Uses Within 500
Feet ....................................................................................................................... 760
Figure 1100: Proportion of SFDR Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 760
Figure 1101: Proportion of SFDR Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 761
Figure 1102: Proportion of SFDR Parcels with Seven Other Land Uses Within 500
Feet ....................................................................................................................... 761
Figure 1103: Proportion of SFDR Parcels with Eight Other Land Uses Within 500
Feet ....................................................................................................................... 762
Figure 1104: Proportion of TCU Parcels with Zero Other Land Uses Within 500 Feet
 .............................................................................................................................. 762
Figure 1105: Proportion of TCU Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 763
Figure 1106: Proportion of TCU Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 763
Figure 1107: Proportion of TCU Parcels with Three Other Land Uses Within 500
Feet ....................................................................................................................... 764
Figure 1108: Proportion of TCU Parcels with Four Other Land Uses Within 500 Feet
 .............................................................................................................................. 764
Figure 1109: Proportion of TCU Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 765
Figure 1110: Proportion of TCU Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 765
xliv
Figure 1111: Proportion of TCU Parcels with Seven Other Land Uses Within 500
Feet ....................................................................................................................... 766
Figure 1112: Proportion of TCU Parcels with Eight Other Land Uses Within 500 Feet
 .............................................................................................................................. 766
Figure 1113: Proportion of TCU Parcels with Nine Other Land Uses Within 500 Feet
 .............................................................................................................................. 767
Figure 1114: Proportion of VAC Parcels with Zero Other Land Uses Within 500 Feet
 .............................................................................................................................. 767
Figure 1115: Proportion of VAC Parcels with One Other Land Use Within 500 Feet
 .............................................................................................................................. 768
Figure 1116: Proportion of VAC Parcels with Two Other Land Uses Within 500 Feet
 .............................................................................................................................. 768
Figure 1117: Proportion of VAC Parcels with Three Other Land Uses Within 500
Feet ....................................................................................................................... 769
Figure 1118: Proportion of VAC Parcels with Four Other Land Uses Within 500 Feet
 .............................................................................................................................. 769
Figure 1119: Proportion of VAC Parcels with Five Other Land Uses Within 500 Feet
 .............................................................................................................................. 770
Figure 1120: Proportion of VAC Parcels with Six Other Land Uses Within 500 Feet
 .............................................................................................................................. 770
Figure 1121: Proportion of VAC Parcels with Seven Other Land Uses Within 500
Feet ....................................................................................................................... 771
Figure 1122: Proportion of VAC Parcels with Eight Other Land Uses Within 500 Feet
 .............................................................................................................................. 771
Figure 1123: Proportion of AG Parcels with Zero Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 773
Figure 1124: Proportion of AG Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 773
Figure 1125: Proportion of AG Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 774
Figure 1126: Proportion of AG Parcels with Three Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 774
Figure 1127: Proportion of AG Parcels with Four Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 775
Figure 1128: Proportion of AG Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 775
Figure 1129: Proportion of AG Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 776
Figure 1130: Proportion of AG Parcels with Seven Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 776
Figure 1131: Proportion of AG Parcels with Eight Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 777
Figure 1132: Proportion of COM Parcels with Zero Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 777
Figure 1133: Proportion of COM Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 778
xlv
Figure 1134: Proportion of COM Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 778
Figure 1135: Proportion of COM Parcels with Three Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 779
Figure 1136: Proportion of COM Parcels with Four Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 779
Figure 1137: Proportion of COM Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 780
Figure 1138: Proportion of COM Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 780
Figure 1139: Proportion of COM Parcels with Seven Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 781
Figure 1140: Proportion of COM Parcels with Eight Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 781
Figure 1141: Proportion of IND Parcels with Zero Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 782
Figure 1142: Proportion of IND Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 782
Figure 1143: Proportion of IND Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 783
Figure 1144: Proportion of IND Parcels with Three Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 783
Figure 1145: Proportion of IND Parcels with Four Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 784
Figure 1146: Proportion of IND Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 784
Figure 1147: Proportion of IND Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 785
Figure 1148: Proportion of IND Parcels with Seven Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 785
Figure 1149: Proportion of IND Parcels with Eight Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 786
Figure 1150: Proportion of MMR Parcels with Zero Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 786
Figure 1151: Proportion of MMR Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 787
Figure 1152: Proportion of MMR Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 787
Figure 1153: Proportion of MMR Parcels with Three Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 788
Figure 1154: Proportion of MMR Parcels with Four Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 788
Figure 1155: Proportion of MMR Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 789
Figure 1156: Proportion of MMR Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 789
xlvi
Figure 1157: Proportion of MMR Parcels with Seven Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 790
Figure 1158: Proportion of MMR Parcels with Eight Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 790
Figure 1159: Proportion of MU Parcels with Zero Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 791
Figure 1160: Proportion of MU Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 791
Figure 1161: Proportion of MU Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 792
Figure 1162: Proportion of MU Parcels with Three Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 792
Figure 1163: Proportion of MU Parcels with Four Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 793
Figure 1164: Proportion of MU Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 793
Figure 1165: Proportion of MU Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 794
Figure 1166: Proportion of MU Parcels with Seven Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 794
Figure 1167: Proportion of MU Parcels with Eight Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 795
Figure 1168: Proportion of MFR Parcels with Zero Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 795
Figure 1169: Proportion of MFR Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 796
Figure 1170: Proportion of MFR Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 796
Figure 1171: Proportion of MFR Parcels with Three Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 797
Figure 1172: Proportion of MFR Parcels with Four Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 797
Figure 1173: Proportion of MFR Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 798
Figure 1174: Proportion of MFR Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 798
Figure 1175: Proportion of MFR Parcels with Seven Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 799
Figure 1176: Proportion of MFR Parcels with Eight Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 799
Figure 1177: Proportion of PUB Parcels with Zero Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 800
Figure 1178: Proportion of PUB Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 800
Figure 1179: Proportion of PUB Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 801
xlvii
Figure 1180: Proportion of PUB Parcels with Three Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 801
Figure 1181: Proportion of PUB Parcels with Four Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 802
Figure 1182: Proportion of PUB Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 802
Figure 1183: Proportion of PUB Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 803
Figure 1184: Proportion of PUB Parcels with Seven Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 803
Figure 1185: Proportion of PUB Parcels with Eight Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 804
Figure 1186: Proportion of PUB Parcels with Nine Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 804
Figure 1187: Proportion of SFDR Parcels with Zero Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 805
Figure 1188: Proportion of SFDR Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 805
Figure 1189: Proportion of SFDR Parcels with Two Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 806
Figure 1190: Proportion of SFDR Parcels with Three Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 806
Figure 1191: Proportion of SFDR Parcels with Four Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 807
Figure 1192: Proportion of SFDR Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 807
Figure 1193: Proportion of SFDR Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 808
Figure 1194: Proportion of SFDR Parcels with Seven Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 808
Figure 1195: Proportion of SFDR Parcels with Eight Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 809
Figure 1196: Proportion of TCU Parcels with Zero Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 809
Figure 1197: Proportion of TCU Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 810
Figure 1198: Proportion of TCU Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 810
Figure 1199: Proportion of TCU Parcels with Three Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 811
Figure 1200: Proportion of TCU Parcels with Four Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 811
Figure 1201: Proportion of TCU Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 812
Figure 1202: Proportion of TCU Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 812
xlviii
Figure 1203: Proportion of TCU Parcels with Seven Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 813
Figure 1204: Proportion of TCU Parcels with Eight Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 813
Figure 1205: Proportion of TCU Parcels with Nine Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 814
Figure 1206: Proportion of VAC Parcels with Zero Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 814
Figure 1207: Proportion of VAC Parcels with One Other Land Use Within 500 Feet
(Normalized) ......................................................................................................... 815
Figure 1208: Proportion of VAC Parcels with Two Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 815
Figure 1209: Proportion of VAC Parcels with Three Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 816
Figure 1210: Proportion of VAC Parcels with Four Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 816
Figure 1211: Proportion of VAC Parcels with Five Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 817
Figure 1212: Proportion of VAC Parcels with Six Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 817
Figure 1213: Proportion of VAC Parcels with Seven Other Land Uses Within 500
Feet (Normalized) .................................................................................................. 818
Figure 1214: Proportion of VAC Parcels with Eight Other Land Uses Within 500 Feet
(Normalized) ......................................................................................................... 818
Figure 1215: Average Distance from AG Parcels to the Nearest AG Parcel ........... 820
Figure 1216: Average Distance from COM Parcels to the Nearest AG Parcel ........ 820
Figure 1217: Average Distance from IND Parcels to the Nearest AG Parcel .......... 821
Figure 1218: Average Distance from MMR Parcels to the Nearest AG Parcel ....... 821
Figure 1219: Average Distance from MU Parcels to the Nearest AG Parcel ........... 822
Figure 1220: Average Distance from MFR Parcels to the Nearest AG Parcel ......... 822
Figure 1221: Average Distance from PUB Parcels to the Nearest AG Parcel ......... 823
Figure 1222: Average Distance from SFDR Parcels to the Nearest AG Parcel ....... 823
Figure 1223: Average Distance from TCU Parcels to the Nearest AG Parcel ......... 824
Figure 1224: Average Distance from VAC Parcels to the Nearest AG Parcel ......... 824
Figure 1225: Average Distance from AG Parcels to the Nearest COM Parcel ........ 825
Figure 1226: Average Distance from COM Parcels to the Nearest COM Parcel ..... 825
Figure 1227: Average Distance from IND Parcels to the Nearest COM Parcel ....... 826
Figure 1228: Average Distance from MMR Parcels to the Nearest COM Parcel .... 826
Figure 1229: Average Distance from MU Parcels to the Nearest COM Parcel ....... 827
Figure 1230: Average Distance from MFR Parcels to the Nearest COM Parcel ...... 827
Figure 1231: Average Distance from PUB Parcels to the Nearest COM Parcel ...... 828
Figure 1232: Average Distance from SFDR Parcels to the Nearest COM Parcel .... 828
Figure 1233: Average Distance from TCU Parcels to the Nearest COM Parcel ...... 829
Figure 1234: Average Distance from VAC Parcels to the Nearest COM Parcel ...... 829
Figure 1235: Average Distance from AG Parcels to the Nearest IND Parcel .......... 830
Figure 1236: Average Distance from COM Parcels to the Nearest IND Parcel ....... 830
xlix
Figure 1237: Average Distance from IND Parcels to the Nearest IND Parcel ......... 831
Figure 1238: Average Distance from MMR Parcels to the Nearest IND Parcel ...... 831
Figure 1239: Average Distance from MU Parcels to the Nearest IND Parcel ......... 832
Figure 1240: Average Distance from MFR Parcels to the Nearest IND Parcel........ 832
Figure 1241: Average Distance from PUB Parcels to the Nearest IND Parcel ........ 833
Figure 1242: Average Distance from SFDR Parcels to the Nearest IND Parcel ...... 833
Figure 1243: Average Distance from TCU Parcels to the Nearest IND Parcel ........ 834
Figure 1244: Average Distance from VAC Parcels to the Nearest IND Parcel........ 834
Figure 1245: Average Distance from AG Parcels to the Nearest MMR Parcel ....... 835
Figure 1246: Average Distance from COM Parcels to the Nearest MMR Parcel .... 835
Figure 1247: Average Distance from IND Parcels to the Nearest MMR Parcel ...... 836
Figure 1248: Average Distance from MMR Parcels to the Nearest MMR Parcel .... 836
Figure 1249: Average Distance from MU Parcels to the Nearest MMR Parcel ....... 837
Figure 1250: Average Distance from MFR Parcels to the Nearest MMR Parcel ..... 837
Figure 1251: Average Distance from PUB Parcels to the Nearest MMR Parcel...... 838
Figure 1252: Average Distance from SFDR Parcels to the Nearest MMR Parcel ... 838
Figure 1253: Average Distance from TCU Parcels to the Nearest MMR Parcel ..... 839
Figure 1254: Average Distance from VAC Parcels to the Nearest MMR Parcel ..... 839
Figure 1255: Average Distance from AG Parcels to the Nearest MU Parcel ........... 840
Figure 1256: Average Distance from COM Parcels to the Nearest MU Parcel ....... 840
Figure 1257: Average Distance from IND Parcels to the Nearest MU Parcel ......... 841
Figure 1258: Average Distance from MMR Parcels to the Nearest MU Parcel ....... 841
Figure 1259: Average Distance from MU Parcels to the Nearest MU Parcel .......... 842
Figure 1260: Average Distance from MFR Parcels to the Nearest MU Parcel ........ 842
Figure 1261: Average Distance from PUB Parcels to the Nearest MU Parcel ......... 843
Figure 1262: Average Distance from SFDR Parcels to the Nearest MU Parcel ....... 843
Figure 1263: Average Distance from TCU Parcels to the Nearest MU Parcel......... 844
Figure 1264: Average Distance from VAC Parcels to the Nearest MU Parcel ........ 844
Figure 1265: Average Distance from AG Parcels to the Nearest MFR Parcel ......... 845
Figure 1266: Average Distance from COM Parcels to the Nearest MFR Parcel...... 845
Figure 1267: Average Distance from IND Parcels to the Nearest MFR Parcel........ 846
Figure 1268: Average Distance from MMR Parcels to the Nearest MFR Parcel ..... 846
Figure 1269: Average Distance from MU Parcels to the Nearest MFR Parcel ........ 847
Figure 1270: Average Distance from MFR Parcels to the Nearest MFR Parcel ...... 847
Figure 1271: Average Distance from PUB Parcels to the Nearest MFR Parcel ....... 848
Figure 1272: Average Distance from SFDR Parcels to the Nearest MFR Parcel ..... 848
Figure 1273: Average Distance from TCU Parcels to the Nearest MFR Parcel ....... 849
Figure 1274: Average Distance from VAC Parcels to the Nearest MFR Parcel ...... 849
Figure 1275: Average Distance from AG Parcels to the Nearest PUB Parcel ......... 850
Figure 1276: Average Distance from COM Parcels to the Nearest PUB Parcel ...... 850
Figure 1277: Average Distance from IND Parcels to the Nearest PUB Parcel ........ 851
Figure 1278: Average Distance from MMR Parcels to the Nearest PUB Parcel...... 851
Figure 1279: Average Distance from MU Parcels to the Nearest PUB Parcel ......... 852
Figure 1280: Average Distance from MFR Parcels to the Nearest PUB Parcel ....... 852
Figure 1281: Average Distance from PUB Parcels to the Nearest PUB Parcel ....... 853
Figure 1282: Average Distance from SFDR Parcels to the Nearest PUB Parcel ..... 853
l
Figure 1283: Average Distance from TCU Parcels to the Nearest PUB Parcel ....... 854
Figure 1284: Average Distance from VAC Parcels to the Nearest PUB Parcel ....... 854
Figure 1285: Average Distance from AG Parcels to the Nearest SFDR Parcel ....... 855
Figure 1286: Average Distance from COM Parcels to the Nearest SFDR Parcel .... 855
Figure 1287: Average Distance from IND Parcels to the Nearest SFDR Parcel ...... 856
Figure 1288: Average Distance from MMR Parcels to the Nearest SFDR Parcel ... 856
Figure 1289: Average Distance from MU Parcels to the Nearest SFDR Parcel ....... 857
Figure 1290: Average Distance from MFR Parcels to the Nearest SFDR Parcel ..... 857
Figure 1291: Average Distance from PUB Parcels to the Nearest SFDR Parcel ..... 858
Figure 1292: Average Distance from SFDR Parcels to the Nearest SFDR Parcel ... 858
Figure 1293: Average Distance from TCU Parcels to the Nearest SFDR Parcel ..... 859
Figure 1294: Average Distance from VAC Parcels to the Nearest SFDR Parcel ..... 859
Figure 1295: Average Distance from AG Parcels to the Nearest TCU Parcel ......... 860
Figure 1296: Average Distance from COM Parcels to the Nearest TCU Parcel ...... 860
Figure 1297: Average Distance from IND Parcels to the Nearest TCU Parcel ........ 861
Figure 1298: Average Distance from MMR Parcels to the Nearest TCU Parcel ..... 861
Figure 1299: Average Distance from MU Parcels to the Nearest TCU Parcel......... 862
Figure 1300: Average Distance from MFR Parcels to the Nearest TCU Parcel ....... 862
Figure 1301: Average Distance from PUB Parcels to the Nearest TCU Parcel ....... 863
Figure 1302: Average Distance from SFDR Parcels to the Nearest TCU Parcel ..... 863
Figure 1303: Average Distance from TCU Parcels to the Nearest TCU Parcel ....... 864
Figure 1304: Average Distance from VAC Parcels to the Nearest TCU Parcel ....... 864
Figure 1305: Average Distance from AG Parcels to the Nearest UNKN Parcel ...... 865
Figure 1306: Average Distance from COM Parcels to the Nearest UNKN Parcel ... 865
Figure 1307: Average Distance from IND Parcels to the Nearest UNKN Parcel..... 866
Figure 1308: Average Distance from MMR Parcels to the Nearest UNKN Parcel .. 866
Figure 1309: Average Distance from MU Parcels to the Nearest UNKN Parcel ..... 867
Figure 1310: Average Distance from MFR Parcels to the Nearest UNKN Parcel ... 867
Figure 1311: Average Distance from PUB Parcels to the Nearest UNKN Parcel .... 868
Figure 1312: Average Distance from SFDR Parcels to the Nearest UNKN Parcel .. 868
Figure 1313: Average Distance from TCU Parcels to the Nearest UNKN Parcel .... 869
Figure 1314: Average Distance from VAC Parcels to the Nearest UNKN Parcel ... 869
Figure 1315: Average Distance from AG Parcels to the Nearest VAC Parcel ......... 870
Figure 1316: Average Distance from COM Parcels to the Nearest VAC Parcel...... 870
Figure 1317: Average Distance from IND Parcels to the Nearest VAC Parcel........ 871
Figure 1318: Average Distance from MMR Parcels to the Nearest VAC Parcel ..... 871
Figure 1319: Average Distance from MU Parcels to the Nearest VAC Parcel ........ 872
Figure 1320: Average Distance from MFR Parcels to the Nearest VAC Parcel ...... 872
Figure 1321: Average Distance from PUB Parcels to the Nearest VAC Parcel ....... 873
Figure 1322: Average Distance from SFDR Parcels to the Nearest VAC Parcel ..... 873
Figure 1323: Average Distance from TCU Parcels to the Nearest VAC Parcel ....... 874
Figure 1324: Average Distance from VAC Parcels to the Nearest VAC Parcel ...... 874
Figure 1325: Average Distance from AG Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 876
Figure 1326: Average Distance from COM Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 876
li
Figure 1327: Average Distance from IND Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 877
Figure 1328: Average Distance from MMR Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 877
Figure 1329: Average Distance from MU Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 878
Figure 1330: Average Distance from MFR Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 878
Figure 1331: Average Distance from PUB Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 879
Figure 1332: Average Distance from SFDR Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 879
Figure 1333: Average Distance from TCU Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 880
Figure 1334: Average Distance from VAC Parcels to the Nearest AG Parcel
(Normalized) ......................................................................................................... 880
Figure 1335: Average Distance from AG Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 881
Figure 1336: Average Distance from COM Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 881
Figure 1337: Average Distance from IND Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 882
Figure 1338: Average Distance from MMR Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 882
Figure 1339: Average Distance from MU Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 883
Figure 1340: Average Distance from MFR Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 883
Figure 1341: Average Distance from PUB Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 884
Figure 1342: Average Distance from SFDR Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 884
Figure 1343: Average Distance from TCU Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 885
Figure 1344: Average Distance from VAC Parcels to the Nearest COM Parcel
(Normalized) ......................................................................................................... 885
Figure 1345: Average Distance from AG Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 886
Figure 1346: Average Distance from COM Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 886
Figure 1347: Average Distance from IND Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 887
Figure 1348: Average Distance from MMR Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 887
Figure 1349: Average Distance from MU Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 888
lii
Figure 1350: Average Distance from MFR Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 888
Figure 1351: Average Distance from PUB Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 889
Figure 1352: Average Distance from SFDR Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 889
Figure 1353: Average Distance from TCU Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 890
Figure 1354: Average Distance from VAC Parcels to the Nearest IND Parcel
(Normalized) ......................................................................................................... 890
Figure 1355: Average Distance from AG Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 891
Figure 1356: Average Distance from COM Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 891
Figure 1357: Average Distance from IND Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 892
Figure 1358: Average Distance from MMR Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 892
Figure 1359: Average Distance from MU Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 893
Figure 1360: Average Distance from MFR Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 893
Figure 1361: Average Distance from PUB Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 894
Figure 1362: Average Distance from SFDR Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 894
Figure 1363: Average Distance from TCU Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 895
Figure 1364: Average Distance from VAC Parcels to the Nearest MMR Parcel
(Normalized) ......................................................................................................... 895
Figure 1365: Average Distance from AG Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 896
Figure 1366: Average Distance from COM Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 896
Figure 1367: Average Distance from IND Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 897
Figure 1368: Average Distance from MMR Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 897
Figure 1369: Average Distance from MU Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 898
Figure 1370: Average Distance from MFR Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 898
Figure 1371: Average Distance from PUB Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 899
Figure 1372: Average Distance from SFDR Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 899
liii
Figure 1373: Average Distance from TCU Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 900
Figure 1374: Average Distance from VAC Parcels to the Nearest MU Parcel
(Normalized) ......................................................................................................... 900
Figure 1375: Average Distance from AG Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 901
Figure 1376: Average Distance from COM Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 901
Figure 1377: Average Distance from IND Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 902
Figure 1378: Average Distance from MMR Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 902
Figure 1379: Average Distance from MU Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 903
Figure 1380: Average Distance from MFR Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 903
Figure 1381: Average Distance from PUB Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 904
Figure 1382: Average Distance from SFDR Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 904
Figure 1383: Average Distance from TCU Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 905
Figure 1384: Average Distance from VAC Parcels to the Nearest MFR Parcel
(Normalized) ......................................................................................................... 905
Figure 1385: Average Distance from AG Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 906
Figure 1386: Average Distance from COM Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 906
Figure 1387: Average Distance from IND Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 907
Figure 1388: Average Distance from MMR Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 907
Figure 1389: Average Distance from MU Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 908
Figure 1390: Average Distance from MFR Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 908
Figure 1391: Average Distance from PUB Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 909
Figure 1392: Average Distance from SFDR Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 909
Figure 1393: Average Distance from TCU Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 910
Figure 1394: Average Distance from VAC Parcels to the Nearest PUB Parcel
(Normalized) ......................................................................................................... 910
Figure 1395: Average Distance from AG Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 911
liv
Figure 1396: Average Distance from COM Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 911
Figure 1397: Average Distance from IND Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 912
Figure 1398: Average Distance from MMR Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 912
Figure 1399: Average Distance from MU Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 913
Figure 1400: Average Distance from MFR Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 913
Figure 1401: Average Distance from PUB Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 914
Figure 1402: Average Distance from SFDR Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 914
Figure 1403: Average Distance from TCU Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 915
Figure 1404: Average Distance from VAC Parcels to the Nearest SFDR Parcel
(Normalized) ......................................................................................................... 915
Figure 1405: Average Distance from AG Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 916
Figure 1406: Average Distance from COM Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 916
Figure 1407: Average Distance from IND Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 917
Figure 1408: Average Distance from MMR Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 917
Figure 1409: Average Distance from MU Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 918
Figure 1410: Average Distance from MFR Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 918
Figure 1411: Average Distance from PUB Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 919
Figure 1412: Average Distance from SFDR Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 919
Figure 1413: Average Distance from TCU Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 920
Figure 1414: Average Distance from VAC Parcels to the Nearest TCU Parcel
(Normalized) ......................................................................................................... 920
Figure 1415: Average Distance from AG Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 921
Figure 1416: Average Distance from COM Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 921
Figure 1417: Average Distance from IND Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 922
Figure 1418: Average Distance from MMR Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 922
lv
Figure 1419: Average Distance from MU Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 923
Figure 1420: Average Distance from MFR Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 923
Figure 1421: Average Distance from PUB Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 924
Figure 1422: Average Distance from SFDR Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 924
Figure 1423: Average Distance from UNKN Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 925
Figure 1424: Average Distance from VAC Parcels to the Nearest UNKN Parcel
(Normalized) ......................................................................................................... 925
Figure 1425: Average Distance from AG Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 926
Figure 1426: Average Distance from COM Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 926
Figure 1427: Average Distance from IND Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 927
Figure 1428: Average Distance from MMR Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 927
Figure 1429: Average Distance from MU Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 928
Figure 1430: Average Distance from MFR Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 928
Figure 1431: Average Distance from PUB Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 929
Figure 1432: Average Distance from SFDR Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 929
Figure 1433: Average Distance from TCU Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 930
Figure 1434: Average Distance from VAC Parcels to the Nearest VAC Parcel
(Normalized) ......................................................................................................... 930
Figure 1435: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to AG
Uses ...................................................................................................................... 931
Figure 1436: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to COM
Uses ...................................................................................................................... 932
Figure 1437: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to IND
Uses ...................................................................................................................... 932
Figure 1438: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to
MMR Uses ............................................................................................................ 933
Figure 1439: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MU
Uses ...................................................................................................................... 933
Figure 1440: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MFR
Uses ...................................................................................................................... 934
Figure 1441: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to PUB
Uses ...................................................................................................................... 934
lvi
Figure 1442: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to
SFDR Uses ............................................................................................................ 935
Figure 1443: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to TCU
Uses ...................................................................................................................... 935
Figure 1444: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to
UNKN Uses .......................................................................................................... 936
Figure 1445: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to VAC
Uses ...................................................................................................................... 936
Figure 1446: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to AG
Uses ...................................................................................................................... 937
Figure 1447: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
COM Uses ............................................................................................................. 938
Figure 1448: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
IND Uses ............................................................................................................... 938
Figure 1449: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
MMR Uses ............................................................................................................ 939
Figure 1450: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MU
Uses ...................................................................................................................... 939
Figure 1451: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
MFR Uses ............................................................................................................. 940
Figure 1452: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
PUB Uses .............................................................................................................. 940
Figure 1453: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
SFDR Uses ............................................................................................................ 941
Figure 1454: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
TCU Uses .............................................................................................................. 941
Figure 1455: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
UNKN Uses .......................................................................................................... 942
Figure 1456: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to
VAC Uses ............................................................................................................. 942
Figure 1457: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to AG Uses ....................................................................................... 943
Figure 1458: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to COM Uses ................................................................................... 944
Figure 1459: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to IND Uses ..................................................................................... 944
Figure 1460: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to MMR Uses ................................................................................... 945
Figure 1461: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to MU Uses ...................................................................................... 945
Figure 1462: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to MFR Uses .................................................................................... 946
Figure 1463: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to PUB Uses ..................................................................................... 946
Figure 1464: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to SFDR Uses................................................................................... 947
lvii
Figure 1465: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to TCU Uses .................................................................................... 947
Figure 1466: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to UNKN Uses ................................................................................. 948
Figure 1467: Proportion of Parcel Area Within a Half Mile of a Limited Highway
Exit Devoted to VAC Uses .................................................................................... 948
lviii
Chapter 1: Introduction
The city of Houston, Texas has been at the heart of a long-running debate in
the United States on government?s proper role in the land development process.  As
the only large American city that never adopted a city-wide zoning ordinance,
Houston is often cited as an example for why more or less government planning is
needed.  Advocates of a more laissez-faire approach to land development reference
Houston as an example of how the private market can ?self-regulate? land use
relationships (the spatial proximity of various land uses to each other) through a
combination of market forces and private covenants.1  These authors argue that
zoning is redundant and unnecessary and claim that Houston largely exhibits a land
use pattern like that in zoned cities.2  Meanwhile, those more sympathetic to a
government role in land development cite examples of potentially incompatible land
uses in close proximity in Houston, something they argue would likely not be the case
had Houston been zoned like other cities.3
It has been difficult to come to a firm conclusion on which of these views
more accurately reflects reality. This is because, despite the amount of discussion
land use in Houston has sparked, no systematic research has been conducted to
characterize the city?s land use relationships and compare them to other large
American cities with zoning.  To date, the discussion of urban land use relationships
1 Private covenants are also referred to as deed restrictions.
2 Siegan, Land Use Without Zoning, 73; Saltzman, ?Houston Says No to Zoning,? 433.
3 Babcock, Zoning Game, 28; Toll, Zoned American, 300; Delafons, Land-Use Controls, 92; Fischel,
Zoning Rules!, 309.
1
has been informed more by perception, casual observation, and anecdotal information
than by actual land use data.  The purpose of this study is to close this gap in
understanding by undertaking a quantitative analysis of land use relationships across
American cities to determine if Houston?s are distinctive. To accomplish this, the
study makes use of a variety of spatial metrics describing land use relationships.  The
metrics are computed for American cities with zoning and for Houston.  By
comparing these metrics, it is revealed whether Houston?s land use relationships are
unique or whether they tend to mirror the patterns observed in other cities.
Note that this study focuses exclusively on the spatial relationship of land
uses; specifically, their relationships to each other and to transportation facilities (key
drivers of urban development).  It is recognized, however, that zoning ordinances
may affect the physical development of cities in several additional ways.  For
example, zoning ordinances can regulate the density/intensity of land uses, the
location of buildings on a lot, building heights, and several other important
components of urban design.  The decision to focus solely on land use relationships
for this study was driven primarily by data availability; the detailed data needed to
measure other aspects of urban form are not yet widely available.  When such data do
become available, future analyses can build upon this study to more fully understand
zoning?s impact on the physical development of American cities.
The findings of this study will help inform the ongoing dialogue of
government?s proper role in the land development process.  They should also be of
interest to those concerned with land use policy in Houston and can inform the
ongoing debate over whether that city should finally adopt zoning.  Cities with zoning
2
might also find the analysis of Houston?s land use relationships insightful;
particularly those who are considering liberalizing their zoning codes to allow greater
mixing of land uses and housing types, a recent trend.  This is exemplified most
notably by Minneapolis? decision to eliminate all single-family zoning4 and the
Oregon legislature?s efforts to do the same for cities larger than 10,000 people.5
Houston may offer lessons on the likely outcomes of such policy decisions.
This report is organized as follows.  First, for context, the next chapter,
Chapter 2, provides a short history and description of planning and land use
regulations in American cities and compares Houston?s regulations with those of
other jurisdictions.  Next, Chapter 3 reviews the literature on how zoning affects land
use patterns.  After this, Chapter 4 discusses the methodology employed in this study.
This includes the formal statement of the overarching research question and
accompanying hypotheses.  Following this, Chapter 5 presents the results of the study
and analyzes them with respect to the stated research question.  Lastly, Chapter 6
summarizes the key conclusions and identifies opportunities for further research.
4 Mervosh, ?Minneapolis Votes to End Single-Family Zoning.?
5 Wamsley, ?Oregon Votes to Ban Single-Family Zoning.?
3
Chapter 2: Planning and Land Use Regulations in American
Cities
Most land in American cities is owned by private entities and most land
development activities are initiated by private landholders. Cities, however, use
comprehensive planning and a variety of regulatory tools to guide the urban
development process and achieve outcomes deemed desirable for the common good.
This chapter begins with a brief description and history of planning and land use
regulation in large American cities with a special emphasis given to zoning;
traditionally, the most prominent land use management tool employed.  Following
this, the unique regulatory regime in Houston is described and compared with land
use regulations elsewhere.
American Planning and Land Use Regulations: A Brief History
American cities use an arsenal of tools to manage urban development within
their borders.  First and foremost are comprehensive plans which provide a holistic
spatially-defined vision of future land uses throughout the city and the infrastructure
needed to support them.  The vision articulated in the plan is, at least in theory,
realized over time through the implementation of various land use regulations.  These
include subdivision ordinances, which regulate lot layouts in new land developments,
and building codes, which regulate the design of structures for life safety.  Policies on
public facility/infrastructure provision (sewer, water, transportation, schools, and
parks) and several other specialized ordinances (e.g. environmental regulations,
affordable housing requirements, etc.) also play important roles in shaping urban
4
development patterns.  However, important as these other tools are, when it comes to
regulating land use spatial relationships and achieving the land use pattern envisioned
in the comprehensive plan, zoning has traditionally been the tool of choice.
Zoning, at its core, divides a jurisdiction up into a series of non-overlapping
districts.  For each district (i.e., zone), a zoning ordinance may specify:
? The various land uses allowed
? The intensities of the allowed land uses
? The building envelope on each lot
? Screening and buffering requirements between land uses
? Parking requirements
? Sign requirements
? Historic preservation requirements
? Design requirements6
? Environmental protection requirements
Several combinations of the various requirements are possible; indeed, zoning
ordinances are often criticized for being quite complex.  Unlike in some countries
(e.g., Germany), American cities are generally free to develop their own rules for
each zone.  Thus, although there are commonalities amongst ordinances in various
cities, each city?s zoning ordinance is unique and adapted to its geography, history,
and culture.
Various components of today?s typical zoning ordinances have been used in
American cities since the colonial period.  From the 17th through the 19th centuries,
select towns and cities have, at various points in their histories, had ordinances
prescribing building setback lines, requirements that certain noxious industries be
relegated to specified parts of town, required building materials (for fire prevention),
6 Design requirements have become increasingly common in zoning ordinances as a means of fostering
more pedestrian-friendly streetscapes, historic preservation, and resiliency to natural hazards.
5
and caps on the maximum height of buildings.7   However, these ordinances tended to
be ad hoc (i.e., not guided by a comprehensive plan), were often applied only to
limited areas, and did not regulate land use, per se.  Nuisance laws also provided a
means for dealing with certain problematic land use relationships.8  Strictly speaking,
however, land use in American cities was not comprehensively planned or publicly
regulated until the early 20th century.
While there were only limited public plans and regulations on urban
development in early American cities, private planning and regulations began to
appear beginning in the latter half of the 19th century.  During this period, a new type
of urban development began to take shape on the peripheries of America?s largest
cities: the large-scale residential subdivision.9  These new subdivisions, enabled by
the advent of the railroad and the more distant commuting it allowed, were marketed
towards the wealthy (who could afford the rail fair) and embodied a new aesthetic
dominated by low density single-family homes set amidst a bucolic natural
landscape.10 Land use relationships within the subdivisions were planned and often
exhibited a separation of land uses; any commercial or denser residential
development was typically concentrated near the train station and the balance of the
subdivision reserved for single-family homes.  The developers of these communities
realized there would be a tendency for denser residential development and other land
7 Reps, The Making of Urban America; Talen, City Rules, 20; Logan, ?The Americanization of German
Zoning,? 381.
8 Hirt, Zoned in the USA, 118.
9 Although these subdivisions were primarily residential, some included limited commercial uses in a
?town center.?
10 Hayden, Building Suburbia, 45; Fischel, ?An Economic History of Zoning,? 320.
6
uses to infiltrate these neighborhoods over time.  Believing that they could enhance
the value of their lots by preventing this, the developers created private restrictions,
known as covenants or deed restrictions, which all purchasers were bound by.
Covenants regulations varied from subdivision to subdivision but typically
included restrictions on the uses allowed on each lot.  Most common were restrictions
limiting the property?s use to single-family residential homes.  Setback specifications,
minimum house sizes, and even racial/ethnic restrictions (later ruled unconstitutional)
were also stipulated.11  Some covenants were written to expire after a set amount of
years (unless renewed by the owners) while others were written to continue in
perpetuity and, indeed, many are in place to this day.  The popularity of covenants
grew over time and, in the twentieth century, came to be used in developments
marketed to a range of income levels.  Covenants continue to be used in many
neighborhoods as an added layer of neighborhood protection on top of zoning.  They
also provide a means to implement restrictions that go beyond what the public sector
is willing (or legally able) to impose.
While private land use restrictions were beginning to gain some acceptance in
the United States during the late 19th century, public land development regulations
continued to lag.  Most of the new innovations in land use regulation were occurring
in Europe, especially in Germany, where cities had been taking a more active role in
the urban development process for centuries.12  In 1876, Reinhart Baumeister from
the Technical University in Karlsruhe put forth an idea for a new tool to regulate
11 Hayden, Building Suburbia, 68; Talen, City Rules, 20.
12 Logan, ?The Americanization of German Zoning,? 379.
7
urban development more holistically; the comprehensive zoning ordinance.13  The
concept was simple yet profound: instead of a single set of urban development
regulations that must be applied to the entire city, different sets of regulations could
be applied to different areas, depending on local needs and plans.  The zoning concept
was generally well-received and adopted first by the city of Frankfurt-am-Main in
1891.14  Other prominent cities quickly adopted their own ordinances and zoning
came into widespread use in Germany by the turn of the 20th century.
Although German zoning did not (and still does not) restrict land use to the
same degree that American zoning eventually would (German zoning has always
allowed for a greater mixing of uses), it did influence those in the United States who
were concerned with the condition of the countries? cities.  Los Angeles was one of
the first cities to see the value in a zoning system when, beginning in 1909, they
started enacting a series of ordinances establishing dozens of residential and industrial
districts throughout the city.15  However, unlike in German cities, Los Angeles?
zoning was not comprehensive; portions of the city were not covered by any land use
restrictions.  The first truly comprehensive city-wide zoning ordinance was not
adopted in the United States until 1916 by the city of New York.16
The adoption of comprehensive zoning in New York was driven by a variety
of factors.  First, the city had an active Progressive political movement which, in
general, viewed zoning as a step towards better city governance, better housing,
13 Logan, 379.
14 Logan, 379.
15 Logan, 381.
16 Logan, 381.
8
enhanced health and safety, and more enlightened planning.17  These advocates
played a notable role in making the case for and helping to shape the zoning
ordinance.  Just as importantly, two powerful and politically well-connected interest
groups, Fifth Avenue retail merchants and lower Manhattan property owners, also
perceived benefits in adopting zoning and threw their considerable political weight
behind the proposal.  Fifth Avenue retailers saw zoning as a tool by which they could
keep textile establishments, and their lower-income heavily Jewish workforce, from
encroaching on their exclusive shopping district.18  Likewise, many Lower Manhattan
property owners were growing dismayed at the height of new buildings being erected
in the city?s financial district.  They argued that the new buildings were taking away
light and fresh air from adjacent properties and causing their property values to
diminish.19   Many saw zoning as a way to limit this trend and preserve their property
values.
The zoning ordinance that New York adopted in 1916 regulated land use,
building height, and lot coverage.  Each of these three components of the ordinance
had its own map showing where different rules applied.20  In general, the ordinance
was much simpler and less restrictive than today?s zoning ordinances.   For example,
only three different districts were enumerated: residence only zones (in which all
types of housing were allowed), business zones, and unrestricted zones.  Furthermore,
the zones were not necessarily exclusive to each use: while residential zones could
17 Logan, 381.
18 Weiss, ?Skyscraper Zoning,? 201.
19 Weiss, 202.
20 Logan, ?The Americanization of German Zoning,? 382.
9
only include residential uses, business zones could include residences and businesses
(excluding heavy industry), while unrestricted zones could include all uses.21  This
hierarchical treatment of land use, typically with residential uses at the top, was
common in the first generation of zoning ordinances in many large American cities.22
Despite legal questions surrounding the constitutionality of zoning, other
jurisdictions, urban and suburban, quickly followed New York?s lead and adopted
their own comprehensive zoning ordinances.  Eight jurisdictions had zoning by the
close of 1916, 68 more adopted it by 1926, and 1,246 more adopted it by 1936.23  The
rate of increase in zoning adoptions picked up appreciably in the late 1920s.  Two
factors help precipitate this: (1) the United States Department of Commerce published
A Standard State Zoning Enabling Act Under Which Municipalities May Adopt
Zoning in 1924,24 a legislative template for states to allow municipal zoning, and (2)
the United States Supreme Court ruled that zoning was constitutional in the 1926
Village of Euclid v. Ambler Realty Co. case.25   Concentrating on the larger cities that
are the focus of this study, Figure 1 provides a timeline showing the date each of
America?s 50 largest cities26 first adopted an effective comprehensive zoning
ordinance.  The figure indicates that the period of most rapid adoption of zoning in
today?s large cities occurred from the mid-1920s through the early 1930s.  By 1960,
all present-day large cities except Houston had a zoning ordinance in place.
21 Logan, 382.
22 Hirt, ?The Devil is in the Definitions,? 438.
23 Fischel, ?An Economic History of Zoning,? 319.
24 United States Department of Commerce, Standard State Zoning Enabling Act.
25 Village of Euclid, Ohio et al. v. Ambler Realty Co., 272 U.S. 365 (1926).
26 United States Census Bureau, Annual Estimates.
10
Figure 1: Year of Adoption of First Comprehensive Zoning Ordinance in America?s 50 Largest Cities27
27 Houston, which never adopted a city-wide zoning ordinance, is not shown on the timeline.  Also, some cities? first ordinances were later rejected by state
courts.  The dates shown are the dates of each city?s first legally approved ordinance.
11
The rapid adoption of zoning in the early 20th century can be traced to the rise
of the motor truck and motor bus, per a thesis put forth by economist William
Fischel.28  Fischel postulates that, prior to widespread use of these inventions, market
forces tended to concentrate externality-prone industrial and high-density residential
land uses in predictable locations that did not appeal to single-family homeowners.
Industrial land uses tended to concentrate along freight rail lines to reduce shipping
costs and high-density residential uses located along streetcar lines where land values
were higher due to greater accessibility.29  Conflicts between these uses and single-
family residential uses were, to a certain degree, naturally minimized.
With the invention of the truck, however, factories and warehouses became
free to locate away from rail lines and many did so to cut down on land costs which
were high near urban rail hubs.  Likewise, buses enabled multi-family housing to be
built away from streetcar lines and yet still be served by public transportation.  The
result was that factories, warehouses, and higher-density housing began to infiltrate
single-family neighborhoods.  In turn, residents of those neighborhoods, who tended
to have political clout, agitated for zoning to be adopted to protect their investments.30
Fischel argues that these forces motivated the adoption of zoning much more than did
a Progressive push for better housing or planning.31
28 Fischel, ?An Economic History of Zoning,? 320.
29 Fischel, 320.
30 Fischel, 321.
31 Fischel, 319.
12
Indeed, in almost all large American cities, the adoption of zoning preceded
the adoption of land use planning, much to the chagrin of early planners.  Although
the development of city-wide plans began in1909 with Daniel Burnham?s Plan of
Chicago (seven years prior to New York?s adoption of the first comprehensive zoning
ordinance), this and other early plans focused on the provision of parks and public
infrastructure and did not contain spatially explicit policies for the use of private
land.32  While the United States? Commerce Department?s zoning enabling act and
several early planners called for comprehensive planning to guide zoning, the
eagerness of cities to adopt zoning ordinances to protect property owners meant that
most instituted zoning ordinances prior to rigorous analyses of land use needs.33
First generation zoning ordinances tended to be relatively permissive by
today?s standards.  Often, municipal officials tended to oversupply land for uses that
could be expected to bring in more tax revenue (e.g.,  retail/commercial uses).34
Also, although zones reserved for a single type of land use had been around since
1916 when Berkeley?s ordinance featured the first exclusively single-family zone,35
use zoning in many large cities was hierarchical (as in New York) and allowed for
some mixing of uses.  To a certain degree, this reflected early legal concerns about
exclusive use zoning but it also reflected the mixed use nature of the extensive pre-
zoning urban landscape in larger cities and, perhaps, a greater tolerance for mixed
land use amongst urban residents.  The drawing of zone boundaries was also done
32 Akimoto, ?The birth of ?land use planning? in American Planning,? 458.
33 Akimoto, 475.
34 Hubbard and Hubbard, Our Cities, 186; Ackerman, ?Zoning,? 21; Delafons, Land-Use Controls, 30.
35 Hirt, ?The Devil is in the Definitions,? 439.
13
with deference to established (pre-zoning) land uses: in many cases, zoning simply
codified the predominate uses that were established in an area.36  If a conflict did arise
between a pre-established land use and its newly established zoning, many cities
grandfathered in the existing land uses.37  This was no doubt done for political
expediency but it rankled planners who saw it as an impediment to progress.38  Thus,
while zoning was initially prompted by a desire to reign in and manage the free
market, there was also some tendency to ?follow the market? as well.
The idea that zoning should be guided by planning got a boost in 1928 when
the United States Commerce Department released the Standard City Planning
Enabling Act (four years after the agency?s publication of the Standard State Zoning
Enabling Act).  The Act, which would help prompt the adoption of planning in
American cities, called for zoning to be part of a city master plan.39  Key technical
advancements that enabled land use planning came in the early 1930s when Harland
Bartholomew, a prominent early planner, released his first book on ?scientific
zoning? which began to outline the analytical steps needed to forecast land use
needs.40  Interestingly, it was rural communities, not large cities, that were some of
the first to undertake land use analyses to inform plans and land development
policies, an outgrowth of agricultural planning programs of the 1920s and 1930s.41  It
was not until after World War II, in the late 1940s and early to mid-1950s, that land
36 Ackerman, ?Zoning,? 21; Willis, ?3-D CBD,? 14.
37 Oppermann, ?Non-Conforming Use,? 94.
38 Oppermann, 94.
39 Akimoto, ?The birth of ?land use planning? in American Planning,? 458.
40 Akimoto, 459.
41 Akimoto, 479.
14
use planning for urban areas and the linking of planning and zoning became standard
practice.42  A major impetus for this was federal urban renewal programs that
required city-wide land use planning as a condition for receiving federal funds.43
In addition to a greater emphasis on zoning following planning, the type of
zoning practiced by most cities had evolved by the middle of the twentieth century.
By this time, a point at which many cities were updating their first generation zoning
ordinances, hierarchical zoning had fallen out of favor; its demise hastened by the
Supreme Court?s Village of Euclid v. Ambler Realty Co. decision which approved the
practice of stricter land use and density separations.  This stricter form of zoning came
to be known as Euclidean zoning after the name of the town involved in the case.
With Euclidean zoning, instead of having just a few different zones that allowed
several different land use types within them, each land use was relegated to its own
zone.  Furthermore, separate zones were typically created for different intensities of
each land use.  The result was a proliferation of zones, longer and more complex
zoning codes, and, on the ground, more segregated land uses.  Zoning practice in the
United States diverged ever more sharply from Europe where there continued to be
more acceptance of land use mixing.44
Euclidean zoning, in part due to the predictability it provides for urban
development, has proven to be politically popular in much of the country and
continues to form the basis for most land use regulation in American cities.  That
42 Even today, however, one can often find disconnects between land use plans and zoning ordinances.
43 Akimoto, 477.
44 Hirt, ?The Devil is in the Definitions,? 439; Hirt, ?Home, Sweet Home;? Hirt, ?Mixed Use by
Default.?
15
said, the practice of Euclidean zoning is not monolithic throughout the country; its
implementation varies based on the historical, cultural, and legal context of the
locations where it has been adopted.  Perhaps the greatest divergence in practice
relates to differences in citizens? acceptance of government regulation over private
property.  In cities and states where the political culture is more in favor of
government intervention, there tends to be greater conformance between
comprehensive plans and zoning ordinances and less tendency for zoning to be
overturned based on requests from landowners.45  On the other hand, in locations that
put greater emphasis on private property rights, zoning need not comport with the
comprehensive plan and changes to zoning based on property owner requests are
more common.  That being said, according to zoning consultants who were
interviewed for this study, there does tend to be a common national consensus on
which uses are incompatible, although, curiously enough, this culturally-influenced
understanding appears not to be documented in any published literature.46
Despite its popularity, many have come to see problems with the Euclidean
approach and have attacked it from social, environmental, and aesthetic viewpoints.
Social concerns have generally focused on the income and racial segregation that
Euclidean zoning has been accused of perpetuating.47  The argument is that zoning
provides a tool by which wealthier and whiter residents can exclude lower income
individuals by disallowing denser, more affordable housing.  Environmental critiques
45 Elliot, interview.
46 Elliot and White, interviews.
47 Delafons, Land-Use Controls, 31; Logan, ?The Americanization of German Zoning,? 377; Levine,
Zoned Out; Hirt, ?Home, Sweet Home,? 301.
16
of Euclidean zoning have focused on its land consumption and transportation effects.
Greenfield land consumption is inherently higher when uses are segregated
horizontally into different structures in different locations, as opposed to being mixed
vertically in the same structure.  In the United States this effect has been greatly
enhanced by, among other things, minimum lot size requirements that are often part
of the zoning code.48  Furthermore, separating land uses necessitates more vehicle
travel which harms air quality and exacerbates greenhouse gas emissions.49  Aesthetic
arguments have focused on the bland homogeneity that Euclidean zoning is accused
of fostering and its lack of flexibility which can dampen the emergence of innovative
designs.50
The various criticisms leveled at Euclidean zoning have inspired reformers to
find ways to increase its flexibility and effectiveness.  The most widely implemented
strategies have generally been those that retain the basic elements of Euclidean
zoning but add some flexibility such as planned use developments (PUDs), floating
zones, and overlay zones.   PUDs, typically applied to larger development projects,
offer alternative development regulations to standard zoning requirements and, within
the site, are generally more flexible with regards to building densities, setbacks, etc.
Thus, they can help foster more innovative site developments.  PUDs are
implemented using floating zones, zones that do not appear on a city?s zoning map
but can be requested by a land developer in lieu of the original zoning if certain pre-
48 Talen, City Rules, 4.
49 Talen, 4.
50 Talen, ?Zoning and Diversity,? 331.
17
determined criteria (set by the municipality) are met.51  Overlay zones, on the other
hand, introduce additional regulations on top of the base zoning classifications.
These are most often used for special purpose restrictions like historic preservation,
protection against natural hazards, or environmental conservation.  Overlay zones
allow a more spatially tailored set of restrictions for each property, in lieu of broad-
brushed restrictions that apply to all properties.
For some reformers, these incremental improvements on Euclidean zoning do
not go far enough, inspiring them to offer more fundamental alternatives for
regulating urban development.  Performance zoning, first put forth as an idea in the
1950s, was one of the earliest alternatives suggested.52  Performance zoning sought to
allow more flexibility in land use so long as externalities between neighboring
properties were effectively managed.  Management would occur through prediction
of the likely externalities and development of appropriate mitigation measures.  If
externalities could not be managed effectively, then the use would be disallowed.
Although it received much discussion in the planning literature, most notably in Lane
Kendig?s book Performance Zoning from 1980, the performance-based approach
lacked the predictability of Euclidean zoning and proved difficult to implement.53
Thus, it has never gained widespread acceptance.  As of 1993 (the last year in which a
survey was undertaken), only around 50 communities in the United States had
51 It should be noted that, despite the flexibility offered by PUDs, many developers choose to stick with
the standard zoning requirements.  PUDs, while adding flexibility, also increase risk on a project
because of the uncertainties associated with the approval process.  Euclidean zoning is often favored
by developers because of its greater predictability (i.e., lower risk).
52 Batstone, ?Zoning?s Deep Freeze,? 34.
53 Kendig et al., Performance Zoning.
18
performance zoning and the trend for use of these types of regulations was
downward.54
In the early 1980s, another alternative to zoning, form-based codes were
developed.  Form-based codes generally relax the separation of land uses and
liberalize density allowances (relative to traditional Euclidean zoning) in exchange
for stricter control over building form and design.  Early proponents of form-based
codes drew inspiration from the urban form of older neighborhoods which developed
in the pre-zoning and pre-automobile eras.  There was a realization that, despite often
being highly sought after areas, these sorts of compact mixed-use walkable
neighborhoods with a variety of housing types in close proximity were no longer
allowed to be constructed due to modern zoning regulations.  Instead, it was argued
that Euclidean zoning?s strict separation of land uses tended to result only in a
?placeless? low-density auto-dependent urban form colloquially referred to as
?sprawl.? 55  Form based code advocates, most prominently Andres Duany, have
argued that a host of negative environmental and social impacts can be attributed to
sprawl and, by extension, to Euclidean zoning.56  These advocates argue for a
paradigm shift in land use planning which, among other policy changes, would
involve wholesale replacement of Euclidean zoning codes with form based codes.
That said, the hoped-for revolution in favor of form-based codes has been
somewhat slow to catch on.  As of the mid 2000s, only 22 localities (out of almost
40,000 in the United States) used form-based codes and typically only for a portion of
54 Marwedel, ?Opting for Performance,? 224.
55 Talen, City Rules.
56 Talen, ?Zoning and Diversity,? 331.
19
the town.57  More recent estimates of form-based code adoption are available from
The Codes Study.  The Codes Study is an ongoing project by PlaceMakers, a form-
based coding consulting and advocacy firm, to track the adoption of form-based
codes worldwide.  Their website states that, as of February 2017, 387 form-based
codes have been adopted worldwide (the majority being in the United States).58  The
accompanying database indicates that many of these codes apply only to a certain
district(s) within a jurisdiction or are optional overlays that complement traditional
zoning.  City-wide replacements of traditional zoning codes with form-based codes
continue to be the exception, not the rule.  The Codes Study does indicate an upward
trend in form-based code adoptions with 88% of the codes being approved since
2003.59
  Of America?s 50 largest cities, there is a notably higher adoption rate of
form-based codes.  In total, 19 of them (38%) have adopted some type of form based
codes as of February 2017.60  That said, most these cities have chosen to retain
traditional zoning for most of their land area with the form-based codes applying only
to a specific building type or district (typically the central business district [CBD] or a
redevelopment area).  Examples of this practice include Colorado Springs, Dallas,
Fort Worth, Fresno, Jacksonville, Mesa, Portland, Raleigh, Seattle, and Virginia
Beach.61  Some cities, however, have gone further and allow form-based codes as an
option in lieu of traditional zoning or in specific contexts more broadly throughout
57 Hirt, ?The Devil is in the Definitions,? 439.
58 PlaceMakers, ?Codes Study.?
59 PlaceMakers.
60 PlaceMakers.
61 PlaceMakers.
20
the city (e.g., Albuquerque, El Paso, Memphis, Nashville, Omaha, and
Philadelphia).62  Only a few large cities have more fully replaced their traditional
Euclidean ordinances with form-based codes (e.g. Baltimore, Denver, and Miami).63
Even in these cities, however, a certain degree of land use separation remains.
Consistent with broader trends, all but one of the form-based codes in large cities
have been adopted since the year 2000.64
In summary, land use regulations in America?s largest cities continue to be
dominated by traditional Euclidean zoning.  Recent trends have shown an increase in
the use of form-based codes but, while they allow more mixing of uses and
densification relative to traditional zoning, they nonetheless retain some separation of
uses and limits on density.  On top of this, form-based codes add detailed regulations
on urban form and design that go well beyond what is traditionally required by
Euclidean zoning ordinances. It can be argued that this is just the latest step in a
broader trend, evident since at least the late 19th century, towards greater public
control of the built environment in American cities.  Where planners in the early 20th
century once fretted over the legality of restricting a property to a generalized subset
of land uses, many communities today enumerate allowed uses very explicitly and
specify strict architectural design standards for individual buildings with the goal of
creating more aesthetically pleasing and pedestrian friendly environments.  That said,
one American city, Houston, still maintains a much more hands-off approach to urban
62 PlaceMakers.
63 PlaceMakers.
64 PlaceMakers.
21
development.  The following section describes Houston?s unique approach to land
use.
Planning and Land Use Regulations in Houston
A section titled ?Planning and Land Use Regulations in Houston? might strike
some as an oxy-moron given the city?s long-running aversion to government
intervention in the land development process.  But, while Houston stands alone
amongst large American cities in never adopting a zoning ordinance (and, until
recently, in never adopting a general plan), the city is not a totally unregulated free
market. Houston, in fact, has several regulations that constrain the land development
process and many that explicitly deal with land use relationships.  As of 2015,
Houston also has an official city-wide general plan.  That said, Houston remains,
arguably, the least planned and regulated large American city with respect to urban
development.  This section will summarize the city?s approach to planning and land
use regulations starting with a brief overview of the city?s long-running zoning
debate.  Following this, the city?s present-day plan and its land use restrictions, both
public and private, will be discussed and compared to typical American zoning
ordinances.
The Zoning Debate
Houston?s lack of zoning is not for want of effort by pro-planning forces in
the city.  Indeed, the city has tried to implement zoning many times.  The first attempt
22
occurred in 1929, during the middle of the initial nationwide zoning movement.65  As
in some other cities, the initial effort failed due to strong opposition from property
owners and real estate interests.66  A 1937 attempt to reconstitute the earlier effort
also ran into intense political opposition.67  In 1948, after rapid growth in the city
following World War II, another attempt at zoning was made.68  However, after being
put to a straw vote, voters rejected it by a two to one margin with some saying it was
?un-American? and deriding it based on its German roots (a politically potent charge
at the time given Germany?s role in the war).69  Additional zoning referenda were
held in 1962 and 1993 and each time zoning was rejected, though only by 57% and
52% of voters, respectively.70  After the 1993 vote, Houston instituted a referendum
requirement into their city charter that mandates any future decision to adapt city-
wide zoning be put directly to the citizenry (previous referenda were done on an ad
hoc basis).71  The requirement stipulates that a draft ordinance be produced and the
community be given at least six months to review and debate it before the vote.
Why did the most recent zoning referendum fail?  As in past zoning debates,
real estate interests and free market advocates helped organize against zoning?s
adoption.  Post-vote analysis from the 1993 referendum found that those voting
against zoning tended to be either the very wealthy or lower-income residents.
65 City of Houston, ?Timeline.?
66 City of Houston
67 City of Houston
68 City of Houston
69 DePillis, ?Character Builder.?
70 DePillis
71 Code of Ordinances City of Houston, Texas (Supplement 82 Update 2) Charter Art. VII-b ? 13
(Municode 2017) (hereafter cited as the ?Houston Code of Ordinances?).
23
Middle class voters were generally in favor of zoning.72   Arguments at the time
against zoning included its potential to be used for (1) limiting economic and racial
integration (i.e., using government power to keep poor people out of wealthier
neighborhoods), (2) increasing housing costs by curtailing density, (3) causing sprawl
and increased energy use, and (4) creating more opportunities for political corruption
by injecting politics into the land development process.73  There was also distaste
from some voters for creating a new bureaucracy in city government.74  Some also
argued that there was weak evidence for zoning increasing property values.75  In the
end, these arguments carried the day over the arguments by pro-zoning advocates that
zoning would enhance property values, protect public health, lead to more efficient
allocation of public infrastructure/facilities, and encourage redevelopment.76
Little known is that, despite the broader city?s inability to adopt a citywide
zoning ordinance, one small neighborhood located west of the CBD, Saint George
Place, did adopt zoning in 1999 (see location map in Figure 2).77  Saint George Place
could do this because it is a tax incentive reinvestment zone (TIRZ).  A TIRZ is an
area deemed by the city to be blighted, having deficient infrastructure, or otherwise in
need of special economic development incentives; specifically, the ability for
incremental property tax receipts from new development to fund public
72 McDonald, ?Houston Remains Unzoned,? 137.
73 McDonald, 139.
74 McDonald, 139
75 McDonald, 139
76 McDonald, 139
77 Saint George Place, ?History.?
24
improvements in the zone.78  These public improvements must follow the vision
outlined in a project plan document.79 Houston has 27 TIRZs in total covering most
of its present-day major activity centers along with other areas targeted for economic
development.  In Texas, TIRZs can institute their own zoning if they are in a
jurisdiction, like Houston, that does not have a zoning ordinance.  To date, Saint
George Place is the only one of Houston?s TIRZs to have exercised this power, the
remainder of the TIRZs focus primarily on public infrastructure provision (e.g.,
construction of new roads and pedestrian infrastructure), streetscape improvements,
and other activities that do not directly influence land use relationships.  In addition to
TIRZs, Houston?s city code also allows zoning to be established near airports;80 a
topic that will be discussed further in the following section.
78 City of Houston, ?Economic Development.?
79 City of Houston, ?Economic Development.?
80 Houston Code of Ordinances ? 9-5.
25
Figure 2: Location Map of the Saint George Place TIRZ
26
Current Plans and Regulations
While Houston has never adopted a comprehensive city-wide zoning
ordinance, it does do some degree of planning and has many other ordinances related
to urban development that are like those found in other cities (although, in many
cases they are, arguably, less restrictive than elsewhere).  For example, the city has a
building code, fire code, buffer requirements for certain land uses, parking
regulations, sign regulations, historic districts, floodplain regulations, and a
subdivision ordinance which regulates, among other things, minimum lot sizes81 and
building setbacks.82  While none of these ordinances directly regulate the spatial
relationships of land uses, they do affect the density, aesthetics, and functioning of the
city.
With respect to planning, Houston has long undertaken limited purpose
planning for the provision of public infrastructure (e.g., the annually updated Major
81 Houston?s minimum lot size requirements are quite permissive when compared to those in most
zoning ordinances. For example, the city?s Code of Ordinances (? 42-181) indicates that single-family
lots of 3,500 square feet (12.4 dwelling units per acre) are allowed by right in virtually any sewered
area of the city.  Remarkably, the Code of Ordinances (?? 42-181, 42-182, and 42-183) permits single-
family lot sizes to be reduced virtually anywhere in the city, to 1,400 square feet (31.1 units per acre),
if compensating open space is provided (or even less if building coverage is kept below 40%).
Furthermore, there are no direct limits on the locations of multi-family developments or on their
densities.  However, the Code of Ordinances (?? 42-190 and 42-236) states multi-family developments
must have lot sizes of at least 5,000 square feet and meet open space requirements.  Multi-family
buildings may locate next to single-family uses if they so choose.  And, with no building height
restrictions or floor-area-ratio (FAR) requirements, high-rises, residential or otherwise, can be
constructed nearly everywhere land values warrant, provided, per the Code of Ordinances (? 42-190),
the lot is at least 5,000 square feet.
82 Per the Houston Code of Ordinances (? 42-150), setback requirements in the city are generally
limited to the sides of lots bordering public streets.  Unlike in most zoned communities, there are
generally no setback requirements for side and rear yards.  Thus, zero lot-line construction is allowed
throughout the city.  An exception is for new high-rise buildings bordering single-family lots.  A recent
change to the subdivision regulations in the Code of Ordinances (? 42-272) requires that buildings over
75 feet tall be set back 30 to 40 feet from the property lines of single-family homes.
27
Thoroughfare and Freeway Plan) or, as mentioned previously, for the redevelopment
of blighted areas (TIRZs).  Until recently, however, Houston was unique amongst
large American cities in not having officially adopted a city-wide general plan.  This
changed in 2015, however, when Houston adopted its first city-wide comprehensive
plan, Plan Houston, that provides strategic direction on urban development
priorities.83  That said, unlike most comprehensive plans, Plan Houston has little to
say on preferred land use patterns, focusing instead on broader strategic goals for the
city. The city also has a Planning Commission and a planning department, the
Department of Planning and Development, with 60 full-time-equivalent staff.84  Their
responsibilities include directing planning activities and helping implement several
ordinances related to urban development that are described below.85
Houston nonetheless has no comprehensive government-mandated controls on
the locations of various land uses.  The city?s land use map is still largely determined
not by a central planning authority or by the community through a participatory
planning process but, generally, by each individual property owner deciding what is
in his/her best interest.  That said, various public land use restrictions have been put
in place, largely in an ad hoc manner, to deal with specific issues as they have come
up.  There are also many private land use controls in effect throughout the city (in the
form of private covenants).  The remainder of this section discusses these restrictions,
focusing first on the private covenants in the city and then on public regulations that
directly affect land use relationships.
83 City of Houston, ?Plan Houston.?
84 City of Houston, Fiscal Year 2018 Proposed Budget, 12.
85 Houston Code of Ordinances Ch. 33 Art. I and II.
28
Private Covenants
Perhaps the most widely-discussed restrictions in Houston are private
covenants which, as in many cities, have become common in new residential
developments built since World War II.86  As discussed previously, private covenants
are deed restrictions that can limit the land use, density, heights, setbacks, and design
of buildings in a subdivision.  The covenants are typically drafted and instituted by
the subdivision?s original developer and enforced and amended after build-out by a
homeowner/community association.  In many ways, the restrictions act like zoning.
However, covenant restrictions often go beyond what zoning can legally require and
delve into aspects of architectural design and property maintenance.  Covenants do
not necessarily last in perpetuity and often require periodic renewal by a majority of
community members.87  Covenant restrictions can be changed although this often
requires the consent of a super-majority of community members, if not unanimous
consent; high hurdles to achieve.
The city of Houston is unique amongst American cities in using public
authority to help manage these private agreements.  For example, the city restricts
changes from being made to some covenants once they?re established.  Specifically,
in subdivisions that have both residentially restricted sections and non-residential or
commercial restricted sections, the city does not allow the restrictions in the non-
residential sections to be amended so that those areas can be converted to multi-
86 Some commercial developments such as office parks also employ covenants.
87 Siegan, Land Use Without Zoning, 34.
29
family or denser single-family uses.88  Presumably, this represents an effort to protect
the adjacent single-family properties from unwanted land uses nearby.
Also, unlike almost all other cities where enforcement of covenants is strictly
through private actions, Houston city government has a program through the City
Attorney?s Office that enables it to enforce covenants at the public?s expense, much
as a city zoning department would enforce zoning restrictions.  Through the program,
citizens can report suspected covenant violations to the City Attorney?s Deed
Restriction Enforcement Team which can open an investigation.  If a violation is
found, the city can pursue legal action to seek a remedy at no direct expense to the
person who reported the violation.89  That said, the city?s purview is limited, only
getting involved in enforcing the type of covenant restrictions most akin to zoning
regulations; namely, issues of land use, building set back lines, lot size, number of
structures per lot, types of structures, orientation of structures, and fences.90  The
issuance of city building permits, certificates of occupancy, life safety compliance
certificates, and various other permits are also tied to the permittee following deed
restrictions.91
The city?s support for private covenants is motivated partly through equity
considerations.  With no public support, it is argued that there would be a tendency
for covenants only to be vigorously enforced in wealthier neighborhoods where
88 Houston Code of Ordinances ? 42-193.
89 City of Houston, ?Deed Restrictions;? Code of Ordinances City of Houston, Texas (Supplement 82
Update 2) ? 10-553.
90 City of Houston, ?Deed Restrictions;? Code of Ordinances City of Houston, Texas (Supplement 82
Update 2) ? 10-551.
91 Code of Ordinances City of Houston, Texas (Supplement 82 Update 2) ?? 10-3, 10-3.1, 10-555, 26-
475, 28-524, and 29-6.
30
residents have more resources to pursue violators in court.  Less wealthy
neighborhoods might tend to let more infractions occur due to lack of resources to
mount a legal challenge.  The same can be said for smaller neighborhoods, regardless
of income levels, where there is a smaller pool of homeowners to cover the fixed
legal costs of enforcement.92  If a pattern of infractions is established in a
neighborhood, this can render the covenants unenforceable: if one resident can violate
a restriction, what grounds does a neighborhood have to enforce that same restriction
on another individual?   Thus, instituting public enforcement of covenant restrictions
can be argued to help level the playing field for small and low-income
neighborhoods.
The pervasiveness of covenants in new residential areas of Houston and their
public enforcement has prompted many observers to claim that the city is highly
regulated; almost as much as a zoned city.93  This is true in only a limited sense since
covenants are not perfect substitutes for comprehensive zoning.  While they can be
highly restrictive in the areas they cover, covenants do not cover the entirety of
Houston like comprehensive zoning restrictions would. Unfortunately, a city-wide
map or geographic information systems (GIS) dataset of covenant protected areas has
never been compiled so definitive statistics or an illustration of the extent of areas
covered by covenants in Houston cannot be made.94  It is estimated, however, that, as
92 Siegan, Land Use Without Zoning, 33.
93 Weaver and Babcock, City Zoning, 218; Mixon, ?Land Use Vignettes,? 182; Qian, ?Without
Zoning,? 39; Levine, Zoned Out, 106.
94 An inquiry was made with the city requesting a GIS dataset showing covenant protected areas but it
was stated by staff that this was not available.  An exhaustive research effort into the tens of thousands
31
of the late 2000s, there were over 10,000 separate private covenants in effect in
Houston95 covering between 30 and 60 percent of residential neighborhoods.96
The lack of covenants is most pervasive in the Inner Loop (the name given to
the areas within the innermost beltway ring).  Many of the pre-World War II
neighborhoods that comprise this area do not have covenants or have very weak ones
(the exceptions being wealthier neighborhoods such as River Oaks).  Neighborhoods
lacking covenants here either never had them or they expired.  Many of the early
post-war neighborhoods just outside the Inner Loop also lack covenant protections.
In several of these neighborhoods, a mix of uses has taken hold in areas once
dominated by single-family homes.  An example of one such neighborhood is shown
in Figure 3.
Figure 3: An Inner Loop Neighborhood Lacking Single-Family Covenant Protections97
Even in newer areas farther from the CBD that have many covenant protected
residential neighborhoods there are often gaps in coverage outside the residential
of subdivisions recorded at the County Clerk?s office would be required to create this dataset.  Such an
effort is beyond the scope of this study.
95 Buitelaar, ?More than Just a Tool,? 1,059.
96 Qian, ?Without Zoning,? 38.
97 Image source: Google Earth Street View
32
neighborhood boundaries.  This is because, unlike with zoning, covenant restrictions
end at the edge of the subdivisions they cover.  Properties adjacent to residential
subdivisions often lack restrictions that would protect the residential uses like zoning
would.  One of the most contentious Houston land use controversies in recent years,
the Ashby High Rise, involved just such a situation.  Developers proposed a 21 story
mixed-use high rise project (Figure 4) adjacent to Boulevard Oaks, one of Houston?s
most exclusive single-family neighborhoods.   Despite having tightly enforced single-
family covenants, the neighborhood was not able to stop the project because it was
located outside the subdivision boundaries.  Figure 5 shows the context of the vacant
lot comprising the proposed development site.98 Even within neighborhoods that have
covenants, the covenants can, theoretically, be eliminated if a developer purchases
enough properties in the subdivision to overturn them and redevelop the site.  In
practice, this rarely happens but it illustrates how, in many ways, covenants offer less
protection than zoning.  Thus, covenants, though widely employed in Houston,
should not be considered a perfect substitute for zoning due to their susceptibility to
change and their limitations in geographic coverage.
98 The neighborhood fought a lengthy legal battle to try and stop the project on the grounds of nuisance
law and traffic regulations.  Ultimately, a judge ruled that these laws did not prevent the project and
allowed the project to proceed (albeit with damages paid to some neighboring residents by the
developers).  The case came to be seen as an example of how, without zoning laws, even the wealthy
could not stop controversial real estate projects in Houston as would typically be the case in zoned
cities. That being said, at the time of writing the project has yet to be constructed.
33
Figure 4: Rendering of the Proposed Ashby High Rise99
Figure 5: Site of the Proposed Ashby High Rise100
99 Mulvaney, ?Ashby high-rise remains unbuilt.?
100 Image source: Google Maps.
34
Public Regulations
Houston, although without zoning, nonetheless has several city ordinances
that directly affect the spatial relationships between different land uses.  This section
discusses each of these regulations.  The ordinances are classified into three groups
based on their primary purpose: (1) health and safety ordinances, (2) nuisance
minimization ordinances, and (3) moralistic ordinances.  Each group is discussed in
turn below.  Following this is a discussion synthesizing the city?s approach to land
use regulation and comparing it to zoned cities.
Health and Safety Ordinances
Houston has a variety of ordinances to deal with specific health and safety
related land use conflicts.  These include ordinances concerning (1) the siting of
hazardous industrial facilities, (2) the siting of outdoor shooting ranges, (3) land uses
near drinking water supply facilities, and (4) land uses near airports.  Each of these
ordinances is described below.
Hazardous Industrial Facilities
Activities conducted at certain industrial facilities can pose a direct danger to
citizens? health and safety.  Addressing this hazard was among one of the earliest
rationales for zoning.  Typical zoning strategy relegates potentially dangerous
industrial land uses to heavy industrial districts that are physically removed from
residential areas.  Houston, without zoning, attempts to mitigate the hazard in two
ways: (1) a ban on hazardous materials storage in key urban centers and (2) an
ordinance that regulates the siting and expansion of hazardous enterprises.
35
With respect to the first mitigation measure, the hazardous materials storage
ordinance forbids the storage of, ?explosives and blasting agents, flammable and
combustible liquids, compressed and liquefied natural gases, cryogenic fluids and LP-
gases? in the CBD and Medical Center101 areas.102 Although the ordinance is not a
full ban on heavy industrial uses in these urban centers (as would typically be the case
under zoning), it is nonetheless likely to prevent the types of industrial uses that are
dependent on these materials from locating in these areas.103
The second mitigation measure, the hazardous enterprises ordinance, applies
more broadly across the city.  It states that new hazardous enterprises (facilities that
handle hazardous materials) are disallowed if one-third or more of the parcels within
1,000 feet of the proposed facilities? parcel boundaries104 are residential105or if there
is a child care facility, hospital, nursing home, or school within the buffer.106
Expansions of existing facilities face less restrictive requirements regarding
residential land uses which are adjusted based on the means of access to the
property.107 For example, facilities with rail links face no restrictions on expansion,
facilities with access exclusively via a major thoroughfare have only a two-thirds
101 The Medical Center is a large, medical-industry dominated ?edge city? located approximately three
miles southwest of the CBD.
102 City of Houston, Houston Amendments to the 2006 International Fire Code, 24.
103 It can be argued that the market, through the high land values found in these urban centers, also
provides a strong disincentive for industrial firms (which tend to be land intensive) to locate there.
104Or 1,000 feet of the outer wall of a designated building, if hazardous materials are confined to that
structure.
105 Note that there are special provisions for adjusting the parcel count upwards when a multi-family
apartment building(s) or condominium(s) occupies a single tract.
106 Houston Code of Ordinances ?? 28-222 and 28-233.
107 The rationale presumably being that the means of transport of these materials to/from the facility
presents different levels of risk.
36
residential threshold, and facilities with no rail or exclusive major thoroughfare
access have a one-half residential threshold.108
Although the hazardous enterprises ordinance is not an outright ban on the
location of industrial facilities (it affects only those involved with hazardous
materials), the ordinance undoubtedly shapes the location decisions of many
industrial firms. Its approach is typical of how Houston deals with several different
land use conflicts.  These ordinances, many of which will be discussed in this section,
require that, before city permits are issued, certain proposed land uses must pass a test
that, through a buffer-based spatial analysis, considers the nearby land uses that could
be adversely affected.  If the proportion of adversely affected properties is too great
or certain sensitive uses are within the buffer, then the proposed use is disallowed at
that location.
The buffer approach is as an attempt by the city to reduce land use conflicts
without having to create pre-established zones for different land uses as one would do
through zoning.  In many cases, however, the thresholds for passing the test are
relatively low so the ordinances end up being relatively permissive relative to typical
zoning practice.  For example, if even as much as one-fourth of tracts within 1,000
feet of a proposed new hazardous enterprise are residential, the facility could still be
built.  This is unlikely to be the case in may zoned communities where new heavy
industries are only likely to be allowed in areas well-removed from residential
neighborhoods (if they?re allowed at all).  Also, the buffer-based ordinances generally
108 Houston Code of Ordinances ? 28-243.
37
only regulate one side of the land use relationship.  In other words, while they may
prevent externality generating uses from locating near protected uses, they do not
prevent the protected uses (in this case, residences, day care facilities, etc.) from
being built near the externality generating uses (the hazardous enterprises).  Thus,
?incompatible? land use relationships can still occur.  The presumption, of course, is
that the developer of the protected use (e.g. the residence) was aware of his/her
surroundings and chose to accept the risk or nuisance of the externality-generating
land use (perhaps in exchange for a lower priced lot).  This is an important difference
from modern zoning ordinances which, by establishing zones exclusive to each land
use, inherently regulate the location decisions of both land uses.
Outdoor Shooting Ranges
Since not everyone who shoots is an excellent marksman, outdoor shooting
ranges present an obvious safety hazard to surrounding properties.  Zoning would
typically address this issue by relegating outdoor shooting ranges to zones segregated
from residential areas or uses that involve a high concentration of people.  Design
requirements for these facilities may also be stipulated.  In Houston, the threat is
mitigated by a simple blanket requirement that all outdoor shooting ranges be located
at least 900 feet from any road, house, or business district.109  This, undoubtedly,
renders many parcels ineligible for outdoor shooting ranges, thereby affecting the
location of this land use.
109 Houston Code of Ordinances ? 5-124.
38
Water Supply Facilities
Many jurisdictions go to great lengths to protect their drinking water supplies
from land uses that could taint the water and require more expensive treatment.  This
is often accomplished through zoning ordinances that limit commercial and industrial
establishments from locating near water supply reservoirs and lakes.  Residential
uses, if they are allowed in the vicinity, are often kept to a low density.  Houston does
have land-use related ordinances that protect their water supplies but they are
generally not as strong as those in many other jurisdictions.
One ordinance regulates the commercial enterprises located around Lake
Houston, a reservoir that is part of the city?s water supply system.  Commercial land
uses are not barred in the area, but special requirements may make some choose a
different location.110  Houston also has an ordinance protecting the location of its
groundwater wells; another source of city water.  This ordinance simply states that no
cemetery is allowed within 50 feet of a wellhead; no chemical or petroleum storage
tanks are allowed within 150 feet; and no animal feed lots, solid waste disposal sites,
or oil wells are allowed within 500 feet.111  Although limited in its geographic scope,
this ordinance has a direct effect on the allowed locations of these types of land uses.
Airports
Airports represent a particularly challenging environment for managing land
use conflicts.  Frequent, low-flying aircraft can present a safety threat to nearby
110 Houston Code of Ordinances ? 23-3.
111 Houston Code of Ordinances ? 47-50.
39
residences and other land uses should there be an accident.  Aircraft noise can also
present a serious nuisance to many residents which can lead to lawsuits and court
findings that restrict airport operations.  Land uses themselves can present hazards to
the aircraft.  Industrial uses that emit smoke or bright lights and tall buildings can
make flying challenging.  To address these conflicts and satisfy Federal Aviation
Administration (FAA) requirements, cities typically incorporate special restrictions
into their zoning ordinances for areas surrounding airports.  While not a panacea for
resolving all airport-land use conflicts (issues with existing land uses often crop up
when airports are expanded or become busier), these ordinances can effectively
prevent new land uses that may conflict with airport operations.
Until recently, Houston, without a zoning ordinance, had no means of
managing land use around the city?s three major airports; George Bush
Intercontinental/Houston Airport (IAH), William P. Hobby Airport (HOU), and
Ellington Field (EFD).  The FAA requires local jurisdictions to manage land use
around airports in exchange for federal funding for the airports.  In 2006, FHWA
informed the city that they must address encroaching incompatible land uses or lose
their federal funding.112  This prompted the city to act and create a special zoning-like
ordinance that applies only to the areas surrounding the city?s three airports.
Figure 6 provides a map of the city?s airport zoning.  As one can see, the
distance Houston?s airport zoning extends outwards from the edge of each airport is
not uniform.  The zoning extends farther outwards along the flight paths (up to,
112 Feibel, ?Houston Looks to Ban New Homes.?
40
approximately, five miles from the airport boundary) than it does otherwise.  Within
any of the zoned area, the ?airport land use envelopes,? no land uses are permitted
that (1) produce steam, smoke, etc.; (2) emit glaring light or have high reflectivity; (3)
attract birds; (4) create electrical interference; or (5) otherwise impact airport
operations.113  This regulation, though not an explicit ban on certain categories of
land use, certainly precludes some land uses from being developed (e.g. certain
industrial uses, landfills, etc.).
The airport land use envelopes are further broken down into three tiers, each
with a different set of regulations that get progressively stricter the closer one gets to
the airport boundary.  In Tier 1, the strictest tier and the one located closest to each
airport, the zoning forbids the construction of all new multi-family buildings and
mobile home parks. Most other new land uses are allowed although many must meet
soundproofing standards.114  This includes single-family homes which are generally
allowed, albeit only on existing lots.115 An exception to this rule involves very high
noise areas at Hobby Airport and Ellington Field where even new single-family
homes are disallowed.116
113 Houston Code of Ordinances ? 9-360.
114 Houston Code of Ordinances ?? 9-403, 9-503, and 9-603.
115 The zoning does not allow lots to be further subdivided to allow for the construction of additional
homes.
116 Houston Code of Ordinances ?? 9-502 and 9-602.
41
Figure 6: Map of Airport Zoning in Houston
42
In Tier 2, the restrictions are like Tier 1 except that single-family subdivisions
and multi-family buildings are allowed.117  In Tier 3, there are essentially no
restrictions beyond the general one?s applying to the airport land use envelope that
were described above.118  In addition to the airport zoning ordinance, there are also
special restrictions limiting petroleum extraction and storage activities near IAH.119
A separate ordinance is used to address the height of structures near airports.120
The airport land use envelopes are the closest restrictions the city has to
regulating the spatial relationships between land uses in a manner similar to zoning.
However, the envelopes apply to only a small fraction of the city?s land area.
Furthermore, the restrictions within each zone (tier) remain quite permissive.  Many
different land uses are allowed within even the strictest tier, Tier 1, and there is no
attempt to regulate the spatial relationships between each of these uses within a given
tier.  Rather than using FAA requirements as a rationale for instituting a true zoning
ordinance (at least in the limited areas around airports), it appears that the city limited
the ordinance?s scope to focus strictly on FAA?s concerns.
Nuisance Minimization Ordinances
Nuisances between land uses might result from noxious odors, loud noises, or
aesthetics.  The separation of land uses that impose nuisances on other uses was one
of the original purposes of zoning.  Houston regulates the following land uses due to
the nuisances they may generate: (1) agriculture and animal processing facilities; (2)
117 Houston Code of Ordinances ?? 9-404, 9-504, and 9-604.
118 Houston Code of Ordinances ?? 9-405, 9-505, and 9-605.
119 Houston Code of Ordinances Art. IV Div. 1.
120 Houston Code of Ordinances ? 9-755.
43
uninhabited towers; (3) automotive and scrap metal facilities; (4) hotels; and (5)
modular homes, manufactured homes, and recreational vehicles.  Ordinances
addressing each of these land uses are described below.
Agriculture and Animal Processing Facilities
The primary nuisance from agricultural uses and animal processing facilities
(slaughterhouses and rendering plants) is foul odor.  Houston regulates the location of
these land uses with several ordinances.  Each of these ordinances make use of simple
buffer tests to evaluate the appropriateness of siting (or expanding) a facility at a
given location.  For example, no fowl can be kept within 100 feet of a residence,121
church, school, or hospital.122  The rules are the same for livestock except that they
must also be kept at least 100 feet from restaurants.123  While these ordinances can
directly affect the location of agricultural facilities, the number of agricultural
facilities within the city limits that are looking to expand is likely quite small.  Also,
100 feet is a modest setback requirement.
Animal processing facilities present their own nuisance challenges.  Here,
large quantities of animals are kept in close quarters leading to concentrated odors.
The buffer setbacks for these facilities are greater than for agricultural facilities as are
the number of other land uses that must be avoided.  For example, new rendering
plants (or additions to existing facilities) are not allowed within 600 feet of churches,
public parks, schools, hospitals, colleges/universities, eating places, or dwelling units
121 An exception is made for the fowl owner?s residence.
122 Houston Code of Ordinances ?? 6-31 and 6-32.
123 Houston Code of Ordinances ?? 6-14 and 6-15.
44
(an exception is made for dwelling units owned by the applicant or by plant
employees).124  Likewise, new slaughterhouses (or additions to existing facilities) are
not allowed within 3,000 feet of the aforementioned land uses.125  These location
restrictions are absolute, however, they apply to only a small fraction of land use
decisions in the city given the limited number of new rendering plants and
slaughterhouses being constructed.  As discussed above, buffer-based restrictions
such as these also don?t prevent any of the protected land uses (residences, churches,
etc.) from locating within the buffers after the processing facility has been built.
Uninhabited Towers
Uninhabited towers (e.g. cell phone towers and large radio/television
antennas) can be perceived as harmful to the aesthetics of a residential neighborhood.
Thus, the city of Houston has an ordinance in place that restricts the location of
proposed uninhabited towers over 60 feet in height.126  As with other land use
restrictions in Houston, the ordinance relies on a buffer test of neighboring land uses
to determine whether permits for the tower will be granted for a specific location.
The area subjected to the buffer test varies by the height of the tower: the higher the
tower, the larger the buffer test area.  Towers between 60 and 100 feet tall will be
denied permits if half or more of the tracts within a 375-foot circular buffer of the
124 Houston Code of Ordinances ? 10-273.
125 Houston Code of Ordinances ? 10-272.
126 Church steeples, amateur radio antennas, and government-owned antennas are excepted from these
rules.
45
tower are residential or residentially deed restricted.127  The buffer radius expands to
600 feet for towers 101 to 150 feet tall and 800 feet for towers 151 feet or taller.128
Furthermore, there is an absolute ban on tower construction if there are any
residences, residentially deed restricted lots, or designated historical
landmarks/districts within one and one-half times the height of the tower.129  Also, no
new towers or tower expansions are allowed in city-designated scenic areas or in
parks or tracts surrounding parks.130  Lastly, no towers are allowed within 1,000 feet
of any other towers that are subject to the above rules.131
Houston?s tower ordinance no doubt affects the location decisions for this
land use.  Surprisingly, the regulations restricting tower locations are in many ways
stricter than those regulating hazardous enterprises in that they entail absolute bans as
well as tests of the proportion of residential land uses nearby.  As with the other
buffer ordinances, however, the tower ordinance does nothing to prevent protected
uses (in this case, residences) from locating within the buffer zone after the tower has
been built.
Automotive and Scrap Metal Facilities
Automotive and scrap metal facilities are often viewed as eyesores.  In zoning
ordinances, they are typically segregated from other uses into light or heavy industrial
districts.   Houston has taken a buffering approach to regulating the locations of these
127 Houston Code of Ordinances ? 28-521.  Note that there are special provisions for adjusting the tract
count upwards when a multi-family apartment building(s) or condominium(s) occupies a single tract.
128 Houston Code of Ordinances ? 28-521.
129 Houston Code of Ordinances ? 28-524.
130 Houston Code of Ordinances ? 28-524.
131 Houston Code of Ordinances ? 28-524.
46
land uses.  The city has an ordinance that says that new automobile storage lots, open-
air used automobile part storage lots, used automotive parts recyclers, and open metal
recycler storage lots are disallowed within 300 feet of a church, school, or
residence.132  This certainly takes some parcels out of consideration for these land
uses.  Although an absolute ban within the buffer, like other city ordinances, the
ordinance does not prevent development of the protected uses within the buffer.
Hotels
Hotels can be perceived as a nuisance to neighboring residential uses due to
the traffic and activity they generate, often well into the evening.  Perhaps even more
concerning to nearby residents, however, are the activities that are perceived to
frequently occur at smaller low budget motels (e.g. drug dealing, prostitution, etc.).
Houston may have been especially focused on the latter types of establishments when
they enacted an ordinance regulating new hotel locations.  The ordinance is curious in
that it places more stringent regulations on smaller hotels than it does on larger
hotels.  For example, new hotels with 50 units or less, are not allowed to border
residential parcels but those with over 50 units can do so (albeit subject to modest
setback and screening requirements).133  This is quite the opposite of what one would
expect of the intent of the ordinance was to regulate hotels based on the bulk of their
buildings or the amount of traffic they generate.  Likewise, hotels with 50 units or
less are not allowed if over half of the parcels within a 1,500-foot buffer are
132 Houston Code of Ordinances ? 28-34.
133 Houston Code of Ordinances ? 28-202.
47
residential.134  The buffer size shrinks to 1,000 feet for hotels with 51 to 75 units.
There are no buffer test requirements for hotels with over 75 units.135
The city also uses the street system to regulate hotel location.  First, hotels of
any size can, generally, not take primary access from a residential street.136  Smaller
hotels (less than 120 units) without service facilities are also not allowed to abut any
street that has within 750 feet of the hotel a school, library, church, day-care center,
health facility, or public park.137  Here too, the city regulates smaller hotels more than
larger ones.  The focus of these regulations seems less about the street?s capacity to
handle traffic and more about ensuring public facilities and social centers are kept a
safe distance from small hotels that could harbor nefarious activates.  It should be
noted that all the rules on hotels, including those related to size requirements, do not
apply to bed and breakfasts or to any type of hotel within the CBD.138
Modular Homes, Manufactured Homes, and Recreational Vehicles
Modular homes (homes manufactured offsite but placed on a permanent
foundation), manufactured homes (mobile homes), and recreational vehicles (RVs)
used as homes are seen by many as unattractive and are often not allowed in single-
family neighborhoods in zoned communities.  Houston too has tried to limit the
locations of these types of residential uses.  Under the rationale of fire protection,
134 Houston Code of Ordinances ? 28-201.  Note that there are special provisions for adjusting the tract
count upwards when a multi-family apartment building(s) or condominium(s) occupies a single tract.
135 Houston Code of Ordinances ? 28-201.
136 Houston Code of Ordinances ? 28-202.  An exception is made for suite hotels that are apartment
conversions.
137 Houston Code of Ordinances ? 28-202.
138 Houston Code of Ordinances ? 28-205.
48
modular homes are not allowed to be constructed in the CBD or Medical Center
districts.139  This ban in some ways mimics zoning in that a given area, albeit
relatively small and unlikely to see development of modular homes given high land
values, is made off limits to a certain land use.
Manufactured homes and RVs used as homes face even stricter regulations.
These land uses are not allowed on individual lots anywhere within the city except in
places where they existed continuously since 1972 or when the area was annexed by
the city.  Instead, all manufactured homes and RV homes must generally be confined
to manufactured home parks/subdivisions or, in the case, of RVs, RV parks.140
Manufactured home parks, where lots are rented by homeowners for placement of
their trailer home, must be at least two acres in size and meet a variety of site
characteristics.  No mixing of land uses is allowed within these communities.141
Manufactured home subdivisions, where the land is owned by the homeowner, must
be a minimum of four acres in size and contain a deed restriction forbidding any
traditional permanent homes from being constructed within them.142    Curiously, this
ordinance, not one of the health and safety focused ones, is one of the few ordinances
that does not allow the protected uses, in this case single-family homes, from
choosing to locate near the use generating the (perceived) externality (manufactured
homes).
139 Houston Code of Ordinances ?? 10-235 and 29-15.
140 Houston Code of Ordinances ?? 29-15 and 29-58.
141 Houston Code of Ordinances ? 29-88.
142 Houston Code of Ordinances ? 29-135.
49
Moralistic Ordinances
The upholding of morals is part of the police powers granted to communities.
Many jurisdictions use zoning to limit the locations of businesses and facilities that
are perceived as threats to community social well-being.  Likewise, Houston, using its
buffer-based approach to land use restrictions, has ordinances in place that limit the
locations of (1) halfway houses, (2) bars and liquor stores, and (3) adult entertainment
venues.  Each of these restrictions is described in detail below.
Halfway Houses
Halfway houses, places for the housing and rehabilitation of (amongst others)
parole or early release prisoners, are perceived by many as hosting members of
society who present a danger to public morals and safety.  There is often a strong
desire to isolate these facilities from residential areas and other community facilities.
Houston has an ordinance in place that disallows halfway houses within 750 feet of a
school, church, community center, facility for the elderly, public park, or day care
center.143  Also, no halfway houses can be built within 1,000 feet of another halfway
house, an attempt to prevent their clustering.144  Furthermore, halfway houses are
disallowed if 75% or more of the tracts in a 1,000 foot buffer of the facility are put to
residential use.145 The ordinance no doubt influences the locations of halfway houses
in the city.  However, as with most of the city?s other buffer-based ordinances,
143 Houston Code of Ordinances ? 28-155.
144 Houston Code of Ordinances ? 28-155.
145 Houston Code of Ordinances ? 28-155.
50
nothing prevents a protected use from locating within the buffer after the hallway
house has been established.
Bars and Liquor Stores
Some view alcohol as a corrupting influence on society.  Throughout the
country, many laws and regulations remain on the books limiting the locations where
alcohol can be sold.  Houston is no exception.  The city disallows the selling of
alcoholic drinks within 300 feet of any school,146 church, or public hospital.147
Exceptions to these rules are made for higher end hotels in the CBD, restaurants,
grocery stores, and any type of alcohol vendor in a large high-density ?mixed land
use/entertainment zone.?  Also, no business (except restaurants) may sell alcoholic
drinks within 300 ft. of certain city council approved day care centers or child care
facilities in predominately residential areas.148   These laws, no doubt, prevent the
development of liquor stores and bars on some parcels.  That said, the effect of the
laws are limited given the relatively small size of the buffer test areas and the number
of exceptions allowed.
Sexually-Oriented Businesses
Sexually-oriented businesses such as adult bookstores and strip clubs are
viewed by many as being disreputable.  Many cities devote extensive portions of their
zoning codes to their regulation.  The geographic proliferation of adult bookstores in
146 Some schools have ?alcohol free school zones? that disallow the sale of alcohol within 1,000 feet of
the school property.
147 Houston Code of Ordinances ? 3-2.
148 Houston Code of Ordinances ? 3-4.
51
Houston, including a high-profile one in the Galleria mall area (the city?s premier
edge city), is often cited in books and presentations as a tangible outcome of the city?s
lack of zoning.  Sexually-oriented businesses, however, are not free to locate
wherever they choose in Houston.  The city has an ordinance in place that disallows
such businesses within 1,500 feet of a school, church, public park, or day-care
center.149  They are also disallowed if 75% or more of the tracts within the 1,500-foot
buffer are residential.150  In addition, to prevent clustering, no sexually-oriented
businesses are allowed within 1,000 feet of any other such business.151  The anti-
clustering provision is curious since many other cities encourage clustering of these
uses to prevent a wider distribution throughout the city.  Undoubtedly, these
restrictions ensure many parcels in the city are off limits to new adult entertainment
establishments.  That said, once again, protected land uses can locate within the
specified distances later if they so desire.
Discussion
This section has shown that Houston, despite lacking zoning, has several
regulations that focus directly on managing land use relationships.  These regulations
are primarily aimed at the siting of new locally unwanted land uses.  Without the
legal authority to use a zone-based system to limit the locations of such uses, the city
has fallen back on a buffer-based testing system that disallows the proposed use if
surrounding land uses are deemed incompatible.  That said, the number of uses
149 Houston Code of Ordinances ? 28-125.
150 Note that there are special provisions for adjusting the tract count upwards when a multi-family
apartment building(s) or condominium(s) occupies a single tract.
151 Houston Code of Ordinances ? 28-125.
52
subject to these special restrictions is limited and the criteria under which they are
disallowed are not particularly stringent when compared with most zoning regimes.
There are also important procedural differences in how Houston?s land use
ordinances are implemented relative to zoning; in particular, the degree to which
members of the public can participate in the process.  In zoned cities, public
involvement is a major factor in shaping land use outcomes.  First and foremost, the
initial development and adoption of a land use plan, zoning ordinance, and zoning
map involve extensive public participation.  Furthermore, once a zoning ordinance is
adopted, it provides a legal vehicle by which members of the public can continue to
participate in and shape the outcomes of proposed land developments as they are
proposed.152   Herein lies the biggest difference between Houston and zoned cities in
terms of public involvement in the land development process.
In Houston, unlike in zoned cities, the vast majority of land use changes
(except the few governed by the ordinances mentioned in this chapter) are,
essentially, allowed by right and not subject to a public hearing.  Even those few land
use changes covered by the ordinances mentioned in this chapter are dealt with, for
the most part, administratively by planning staff and involve limited community
participation (save for required public hearings if a property owner objects to the
findings of the planning staff).  By contrast, in zoned communities, a much smaller
set of land use changes are allowed by right.  Instead, many require some degree of
zoning change or special approval that trigger additional public processes which can
152 Although legally risky, it is not uncommon for communities to change zoning ordinances to try and
stop specific developments that are unwanted by the community but would otherwise be allowed by
right under the existing zoning ordinance.
53
alter or stop planned projects.  Thus, in a city without zoning, the public has much
less ability to weigh in on the development process and to help shape land use
outcomes.  The Ashby High Rise case mentioned previously is a prime example of
how even a politically connected and well-financed community has limited ability to
influence development outcomes in Houston.
Do these important differences in regulatory scope and procedure make a
difference on the ground?  Is Houston an outlier in terms of its land use relationships
as a result?  This study will help answer these questions.  First, however, previous
research into these questions is reviewed and summarized.
54
Chapter 3: Review of the Literature
A thorough review of the literature was undertaken to identify previous work
exploring zoning?s effects on land use patterns.  The review revealed that several
authors have discussed the subject but very few have conducted empirical work on it.
This chapter will summarize the information that was found.
The chapter is organized around two opposing perspectives on zoning?s
influence over land use patterns.  One perspective, discussed in this chapter?s first
section, maintains that zoning largely follows the market and that land use patterns in
zoned communities will not differ substantially from those in unzoned communities.
This would tend to happen if (1) planners pay close attention to market forces when
drafting plans and zoning ordinances, (2) allow many non-conforming uses153 to
continue after a zoning ordinance is adopted, and/or (3) readily permit property
owners to obtain variances154 from ordinances.  An opposing perspective, discussed
in the chapter?s second section, maintains that zoning is, in fact, binding in many
cases and constrains what the free market would otherwise do.  The implication of
this perspective is that land use patterns in zoned communities would differ
noticeably from those in unzoned communities.  The chapter concludes with a
summary of the gaps identified from the literature review.
153 Non-conforming uses are land uses that are not allowed in a zoning district but were grandfathered
in when the ordinance was either first adopted or the zoning changed.
154 Variances are allowed deviations from the letter of the ordinance.  Technically, variances are only
supposed to be granted in cases where, due to special property characteristics, strictly applying the
ordinance would cause undue hardship to the owner.  In practice, however, judging which cases are
?special? and rightfully deserve a variance is a grey area subject to interpretation.
55
Evidence that Zoning Follows the Market
Evidence that the land use patterns codified in American zoning ordinances do
not deviate greatly from the market has been accumulating since the very first
comprehensive zoning ordinance went into effect in New York in 1916.  Carol Willis,
in a historical analysis, noted that the zoning requirements in Manhattan tended to
closely match established land use patterns.155  Furthermore, she documents how, as
early as the 1920s, many of the reformers who helped get the ordinance passed had
grown disillusioned with the amount of development it allowed.  Excessive
skyscraper height continued to be a key concern with some feeling the ordinance had
only a minor impact on building heights.156
As the adoption of zoning spread rapidly during the 1920s and early 1930s, so
too did the feeling amongst planning advocates that zoning was being applied in a
way that was too accommodating to market pressures and not living up to its
potential.   By the second half of the 1930s, many notable planners were highly
concerned and began writing articles on the subject in planning journals.  In 1935,
Frederick L. Ackerman lamented how the zones in new ordinances were often based
simply on the land uses that were there prior to adoption; an observation consistent
with Willis? findings in New York.157  Ackerman decried how this resulted in zoning
maps that had a patchwork of small zones that resembled the ?chaos? of free market-
determined land use patterns.158  So-called ?spot zoning,? the application of a zoning
155 Willis, ?3-D CBD,? 14.
156 Willis, 20.
157 Ackerman, ?Zoning,? 21.
158 Ackerman, 21.
56
district to a single parcel of land to legalize an incompatible existing land use, became
a matter of serious concern amongst zoning advocates.159
Even in areas where new land use requirements ran counter to existing land
use patterns, the old uses were typically grandfathered in as non-conforming uses to
minimize political opposition to passage of the ordinance.  Efforts to codify horizon
years beyond which non-conforming uses must cease to exist often ran into strong
opposition.160  Thus, many non-conforming uses were allowed to continue
indefinitely (subject to limitations on physical expansions) until a lapse in that use
occurred.  The hope was that this policy of attrition would eventually lead to the
elimination of non-conforming uses.  However, many early planners became
impatient with the pace of this process.161  Prominent planners of the time such as
Harland Bartholomew, Alfred Bettman, and Paul Oppermann all railed against the
continuation of non-conforming uses in early planning articles, largely to no avail.162
It is possible that some of these legacy non-conforming uses may even continue to
this day.  The tendency of planners to allow the continuation of non-conforming uses
provide evidence that zoning, at least as practiced in the United States at the time,
was often accommodating of the market.
By the 1960s, zoning had been in place in many cities for three to four
decades, long enough to shape urban development patterns, and several authors began
159 Oppermann, ?Non-Conforming Use,? 94.
160 Ascher, ?New York City,? 347.
161 Ukeles, Consequences of Municipal Zoning, 40.  Illustrating the slow rate of attrition, a study
undertaken in Cleveland showed that 84% of the non-conforming uses created when the city adopted
zoning in 1929 were still in existence in 1954.
162 Bartholomew, ?Non-Conforming Uses;? Oppermann, ?Non-Conforming Use;? Bettman,
?Backward Step.?
57
to take stock of its effects.  These authors, writing in an era predating sophisticated
computer-enabled empirical analyses, worked mainly from observations.  Many
espoused a view that zoning had minimal effect on land use patterns in American
cities up to that time and that a new approach to land use was needed.  James E. Lee,
in a 1960 Land Economics article, summarizes this sentiment well:
So far from having transformed the landscape the landscape seems to have
transformed zoning.  We can visit cities that have had zoning thirty years, half
that long, or not at all.  In each case, we would find congestion, deterioration,
confusion, and disarray in about the same measure.  Where zoning has long
been established, its effect is not apparent.  Where it has been missing, its
absence has been hard to detect.163
Lee went on to note the pervasiveness of non-conforming uses in areas that were built
out before zoning as one reason for his views.  He also argued that zoning had been
applied arbitrarily and was not based on a rational understanding of externalities
between uses.  He called for a combination of performance and design standards,
based on a better understanding of the interactions between land uses, to be used in
lieu of zoning.
Jacob B. Ukeles, in a 1964 Urban Land Institute (ULI) book entitled The
Consequences of Municipal Zoning, espoused a similar viewpoint.  Ukeles felt that
zoning had, ?only marginal effects on land value and amenity, and almost negligible
effects on the distribution of space users in the city.?164  He noted the inability of
zoning to force the market into a land use pattern that was not profitable or desired.
In such cases, he argued the market would simply not construct the land use called for
163 Lee, ?Paradise Lost,? 297.
164 Ukeles, Consequences of Municipal Zoning, 61.
58
by the zoning.  Like Lee, Ukeles called for a regulatory system that was more
explicitly focused on managing the interactions between land uses, and allowed more
mixing of uses, rather than one that was based on discrete zones.165
Not all authors of this era felt that a different regulatory regime was the
answer to zoning?s woes, however.  Bernard H. Siegan, in his 1972 book Land Use
Without Zoning, called for zoning to be eliminated altogether and land use decision-
making returned to individuals acting in a free market.  He came to his conclusion
based on his analysis of land use patterns in Houston which, just as it is today, was
the only large city that had not adopted zoning.  Although there were many nuances
to his findings, his overarching assessment was that land use patterns in Houston were
not that different than those in other American cities (especially those that developed
rapidly in the post-war years).  His assessment rested on two basic observations: (1)
that land use patterns in zoned cities are not nearly as orderly as one might expect and
(2) that land use patterns in Houston are, in fact, more orderly than might be
expected.
With respect to zoned cities, Siegan, drawing upon his research and his own
experience as a land use attorney in Chicago, argued that zoning is often quite
malleable in response to market pressures.  He cited data from a variety of cities
showing that changes in zoning requested by property owners are, in most cases,
approved.166  He presented this as evidence that zoned cities often have land use
patterns that, in practice, essentially do not follow any plan and are more market
165 Ukeles, 64.
166 Siegan, Land Use Without Zoning, 14.
59
driven.167  He said this was especially the case in large cities, perhaps less so in the
suburbs.168
On the other hand, drawing upon his research in Houston, Siegan found that
market-driven land use patterns are not completely random and often resemble the
order (supposedly) imposed by zoning.169    For example, he noted how developers in
Houston create single-family residential neighborhoods that are just as homogenous
as those in zoned cities and how they use private covenants, in lieu of zoning, to keep
them that way.  Even in single-family neighborhoods where covenants have been
allowed to expire, Siegan found that there has not been a pronounced trend towards
diversification of land uses.170  He hypothesized that businesses have a disincentive to
move onto the interior streets of residential neighborhoods because they will be less
visible to passing motorists.171  Instead he observed that commercial land uses tend to
locate in a strip pattern along major thoroughfares with nodes at major intersections; a
pattern he also observed in zoned cities.172  Offices too were not scattered randomly
throughout Houston, instead clustering into districts as in zoned cities.173  He
observed that gas stations located themselves at major intersections.174  Likewise, he
noted that industrial land uses exhibited a clear pattern, clustering along railroads,
167 Siegan, 16.
168 Siegan, 76.
169 Siegan, 73.
170 Siegan, 39.
171 Siegan, 36.
172 Siegan, 46.
173 Siegan, 48.
174 Siegan, 48.
60
waterways, and major highways.175  He hypothesized that industry has a natural
disincentive to locate next to housing as it may generate bad publicity.176
Siegan synthesized his observations on Houston into an overarching theory
that market-driven land use patterns are not random and exhibit a ?natural order? that
is driven by convergences between each individual owner?s self-interest.177  He
contended that this natural order results in cities without zoning having land use
patterns quite like zoned cities.  To prove his point, Siegan discussed how he would
often share land use maps of zoned and unzoned Texas towns to people and see if
they could pick out which ones lacked zoning.  Often, people could not tell the
difference.178  Thus, Siegan came to view zoning as unnecessary, a motivator of
political corruption, and a waste of taxpayer resources and argued that cities would do
just as well without it.
Siegan?s conclusions drew strong reactions in the urban planning field.
Clifford L. Weaver and Richard F. Babcock, in their 1979 book City Zoning: The
Once and Future Frontier, while agreeing with Siegan that the market does tend to
create a natural order to land uses and that, at least in the CBDs of large cities, market
forces often prevailed over zoning,179 argued that abolishing zoning was going a step
too far.180  Writing during a period of increasing environmentalism, they noted that
even if market forces could distribute land uses like zoning, they could not manage
175 Siegan, 62.
176 Siegan, 62.
177 Siegan, 73 and 75.
178 Siegan, 74.
179 Weaver and Babcock, City Zoning, 4.
180 Weaver and Babcock, 222.
61
the environmental impacts from development in the same way that a zoning
ordinance could.181  Therefore, zoning was argued to still be valuable and necessary,
though in need of some reforms.  In the end, this is the view that prevailed, with
Siegan?s arguments to abolish zoning gaining little traction.
Nonetheless, Siegan?s viewpoints continued to reverberate for many years
after Land Use Without Zoning was published, especially in the libertarian
community.  For example, echoes of Siegan?s observations can be heard in a 1994
article by James D. Saltzman in the libertarian magazine The Freeman.  Saltzman, in
attempting to explain why Houstonians rejected zoning in the last referendum,
essentially argued that zoning was unnecessary because it does not make a major
difference in land use patterns.  He cited an example of one century-old Houston
residential neighborhood, Houston Heights, that, despite having virtually no land use
restrictions, remained 86 percent single-family after nearly 100-years.182  While he
acknowledged that there may be some odd land use juxtapositions in Houston, he
argued that they could be found in the same quantity in zoned cities.183  He concluded
that, ?In land-use patterns and in the predictability of those patterns, Houston and
zoned central cities are more similar than pro-zoners admit.?184
Saltzman?s views on zoning?s ineffectiveness, like Siegan?s and the zoning
advocates before him, were all based on personal observations and limited (if any)
technical analysis.  Rigorous empirical analyses on whether zoning tends to follow
181 Weaver and Babcock, 221.
182 Saltzman, ?Houston says No to Zoning,? 432.
183 Saltzman, 433.
184 Saltzman, 433.
62
the market or is binding did not start appearing until the 1980s.  Barbara Sherman
Rolleston, in a 1987 Journal of Urban Economics article, conducted an empirical
analysis of zoning on vacant developable land in northern New Jersey.  She found
that zoning tended to follow the market, at least with respect to residential land use.
Her findings indicated that, where there is more demand for residential uses due to
higher job density, zoning often accommodated higher density housing.185   A similar
finding was made by Chakraborty et al. during an analysis examining the relationship
between zoning and housing construction in six major United States metropolitan
areas.186
Further empirical evidence that zoning follows the market was provided in a
1990 study of zoning patterns in Chicago?s northwest suburbs by Daniel P. McMillen
and John F. McDonald.  The authors looked at spatial patterns in the area?s zoning
from the early 1960s through the 1980s.  They found notable patterns to zoning that,
according to the views of the authors, seemed to match the land use patterns one
would expect from market forces.  For example, they found that single-family zones
tended to be located away from major highways and rail lines.187  Multi-family,
manufacturing, and business/commercial zones, on the other hand, tended to be
located closer to rail lines with manufacturing zones also often being located near
major highways.188  The authors concluded that zoning designations are influenced by
185 Rolleston, ?Determinants of Restrictive Suburban Zoning,?17.
186 Chakraborty et al., ?Effects of High-density Zoning,? 446.
187 McMillen and McDonald, ?Two-Limit Tobit Model,? 277.
188 McMillen and McDonald, 277.
63
transportation facilities and therefore by market forces associated with
accessibility.189
In 1991, Andrew J. Cappel published an interesting historical study comparing
pre- and post-zoning land uses in New Haven, Connecticut.  The study corroborated
Siegan?s observations that zoning makes little difference to land use patterns and that
land uses tend to order themselves naturally based on market forces.  Cappel gathered
land use and building data from Sanborn maps that were published prior to the city?s
adoption of zoning.190  He then compared what was shown on the maps to what was
required subsequently under the zoning ordinance.  He noted that, prior to zoning,
industry was already clustered in certain areas of the city while commercial uses were
grouped in the CBD or on street corners in residential areas; a pattern that matched
the use districting later required by the code.191  Building heights, setbacks, lot sizes,
and lot coverages were also already found to be relatively uniform prior to zoning,
despite small-scale piecemeal development.192  He reasoned that nuisance law,
neighborliness, and transportation facilities helped shape a land use pattern that
minimized land use conflicts.  His overall conclusion was that zoning merely codified
existing market-driven land use and building patterns.
By the early 1990s, enough studies had been done into zoning to warrant a
literature review of its effects.  The survey, conducted by J. M. Pogodzinski and Tim
R. Sass, summarized the literature to date on a host of issues involving zoning and
189 McMillen and McDonald, 281.
190 Cappel, ?Walk Along Willow,? 621.
191 Cappel, 622.
192 Cappel, 624 and 626.
64
economics.  One of the topics they focused on was whether zoning tends to follow the
market or is binding.  The authors found that most of the research up to that time
indicated that zoning, indeed, followed the market,193 however, they did note some
studies that provided contrary findings.  The next section summarizes literature that
indicates zoning may have a greater influence on land use patterns than the sources
just mentioned suggest.
Evidence that Zoning is Binding
Arguments that zoning has been effective at forcing land uses into a pattern
different from what the free market would have created date back to some of the
earliest American planning literature.  For example, Thomas Adams and Harland
Bartholomew, in response to Ackerman?s previously mentioned article on zoning?s
ineffectiveness,194  offered some defense of the tool.  The authors argued that zoning
had, in fact, prevented several incompatible land uses from locating in established
neighborhoods.195  They acknowledged that the effects were less pronounced in large
cities but stated that they believed zoning was proving to be very effective at shaping
land use patterns in mid-sized cities and suburbs.196  Similar observations were
expressed nearly thirty years later by Carl Feiss in a 1961 Journal of the American
Institute of Planners article.  Within the article, Feiss noted that, based on his
observations, zoning had ?barely discernible? effects in older parts of cities but that in
193 Pogodzinski and Sass, ?Measuring the Effects,? 617.
194 Ackerman, ?Zoning,? 21.
195 Adams and Bartholomew, ?Zoning: Discussion,? 66.
196 Adams and Bartholomew, 66.
65
higher end single-family neighborhoods it was very effective at limiting the intrusion
of incompatible uses.197
The belief that zoning was proving effective at fostering homogenous single-
family neighborhood was also expressed by Richard F. Babcock in his 1966 book The
Zoning Game: Municipal Practices and Policies.  In his book, Babcock included a
brief discussion of Houston and how, based on his observations, it differed from Los
Angeles, a zoned city of comparable age.  The primary difference he observed
involved the degree of homogeneity in single-family areas.  He claimed that in Los
Angeles the single-family neighborhoods were largely homogenous while in Houston
there was more mixing in of other land uses (especially small shops).198  Note that
this observation differs somewhat from Siegan?s later writings, which downplayed
any mixing of land uses in single-family areas in Houston.
Seymour I. Toll, in his 1969 book, Zoned American, also noted the perceived
effectiveness of single-family zoning.  He asked planners what they thought would
happen if the zoning ordinances were rescinded in their communities and they
responded that the higher end residential areas would likely be the ones most
affected.199  They foresaw apartments and commercial businesses moving into these
areas and Toll notes that there was some evidence this had happened in Houston.200
197 Feiss, ?Planning Absorbs Zoning,? 124.
198 Babcock, Zoning Game, 28.
199 Toll, Zoned American, 300.
200 Toll, 300.
66
He also foresaw the possibility of industrial uses encroaching on lower-income
residential neighborhoods.201
John Delafons, a British author who investigated American land use policies,
observed similar patterns in his 1969 book Land-Use Controls in the United States.
Like Siegan, he felt that, overall, Houston?s land use patterns resembled those of
zoned cities,202 however, he did note some differences that revealed themselves upon
closer inspection.  Many of these differences manifested themselves in residential
neighborhoods, particularly lower-income ones.  For example, in low-income
African-American neighborhoods, he observed apartments built to much higher
densities and with more limited setbacks than in other cities of comparable age.203
Even in wealthier single-family neighborhoods, he noted that side-yard setbacks were
much smaller than in zoned communities.  In fact, he observed that houses in one
subdivision even had overlapping roofs.204  He also commented on how residential
uses were more at risk of commercial uses being built nearby than in zoned cities.205
Delafons also noted how commercial uses in Houston tended to be more
oriented in a strip development pattern along major streets than they were in other
cities.  He ascribed this to residential developers who held parcels along major streets
in reserve for commercial uses that could be developed after the occupants of the new
homes moved in.  He reasoned that developers could get a higher price for highly
visible commercial lots in an unserved area than they could if they initially developed
201 Toll, 300.
202 Delafons, Land-Use Controls, 91.
203 Delafons, 91.
204 Delafons, 91.
205 Delafons, 92.
67
the lots as homes (which would probably need to be sold at a discount because of
their locations on busy thoroughfares).206  In Houston, this decision was left up to
developers based on their own best interests whereas in other cities the zoning code
may forbid the practice and require single-family along major streets for aesthetic
reasons.
Even Siegan, despite his overarching viewpoint that the free market is capable
of distributing land uses similarly to zoning, did acknowledge some differences in
Houston?s land use patterns relative to zoned cities.  Like Delafons, he observed in
Houston a tendency towards more strip commercial development along major roads,
whereas zoned cities may have more single-family development.207  And, like
Delafons, Toll, and Babcock, he acknowledged that there may be some mixing of
commercial land uses into residential areas where covenants have expired.  He
hypothesized that the types of businesses that may do so would be those for which
accessibility and visibility are not important, those catering to a local clientele, home
occupations, and businesses spilling over from nearby strip commercial areas.208
Siegan downplays this intermixing though saying it is generally of limited scope,
differs little from zoned areas where such uses may occur illegally anyway, and that it
may even be a good thing to have some commercial uses near residences.209
Also, like Delafons, Siegan did note a tendency towards smaller lots and
smaller setbacks in Houston?s single-family neighborhoods compared with those in
206 Delafons, 92.
207 Siegan, Land Use Without Zoning, 46.
208 Siegan, 41.
209 Siegan, 42 and 43.
68
zoned cities.210  In addition, he found accessory housing units on single-family lots to
be more prevalent in Houston than in zoned cities.211  However, the biggest difference
Siegan noted between zoned cities and Houston related to the quantity and location of
apartments.  Siegan felt that Houston, for its size, had more apartments than zoned
cities.  This could be attributed to the tendency for zoned cities to limit the amount of
land zoned for multi-family housing.212  Siegan also acknowledged a trend of high
density apartments being built in single-family areas with no covenants and strong
housing demand; a pattern not typically found in zoned cities.213
As zoning research became more quantitative starting in the early 1980s, the
question of how zoning was shaping development patterns continued to be of interest.
Much focus was placed on determining whether zoning increased or decreased
property values, a question tied, in part, to its potential to limit land use choices
relative to what the market demands.  One such study dating from 1981, by Jonathan
H. Mark and Michael A. Goldberg, explored the price impacts from land use controls
on residential neighborhoods in Vancouver, British Columbia, Canada.  The study
focused on re-zonings that allowed multi-family housing to be built in two
exclusively single-family neighborhoods.  The authors found that the up-zoning of
one of the neighborhoods allowed for significant re-development to denser housing
(and higher sales prices) whereas the up-zoning for the other did not. 214  Thus, the
210 Siegan, 50 and 59.
211 Siegan, 50.
212 Siegan, 76.
213 Siegan, 41.
214 Mark and Goldberg, ?Land Use Controls,? 424.
69
study indirectly indicated how zoning can, in fact, be binding if demand for a
disallowed land use (in this case, higher density housing) is high.
Later in the decade, Nancy E. Wallace researched whether zoning of
undeveloped land in King County, Washington (the county that contains Seattle)
followed the market or was binding.  While she concluded that, in general, the zoning
of undeveloped land in King County reflected market-driven land uses, she did note
some exceptions.  For example, she found that the zoning likely provided for more
large lot residential development than the market demanded.215  Also, she found that
commercial and manufacturing zones were likely undersupplied relative to market
demands.216
An interesting historical analysis by Daniel P. McMillen and John F.
McDonald in the early 1990s also touched on whether zoning follows the market.
Their research looked at the initial adoption of zoning by Chicago in 1923 and
focused on whether the new ordinance enhanced land values.  As part of their work,
they evaluated the zoning categories applied to various existing land uses.  This
documentation provided invaluable information regarding to what degree the zoning
followed the market (i.e., permitted the established land uses) or went against it.  Like
many first-generation zoning ordinances, Chicago?s ordinance was hierarchical with
residential uses given preference.  Thus, the city had a residential-only zone and
zones that allowed mixing of residences and other uses.
215 Wallace, ?Market Effects of Zoning,? 323.
216 Wallace, 325.
70
The authors looked at existing land uses on a block-by-block basis and found
that the zoning adopted generally matched the existing uses provided by the market.
Thus, if blocks consisted exclusively of residential land uses, they were almost
always put in the residential-only zone.217  Likewise, if blocks were exclusively non-
residential, they were almost always put in one of the zones that allowed non-
residential uses.  Many blocks in the city, however, consisted of a mix of land uses.
Rather than assign all these blocks to the zones that allowed mixing, around half the
blocks were assigned to residential-only zones.  The authors found a greater tendency
for this to happen if the land value premium from non-residential uses was low, there
was a greater proportion of residential uses, or it was not on a major street or rail
line.218 The assigning of mixed land use areas to residential only zones shows how
zoning can be implemented in a way that runs counter to the market.
Another historical analysis of zoning was performed by York et al. in 2014.
Their research focused on Phoenix, Arizona?s first zoning ordinance (dating to 1930)
and its impact on environmental justice.  As part of their analysis, they investigated
the degree of land use homogeneity within each zoning category prior to and after the
adoption of zoning.219  The authors conclude that zoning was effective at creating
more land use homogeneity in the residential and industrial zones but less
homogeneity in the multi-family, commercial, and light industrial zones.220  The
increase in homogeneity in the single-family zones is consistent with the observations
217 McMillen and McDonald, ?Land Values in Chicago,? 185.
218 McMillen and McDonald, 186.
219 York et al., ?Zoning and Land Use,? 837.
220 York et al., 841.
71
of some of the earlier authors who claimed that zoning was proving most effective at
protecting single-family neighborhoods.  The findings of less homogeneity with
zoning, however, are somewhat counterintuitive and the authors do not make clear if
it is a result of the zones themselves allowing a mix of uses, extensive use of zoning
variances/re-zonings after the ordinance went into effect, a side-effect of their grid-
based reporting metrics, or some other factor.221
Consistent with the findings and observations that zoning is effective at
protecting single-family neighborhoods, a large body of literature on affordable
housing has been developed in recent years that implicitly assumes that zoning is
binding, at least with respect to residential densities.  The general contention is that
many municipalities, particularly suburban ones, use their zoning ordinances to
disallow multi-family and other denser housing types that the market would otherwise
provide, favoring construction and protection of more expensive single-family homes.
This supply constraint is argued to result in higher housing prices for all, exacerbating
the affordability crisis.  Jonathan Levine made this argument a central focus of his
2006 book Zoned Out: Regulation, Markets, and Choices in Metropolitan Land Use.
In the book, he offers much evidence that zoning is binding with respect to residential
density and, were zoning to be eliminated, residential densities would be much higher
in many neighborhoods.222  Likewise, Joseph Gyourko and Raven Molloy, in their
chapter on ?Regulation and Housing Supply? in the 2015 Handbook of Regional and
221 York et al. (841) seem to indicate that the findings could be a result of mixed uses being allowed in
the zones.  However, in doing so, they misstate that Euclidean zoning allows higher order land uses
within lower level zones; something that is instead a hallmark of hierarchical zoning.
222 Levine, Zoned Out, 52.
72
Urban Economics, Volume 5A state that the preponderance of evidence to date is that
zoning often runs counter to the market when it comes to residential density and
allowable housing types.223
William A. Fischel, a prominent author in the field of urban economics, has
also recently weighed in on whether traditional Euclidean zoning is effective at
shaping land use patterns.  In his 2015 book Zoning Rules! The Economics of Land
Use Regulation, he argues strongly for the continued use of traditional Euclidean
zoning.  He claims that, ?Without some check on private behavior, the uncoordinated
efforts of developers are apt to mix incompatible uses excessively and build too
intensively.?224  Obviously, this statement assumes that zoning can be binding and
shape land use patterns.
An entire movement, New Urbanism, has, in fact, formed around the concept
that Euclidean zoning has had a large (negative) impact on the built environment and
that a new form of land use regulation is necessary.  Emily Talen, in her book City
Rules: How Regulations Affect Urban Form, documents many examples of zoning?s
impact on land use patterns.225  She then uses the examples as an argument for why a
different, finer-grained approach to regulating land use relationships is needed.
Thus, over the course of many years, several authors and researchers have
concluded that zoning has markedly shaped land use patterns in America?s cities.
Some have argued that the results are desirable, others just the opposite.  Either way,
there is agreement by many that there are situations when zoning can be binding and,
223 Gyourko and Molloy, ?Regulation and Housing Supply,? 1,315.
224 Fischel, Zoning Rules!, 327.
225 Talen, City Rules.
73
therefore, that it can change land use patterns relative to what the free market would
have created.
Gaps in the Literature
The literature review uncovered a wealth of information focusing on zoning?s
effectiveness at altering land use patterns and other aspects of urban development.  As
discussed, many prominent authors have argued that zoning, at least as practiced in
the United States, has largely followed the market.  The implication of this viewpoint
is that an unzoned city, like Houston, should have land use relationships that are, for
the most part, consistent with those of zoned cities.  On the other hand, many other
prominent authors have argued that zoning can be binding and that it plays a large
role in shaping land use patterns.  The implication of this viewpoint is that Houston
would be likely to have a very different land use relationships than zoned cities.
Which of these points of view is more accurate?  Unfortunately, the literature review
uncovered no studies that can definitively answer this question.  There have simply
been no studies that, in a systematic and quantitative way, compared land use
relationships across American cities let alone any that convincingly used this data to
determine if land use relationships in unzoned cities are distinct from those in cities
with zoning.
These gaps in the literature are not because researchers did not recognize the
value of such research; more so because they lacked the data and computing
resources needed to undertake it.  The first references to the need for a comparative
study date as far back as the 1960s.  For example, in Jacob B. Ukeles? 1964 book The
Consequences of Municipal Zoning, he states that he initially intended to carry out an
74
empirical investigation of zoning?s effects on land use across multiple cities but that
data was simply not available (his book ended up being a theoretical work on the
topic instead).226  A few years later, Seymour I. Toll, in his 1969 book Zoned
American, laments how no study investigating zoning?s true impact on land use
patterns in various cities had ever been done.227
The challenges involved in undertaking a quantitative comparative analysis
were also documented by Bernard H. Siegan in his 1972 Land Use Without Zoning
book studying Houston?s land use patterns.  While recognizing the desirability of
such an analysis, he concluded that, ?it would seem impossible to evaluate the
aesthetics and physical composition of over 450 square miles of real estate
[Houston?s land area at the time he was writing] and compare such a determination
with a similar area elsewhere.?228  For this reason, he opted to undertake a more
qualitative observation-based comparison between Houston and zoned cities with
which he was familiar.
Over 10 years later, in 1987, Patricia Burgess Stach, in a Journal of Planning
Literature article focused on reviewing the literature on zoning?s effects, noted that a
study documenting how zoning has shaped cities remained a gap.  In the article, she
asked,
How has the application of zoning shaped our cities?  Or has it?  Do American
cities and suburbs look the way they do despite zoning rather than because of
it?  Most of the literature examined here focused on the process in some way
or other rather than the product ? that is, the city itself.229
226 Ukeles, Consequences of Municipal Zoning, 1.
227 Toll, Zoned American, 300.
228 Siegan, Land Use Without Zoning, 45.
229 Burgess Stach, ?Zoning ? To Plan or to Protect?,? 480.
75
Even as recently as 2012, Arthur O?Sullivan stated in his Urban Economics textbook
that, ?a rigorous comparison of land-use patterns [between Houston and other cities]
may be impossible.?230  Fortunately, with the advent of GIS technology and the
widespread public dissemination of GIS-compatible parcel-level land use data, such
an analysis is now finally practical.
230 O?Sullivan, Urban Economics, 239.
76
Chapter 4: Methodology
To address the gaps in the literature noted in the last chapter, this study
utilized a cross-sectional research design to quantitatively compare current land use
relationships in large American cities using parcel-level land use data.  This chapter
describes the methodology employed for doing so and for determining if Houston,
with its lack of zoning, is an outlier.  The chapter begins by stating the overarching
research question and the accompanying hypotheses.  Following this are sections
describing the process of selecting study cities, the land use data, the schema for
harmonizing land use classifications across cities, the land use metrics computed, and
the techniques used for comparing cities.
Research Question and Hypotheses
Given the long-standing debate on Houston in the literature and the stated
desire for, but dearth of, quantitative studies comparing land use relationships
amongst American cities, the overarching research question this study aimed to
answer is:
Are Houston?s land use relationships unique amongst large231
American232 cities?
231 Large cities, in this case, refers to city population, not land area.  The decision to focus the
comparison on large cities was made for two reasons.  First, large cities are most likely to have the full
range of land uses present within their borders whereas smaller jurisdictions may not.  Not having the
full spectrum of land uses would make comparisons with Houston less useful.  Second, the pressures
for urban redevelopment and land use change are often less in smaller jurisdictions, potentially taking
this important shaper of land use patterns out of consideration for the comparison.
232 While many cities around the world use zoning, it was decided to focus only on American cities for
this initial study.  Zoning governance varies greatly by country.  Limiting the study to only American
cities keeps the comparison with Houston focused on locations that are subject to relatively similar
77
Note that while the research question focuses on how Houston?s land use
relationships compare with other large central cities, this study also explored how
land use relationships in Houston compare to its zoned suburban municipalities.233
Also, note that, per Chapter 2, zoning affects land use patterns in many ways
(location of uses, density, building setbacks, etc.).  Due to data limitations, this study
focuses strictly on land use spatial relationships. Further research will need to be
undertaken to ascertain whether Houston is unique across other aspects of land use
patterns that zoning could influence.
The following are the null and alternative hypotheses associated with the
research question:234
? Null hypothesis: Land use relationships in Houston are not unique
amongst large American cities.
? Alternative hypothesis: Land use relationships in Houston are unique
amongst large American cities.
The null hypothesis in this case aligns with those who argue that zoning, as practiced
in the United States, tends to follow the market and/or is redundant because the land
development process is self-regulating.  In contrast, the alternative hypothesis aligns
more with those who argue that zoning is binding and has affected land use
legal regimes, policies, and cultural traditions.   That said, a comparison of land use patterns amongst
cities around the world is worthy of consideration for future research.
233 The city of Houston and surrounding unincorporated areas have no zoning, however, several
smaller municipalities within the Houston metropolitan area do have zoning ordinances.  Houston?s
suburban jurisdictions with zoning will be considered collectively as one entity in the analysis to
mitigate against the issues with comparing a large city like Houston to smaller towns.
234 Although written to focus on the research question?s comparison between Houston and other large
cities, these hypotheses can also be applied to the comparison between Houston and its zoned suburban
municipalities as well.  To do so, simply substitute the words ?compared to its zoned suburban
municipalities? for ?amongst large American cities.?
78
relationships.  With this line of reasoning Houston is unique with respect to land use
relationships, potentially because of its lack of zoning.
The word ?potentially? is emphasized above because the results of this study
cannot, in and of themselves, provide enough evidence to definitively conclude that
zoning (or the lack thereof) is the primary driver of any differences observed.  This is
because variables other than zoning could influence land use relationships amongst
the cities.  While the comparison between Houston and its zoned suburban
municipalities will help control for some of these potentially confounding variables
(e.g., geographical, historical, and cultural differences between cities), the findings of
this analysis will only be drawn from a single case, the Houston region, making it
hard to draw broader conclusions for other cities in the country without further
research.  Thus, if the null hypothesis is rejected, further research, building on the
findings of this analysis, will be required to ascertain whether any land use
relationship differences between Houston and other cities are, in fact, definitively due
to zoning.
Even if the null hypothesis were to be rejected, an exploratory research study
like this is an important first step towards understanding the impacts of zoning on
land use relationships.  This is because the findings of the cross-sectional analysis can
be used to identify the most promising cities for follow-on research into causality.
For example, the cross-sectional analysis may reveal that some cities have land use
relationships like Houston?s and others do not.  Using this information, subsequent
research (e.g., qualitative studies of zoning governance at the city level, longitudinal
studies of land use change pre- and post-zoning, etc.) can be targeted at the cities that
79
differ substantially from Houston to help understand whether these cities were always
different or were once more like Houston and evolved after zoning was adopted.
Thus, doing the cross-sectional analysis first will enable better identification of study
locations and more nuanced research questions for subsequent causality-focused
studies.
Selection of Study Cities
Several cities were included in the analysis to provide a robust basis for
evaluation and comparison of land use relationships.  Altogether, a total of 49 large
cities235 (inclusive of Houston) were evaluated along with 33 zoned municipalities in
Houston?s immediate environs.236  Figure 7 shows a map of the major cities included
in the study and Figure 8 shows a map of the municipalities in the Houston area that
were analyzed.  With respect to the latter, while many individual municipalities are
shown on the map, they are considered collectively as one entity in the study to
235 The original intention was to study 50 of the largest cities in the United States, however, land use
data for one of these cities, San Jose, was not readily available leaving 49 cities to study.  The choice
of 50 cities was somewhat arbitrary and driven primarily by the desire to include (nearly) the universe
of all large American cities in the analysis.
236 The selection of suburban jurisdictions focused on those that were directly connected to the city of
Houston by urban development: isolated communities with zoning located farther out in the
metropolitan area were not included. Note that three suburban jurisdictions (Pasadena, Humble, and
Kemah) that are connected to Houston by urban development were nevertheless not included in the
comparison because they, like Houston, have not adopted zoning.  All unincorporated areas in the
metropolitan area are also unzoned and not included in the study.  Lastly, the small portions of Katy
and Baytown outside of Harris and Fort Bend Counties are also not included in this study due to lack
of readily accessible data for these areas.
80
provide a more appropriate point of comparison with Houston and other large
cities.237
As shown in Figure 7, the study includes a geographically diverse set of cities
covering all regions of the country.  The colors of the dots on the map indicate the
geographic region each city has been assigned to; a classification that will be used to
flag regional patterns to the findings in addition to determining whether Houston is an
outlier.  Note that most of the major cities included in the analysis are the central
cities in their metropolitan areas, however, there are a few instances (besides
Houston) where multiple cities from the same metropolitan area are represented.  In
three of these cases this occurs when there are two or more larger older cities
clustered together (Los Angeles and Long Beach; San Francisco and Oakland; Dallas
and Fort Worth).  However, there are also two cities, Arlington, Texas and Mesa,
Arizona, that, while they developed from older small towns, are, by and large, newer
suburban communities238 that grew rapidly in the last several decades.
237 Several of the zoned suburban municipalities are so small that they do not include the full range of
land uses that can be found in Houston and other large cities making direct comparisons with these
larger jurisdictions less useful.
238 Arlington is a suburb of Dallas and Fort Worth while Mesa is a suburb of Phoenix.
81
Figure 7: Map of Study City Locations Showing Regional Classification
82
Figure 8: Map of Houston Area Study Cities
83
Land Use Data
Detailed data on the current use of land within each selected city is
foundational to this study.  As noted in the literature review, lack of detailed land use
data has been one of the primary impediments preventing researchers from addressing
this study?s research question.  Raster data on land use/land cover derived from
remote sensing has been available for several decades and many researchers have
used it to study urban sprawl, however, it is generally too coarse to be used for
comparing land use relationships within developed urban areas.  With remotely
sensed data it is also difficult to differentiate various urban land uses (e.g., a duplex
from a single-family detached home); an important consideration for this study.
Furthermore, the data, being gridded in a raster, do not relate directly to geographic
boundaries that are meaningful to property owners. What is needed is land use data at
the scale of individual land parcels; data that was difficult to obtain in the past but is
now available.
Parcels are legally defined units of land that are created by governments to
define and track land ownership rights and responsibilities.  They are the smallest
geographic unit for which land use information is captured.  Because they correspond
to land ownership boundaries, they are inherently meaningful to property owners.
Parcels are also customarily used in the zoning process to establish zone boundaries
and define the units of land for which the individual zoning requirements apply to.
For all these reasons, parcels were chosen as the basic geographic units of measure
for this study.
84
Despite its advantages, using parcel data for a study like this does have some
limitations that should be noted.  First, some parcels can be quite large and land uses
on a neighboring parcel may be far removed from the buildings on the parcel next
door.  For example, a large single-family residential parcel may border a commercial
parcel but the single-family structure itself may be on one end of its parcel and the
commercial structure on the far end of the other parcel.  This distance between the
structures may tend to mitigate any externalities between the uses.  Unfortunately,
such detail cannot be easily captured in an analysis where parcels are the geographic
units of measure.  That said, given this study?s focus on urban areas, most parcels will
tend to be smaller thereby mitigating this issue in most cases.
A second limitation with using parcel data is that it does not consider any
buffering or design elements that may also help to mitigate externalities between
uses.  In the previous example, even if the single-family residential and commercial
structures were near each other, there could be dense vegetation or design features
(including walls and fences, well-apportioned building massing, etc.) that help to
separate them or otherwise enhance their compatibility.  Indeed, many zoning
ordinances require these sorts of measures where use districting alone cannot manage
all externalities.  However, important as these mitigation measures are, data on them
is very limited and such a high level of detail is currently not possible to consider
here.  In the future, data on such features may become more widely available enabling
consideration of these elements in follow-on research.
At this point in time, just obtaining parcel data remains a challenging and
time-consuming affair.  Most parcel data (and associated land use information) is
85
developed and maintained by local or county government taxing agencies who need
this information for conducting property tax assessments.  Thus, there is no freely
available nationwide repository for the data where it can all be obtained in one
location, for a common date, and with common formatting.  Instead, one must go to
each jurisdiction, search for the latest data on their website(s), download it, and
understand how best to use it.   This task proved to be a major undertaking.
Table 1 documents the parcel data that was acquired for the study cities and
used in the analysis.  The Primary Land Use Dataset column shows the source and
vintage of the main land use dataset used for the analysis.239  In most jurisdictions, the
land use information was already joined to GIS features showing the parcel
boundaries.  These jurisdictions appear in the table as having only the Primary Land
Use Dataset column filled and nothing shown for the Parcel Boundary Data column.
239 In some cases, the main land use dataset needed to be augmented with secondary data sources to
properly characterize the land uses on all parcels.  Due to space limitations, these secondary data
sources are not shown in Table 1 but information on them can be obtained by contacting the author.
86
Table 1: Data Sources and Dates for Parcel Level Land Use Information Used in this Study
Primary Land Use (LU) Dataset Parcel Boundary Data
Jurisdiction (if separate from LU data)
Source Year Source Year
Albuquerque City of Albuquerque 2018 City of Albuquerque 2018
Arlington (TX) Tarrant CountyAppraisal District 2018 - -
Atlanta240 Fulton County 2017 - -
Austin City of Austin 2016 - -
Baltimore Maryland Departmentof Planning 2018 - -
Boston City of Boston 2016 - -
Charlotte City of Charlotte 2015 - -
Chicago Chicago MetropolitanAgency for Planning 2013 Cook County 2013
Cleveland Cuyahoga County 2017 Cuyahoga County 2018
Colorado
Springs El Paso County 2018 El Paso County 2018
Columbus
Delaware Co.
portion Delaware County 2018 - -
Fairfield Co.
portion Fairfield County 2018 - -
Franklin Co.
portion Franklin County 2018 - -
Dallas City of Dallas 2017 City of Dallas 2017
Denver City of Denver 2018 - -
Detroit Southeast MichiganCouncil of Governments 2015 City of Detroit 2018
El Paso El Paso CentralAppraisal District 2017 - -
240 A small portion of Atlanta also extends into DeKalb County.  Parcel level land use data was not
readily available for this jurisdiction. Thus, this study only considered the Fulton County portion of
Atlanta.
87
Primary Land Use (LU) Dataset Parcel Boundary Data
Jurisdiction (if separate from LU data)
Source Year Source Year
Fort Worth241
Denton Co. Denton Central 2018 Denton Centralportion Appraisal District Appraisal District 2018
Tarrant Co. Tarrant County
portion Appraisal District 2018 - -
Fresno City of Fresno 2017 City of Fresno 2018
Houston and its
zoned suburbs
Brazoria Co. Brazoria CountyAppraisal District 2019 - -
Fort Bend Co. Fort Bend CentralAppraisal District 2018 - -
Galveston Galveston Central
Co. Appraisal District 2019
Galveston Central
Appraisal District 2019
Harris Co. Harris County 2018 Harris CountyAppraisal District Appraisal District 2018
Montgomery
Co. Montgomery County 2018 - -
Indianapolis Indiana GeographicInformation Office 2018 - -
Jacksonville Florida Department Florida Departmentof Revenue 2018 of Revenue 2018
Kansas City
(MO) City of Kansas City 2018 - -
Las Vegas Clark County 2017 - -
Long Beach Los Angeles County 2014 - -
Los Angeles Los Angeles County 2014 - -
Louisville/Jefferson
Louisville County Information 2018 - -
Consortium
Memphis Shelby County 2018 Shelby County 2018
Mesa Maricopa CountyAssessor?s Office 2014
Maricopa County
Assessor?s Office 2014
Miami Miami-Dade County 2018 - -
Milwaukee City of Milwaukee 2018 City of Milwaukee 2018
Minneapolis Hennepin County 2018 - -
241 Small portions of Fort Worth also extend into Parker and Wise Counties. Parcel level land use data
was not readily available for these jurisdictions.  Thus, this study only considered the Denton and
Tarrant County portions of Fort Worth.
88
Primary Land Use (LU) Dataset Parcel Boundary Data
Jurisdiction (if separate from LU data)
Source Year Source Year
Nashville City of Nashville 2018 - -
New York City of New York 2018 - -
Oakland Alameda County 2017 Alameda County 2018
Oklahoma
City242
Canadian Co. Canadian County
portion Assessor?s Office 2018 - -
Cleveland Co. Cleveland County Cleveland County
portion Assessor?s Office 2019 Assessor?s Office 2019
Oklahoma Oklahoma County 2019 Oklahoma CountyCo. portion Assessor?s Office Assessor?s Office 2019
Omaha Douglas County 2018 - -
Philadelphia City of Philadelphia 2018 - -
Phoenix Maricopa County 2014 Maricopa CountyAssessor?s Office Assessor?s Office 2014
Portland (OR)243 Multnomah County 2017 - -
Raleigh
Durham Co.
portion Durham County 2018 - -
Wake Co.
portion Wake County 2018 - -
Sacramento Sacramento County 2018 - -
San Antonio Bexar Appraisal District 2014 Bexar Appraisal District 2014
San Diego San Diego Association 2017 San Diego Associationof Governments of Governments 2018
San Francisco City of San Francisco 2017 City of San Francisco 2017
Seattle King County 2018 - -
Tucson Pima County 2018 - -
Tulsa244 Tulsa County Assessor 2018 - -
242 A small portion of Oklahoma City also extends into Pottawatomie County.  Parcel level land use
data was not readily available for Pottawatomie County.  Thus, this study only considered the
Canadian, Cleveland, and Oklahoma County portions of Oklahoma City.
243 Small portions of Portland also extend into Washington and Clackamas Counties.  Parcel level land
use data was not readily available for these jurisdictions.  Thus, this study only considered the
Multnomah County portion of Portland.
244 Small portions of Tulsa also extend into Osage and Wagoner Counties. Parcel level land use data
was not readily available for these jurisdictions.  Thus, this study only considered the Tulsa County
portion of Fort Worth.
89
Primary Land Use (LU) Dataset Parcel Boundary Data
Jurisdiction (if separate from LU data)
Source Year Source Year
Virginia Beach City of Virginia Beach 2017 - -
Washington District of Columbia 2018 - -
Wichita City of Wichita 2018 - -
Jurisdictions that have information shown in the Parcel Boundary Data
column either (1) provided the parcel boundaries and land use data in separate files
that needed to be joined or (2) provided a GIS file where land use data was dissolved
across parcel boundaries such that neighboring parcels with the same land use were
shown as a single feature.  In the former case, the Primary Land Use Dataset column
shows the source and date of the tabular land use date and the Parcel Boundary Data
column shows the same information for the GIS file depicting the parcel boundaries.
In the latter case, the Primary Land Use Dataset column shows the source and date of
the GIS dataset with dissolved land use information and the Parcel Boundary Data
column shows the same information for the GIS file depicting the parcel boundaries.
Before the analysis was conducted, cities with land use data dissolved across parcels
underwent geoprocessing to break up the blocks of uniform land use and assign them
to each individual parcel.
It is also worth noting that some study cities span several counties and, in
some cases, separate datasets had to be obtained for each corresponding county that
makes up the city.  These cities have multiple rows of data shown in the table.  The
individual rows provide the source and date of the dataset for each county that is
covered by the city.  Prior to the analysis, parcel data for these cities were merged
across the constituent counties to create complete citywide datasets.
90
Note that portions of Atlanta, Fort Worth, Oklahoma City, Portland, and Tulsa
extended into counties that did not have parcel level land use data readily available in
GIS (see the footnotes in the table for further detail).  These areas of the cities were
excluded from the analysis.  Fortunately, the counties missing data make up a
relatively small proportion of each of these cities? land areas, therefore the omission
of this data is not expected to significantly alter the findings.
There were several cities where land use data covered a geographic area that
extended beyond the city limits.  These are generally indicated in the table where the
source of the parcel data is not from the city itself.  For all these cities, GIS was used
to extract the land use data only within the current boundaries of each study city.
This was done to ensure the analysis only considered the parcels whose land use is
controlled by each study city.
Lastly, note that the dates of the data vary by jurisdiction.  For all cities, the
most recent publicly available parcel level land use dataset was obtained with the
dates ranging from 2013 to 2019.  Although there is some variation in the dates of the
data between cities, it was felt that the range was narrow enough to allow for a valid
cross-sectional comparison indicative of conditions in the 2010s.
Land Use Reclassification Schema
The land use information acquired for this study, having come from several
different local sources, did not have a common land use classification system.
Instead, each data provider classified land uses differently to suit their needs.
91
Although planners and researchers have been calling for a common nationwide land
use classification schema since at least the 1940s,245 there has been little movement
amongst cities to adopt such a system.  This presents a major challenge for cross-
sectional studies like this one because the comparison of land use relationships
between cities requires a common definition of land uses.  As Robert M. Sparks aptly
states in a 1958 journal article advocating for a national land use classification
system, ?A [comparative] land use analysis can be no better than the classification
system it is based upon.246  With that in mind, a substantial effort was devoted to
establishing a unified land use classification schema for the study cities.
The effort began with a review of the literature on land use classification
systems with the hopes of finding a schema that could work well with the land use
data available for this study.  The review revealed several studies on land
classification in the 1950s and 1960s, a period in the planning profession
characterized by a push towards more quantitative analysis of cities.  Most of these
early authors advocated for the establishment of a uniform national land use
classification system and provided ideas on what it could look like.
One of the most important developments to come out of this early work was
the idea that land use is multi-dimensional.  A pioneer of this concept, Albert Z.
Guttenberg, classified land using a variety of dimensions including (1) building type,
(2) actual use (which can differ from building type if, for example, a building has
been re-purposed), (3) economic use (which groups different actual uses devoted to
245 Howard, ?Comment on ?Categories of Land Use,?? 25.
246 Sparks, ?Uniform Land Use Classification,? 176.
92
the same business enterprise into one category; for example, a factory and that
factory?s office), (4) site development characteristics (i.e., developed versus
undeveloped), and (5) activity characteristics (e.g., land uses grouped by common
time pattern of activities).247
Guttenberg?s multi-dimensional conceptualization formed the basis for much
of the subsequent work in this topic area.  In 1965, for example, the United States
Urban Renewal Administration developed a similar multi-dimensional land use
classification schema.  The system was recommended for use by federal agencies and
local governments, however, it appears not to have gained much traction. 248
More recently, in the late 1990s, the American Planning Association (APA),
in conjunction with the federal government, revisited the topic as part of the Land
Based Classification Standards (LBCS) Project.  Like Guttenberg?s schema, the
LBCS schema is multi-dimensional and provides for separate land use classifications
based on (1) structure (building) type, (2) activity,249 (3) function,250 and (4) parcel
site characteristics (e.g., developed versus undeveloped).251  One difference from
Guttenberg?s schema is that the LBCS provides an ownership dimension (e.g., private
vs. public ownership) in lieu of the activity characteristic dimension,
With the LBCS, each parcel would, ideally, be classified under each
dimension and then a holistic view of the character of its land use arrived at by
looking across all five dimensions. For example, a parcel with a single-family
247 Guttenberg, ?Multiple Land Use Classification,? 144.
248 Urban Renewal Administration, Standard Land Use Coding Manual, 5.
249 Similar to Guttenberg?s actual use dimension.
250 Similar to Guttenberg?s economic use dimension.
251 American Planning Association, ?LBCS Standards.?
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detached home may be classified as having (1) a residential building for the structure
type dimension, (2) a residential activity for the activity dimension, (3) a residence
function for the function dimension,  (4) being a developed site with buildings for the
site dimension, and (5) in private ownership for the ownership dimension.  These five
classes could then be rolled up into a single multi-dimensional class that captures this
unique combination of all five dimensions.  Continuing with the example, consider
another single family detached home in the community similar in all respects to the
aforementioned except that it is publicly owned low-income housing.  Because of the
difference in the ownership dimension, it would fit into a different multi-dimensional
class than the first example.   Thus, dozens of unique multi-dimensional classes could
be created from the various possible combinations of the five LBCS land use
dimensions.  These multi-dimensional classes could then be used to make a detailed
land use map for the city.
Unfortunately, like the other systems that have come before it, LBCS has also
been slow to catch on.  Undoubtedly, this is partly due to the institutional inertia
behind existing local classification systems.  The LBCS may also be viewed by some
as too complex, detailed, and data intensive.  Whatever the case, many cities
(including most of the study cities) do not currently maintain land use data in a form
that can be used to create a fully multi-dimensional land use dataset.  This motivated
the need to develop a new, simpler land use classification schema for this study; one
that could work with the land use data currently available from the study cities and
that was suited to the research question.
94
The schema developed for this project includes the 11 land use classes shown
in Table 2.  Future references to these land use classes in this report will use the
abbreviations noted in this table.  In LBCS parlance, these classes generally adhere to
the activity dimension of land use.  In other words, the classes capture the actual use
of the land.  That said, other LBCS land use dimensions were included in the
classification.  For instance, the structure dimension was used to provide a more
detailed breakdown of residential land uses by type of dwelling unit.  It was felt this
was an important item to capture in the analysis given American zoning?s long-
running emphasis on segregating residential dwellings by type.  While, ideally, one
might classify residential uses by some combination of residential density (a common
measure used in zoning ordinances) and building type, information on the number of
units per parcel was not readily available for every study city.  Thus, the classification
schema used for this study had to rely on building type alone.
In addition, the LBCS ownership dimension was used to separate out non-
residential publicly owned properties (along with other institutional and cultural uses
that are focused on serving the public).  This was done, in part, because many zoning
ordinances grant such uses immunity from zoning requirements.  Thus, separating out
public/institutional/cultural (PUB) uses allows for analysis of their locations relative
to the other uses whose locations are often more regulated.
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Table 2: Land Use Classification Schema Used in this Study
Land Use Class Uses Included
Single-family detached residential ? Single-family detached homes252 on parcels
(SFDR) > 3,000 square feet in area
Missing middle residential253 ? Single-family detached homes on parcels
(MMR) ? 3,000 square feet in area
? Attached single-family homes (townhouses,
rowhouses, and side-by-side duplexes)
? Small (? 4 units254) multi-family buildings
(over-under duplexes, triplexes,
quadraplexes, and small apartment
buildings)
? Multiple individual homes (? 4 units
overall254) on the same parcel (any
combination of types)
Multi-family residential ? Multi-family buildings > 4 units254
(MFR) (apartments, boarding houses,
fraternities/sororities, retirement homes,
nursing homes, etc.)255
? Multiple individual homes (> 4 units
overall254) on the same parcel (any
combination of types)256
Commercial ? Offices
(COM) ? Retail stores
? Service businesses (barbers, auto repair
shops, construction contractors, etc.)
? Equipment storage yards
? Warehouses
? Commercial parking garages/lots
Industrial ? Manufacturing and processing facilities
(IND) ? Mines/quarries
252 Includes mobile homes on individual lots and single-family detached condominium units.
253 Includes both townhouse style and small (less than five unit) multi-family style condominium
complexes.  Where the data allows, individual townhouse style condominium units were treated as
separate parcels whereas the individual multi-family style condominium units were grouped and
treated collectively as a single MMR coded parcel.
254 The four-unit threshold was applied whenever the data allowed.  In several cities, the data left some
ambiguity as to the number of units on each parcel.  Thus, this threshold should be interpreted as a
general guideline rather than a hard-and-fast rule.
255 Includes multi-family style condominium complexes with more than four units.  The individual
condominium units were treated collectively as a single MFR coded parcel for the analysis.
256 Includes mobile home parks.
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Land Use Class Uses Included
Transportation/communications/utilities ? Railroad right-of-way and stations
(TCU)257 ? Bus terminals
? Airports
? Seaports
? Antennae
? Electrical infrastructure
? Natural gas infrastructure
? Water/wastewater facilities
Public/institutional/cultural ? Public buildings (city halls, government
(PUB) offices, fire stations, police stations, etc.)258
? Schools and universities259
? Houses of worship
? Hospitals
? Museums
? Zoos
? Stadiums
Vacant/undeveloped/open space ? Parks260
(VAC) ? Conservation lands
? Vacant lots
Agriculture ? Cultivated farmland and associated
(AG) structures261
? Ranchland and associated structures261
? Orchards/vineyards and associated
structures261
Mixed use ? Various combinations of residential and non-
(MU) residential uses (see Table 3 for a detailed
breakdown)
Unknown ? Missing land use data
(UNKN) ? Ambiguous land use classes
257 Public and privately-owned road right-of-way (ROW) was removed from the data as much as
practical. Some scattered ROW parcels may remain, particularly for private ROW.  If so, these are
generally coded as vacant land.
258 Public housing is generally included under the appropriate residential categories.  Where possible,
public utilities were included under the TCU category.
259 Includes both public and private schools/universities.
260 Includes separately parceled private pool and clubhouse facilities associated with some large
residential developments.
261 Includes farmhouses, barns, retail stands, and other structures related directly to agricultural
operations.
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As shown at the top of Table 2, a total of three classes are used to differentiate
residential land uses.  The selection of these three classes was informed by the history
of zoning and contemporary debates over land use policy.  Hence, single-family
detached residential (SFDR) was given its own class because, as mentioned in the
previous chapter, protection of these uses has traditionally been a key feature of
American zoning ordinances.  A class representing only SFDR allows for an
assessment of whether this politically sensitive land use type enjoys the same level of
protection in Houston as it does in zoned cities.
In contrast to the SFDR class, which represents only a single building type,
the missing middle residential262 (MMR) land use class encompasses several different
moderate scale residential building types, from duplexes to small multi-family
buildings.  Many contemporary urban planners view MMR as being a desirable
housing form263 but find that it has been severely constrained under traditional
Euclidean zoning ordinances.264  As a result, several planners advocate for the
allowance of more MMR uses in land development regulations.  In recent years, a
few cities have addressed these concerns with one, Minneapolis, even voting to allow
262 The term ?missing middle housing? was coined by urban planner Daniel Parolek in 2010 (Opticos
Design, ?What is Missing Middle Housing??).  It refers to medium scale (middle) housing that has
traditionally been limited (missing) under American zoning ordinances. The term is used here because
it represents a concise way to describe several different medium scale housing types.  The word
?missing? is a bit of a misnomer when considering the large central cities included in this study.  In
most of the study cities, such housing types are not missing at all (due to the extensive amount of pre-
zoning development, potentially more permissive zoning policies, etc.) and, in some, are even the
predominant housing type.
263 For providing more affordable housing choices near downtown, providing more housing in
walkable areas close to job centers, etc.
264 Opticos Design, ?What is Missing Middle Housing??
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MMR citywide in all areas previously reserved solely for SFDR uses.265  As
discussed in Chapter 2, this is already the de facto policy in Houston given the lack of
zoning.  Creating a separate class for MMR enables investigation of the outcomes of
Houston?s approach that can help inform the debate in other cities.
The final residential land use class shown in Table 2, multi-family residential
(MFR), includes a variety of different multi-family housing types.  MFR is provided
its own class because it has long figured prominently in the debate over zoning and its
effects.  Traditional Euclidean zoning practice has tended to separate MFR uses from
SFDR uses.266  In recent decades, however, planners have tended to advocate for
more mixing of residential housing types and land uses.  Inclusion of MFR as its own
class will allow the analysis to explore whether Houston?s lack of zoning has resulted
in greater mixing of that land use with other housing forms.
With respect to non-residential uses, Table 2 shows that, unlike the land use
schemas used in many cities, the schema used for this study makes no distinction
between ?light? and ?heavy? industrial uses.  This is because several cities considered
light industrial uses (e.g., construction/building supply companies, equipment storage
yards, warehouses, etc.) as commercial uses, making it impossible to extract and
separate them out into their own light industrial category.  Thus, for purposes of this
study, light industrial uses are generally included in the commercial (COM) class
265 Mervosh, ?Minneapolis Votes to End Single-Family Zoning.?
266 The Village of Euclid v. Ambler Realty Co. majority opinion even included a statement by the
justices (in an aside from the direct circumstances of the case at hand) that it would be desirable to
separate single-family homes from multi-family apartment buildings.
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while the industrial (IND) class is reserved for manufacturing, processing, and
resource extraction activities.
Table 2 also shows an agricultural (AG) land use class.  Given this study?s
focus on large urban centers, this may seem unnecessary.  However, while some of
the cities included in this study have no farmland within their borders, the majority
do.  In fact, some study cities with expansive borders include significant amounts of
AG land.  That said, in most cities AG uses occupy only a handful of parcels.
Nonetheless, a land use class devoted to AG must be included to provide a
comprehensive view of land use.
Lastly, the bottom of Table 2 reveals two classes that require further
explanation: the unknown (UNKN) and mixed use (MU) classes.  The UNKN class is
used when a parcel?s land use cannot be determined.  This occurs when the city either
did not provide a land use classification for a parcel267 or provided a land use
classification that, upon inspection, was ambiguous and covered a range of different
land uses.  An alternative to creating a (UNKN) class would be to simply delete these
parcels from the dataset.  However, doing this has the potential to bias the study
findings by making it appear that these parcels do not exist.268  Thus, it was felt that
retaining the UNKN parcels and being explicit about the uncertainty in the results
would be more appropriate.
267 This is often the case for parcels that were being developed/redeveloped when the parcel data was
created.
268 While the effect would likely be minimal, given the small proportion of unknown parcels in each
city, it could still make a difference.
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The final class in Table 2 that warrants explanation is MU.  The MU class is
used for cases where residential and non-residential uses share the same parcel.269  A
parcel could be assigned to the MU class in two different ways.  The most
straightforward way is when the city?s local land use schema has an MU category for
residential and non-residential use combinations.  In these instances, any parcel with
that coding is assigned to the MU category.270
A second way a parcel could be classified as MU is if there are duplicate
parcels stacked on top of each other in the parcel dataset, some residential and some
non-residential.  This happens because some of the study cities create duplicate
parcels when multiple uses share the same plot.271  Table 3 shows how a single land
use was assigned to each parcel, a requirement of the analysis, when there is overlap.
As one can see, the combination of virtually any other use with a residential use
results in an MU designation.  The exceptions are AG uses (which retain an AG
classification), vacant/undeveloped/open space (VAC) uses (which are assigned the
land use of the residential use), and UNKN uses (which, like VAC, assume the
appropriate residential land use classification).
269 Parcels with a mixing of different non-residential uses on the same parcel are not classified as MU.
Nor are parcels with a mixing of different residential uses (building types).  Instead, these parcels are
assigned a land use based on the schema shown in Table 3.
270 While most cities? classification schemas included mixed use classes, some did not.  Instead, these
cities tended to classify mixed use properties according to their predominate land use type.  Thus, in
some cities, the amount of mixed use property may be underestimated.
271 This is especially common for condominium properties.
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Table 3: Schema for Assigning A Land Use to Parcels Associated with Multiple Land Uses
SFDR MMR MFR COM MU PUB IND TCU AG VAC UNKN
SFDR MMR/MFR MMR/MFR MFR MU MU MU MU MU AG SFDR SFDR
MMR MMR/MFR MFR MU MU MU MU MU AG MMR MMR
MFR MFR MU MU MU MU MU AG MFR MFR
COM COM MU PUB IND TCU COM COM COM
MU MU MU MU MU MU MU MU
PUB PUB IND TCU PUB PUB PUB
IND IND IND IND IND IND
TCU TCU TCU TCU TCU
AG AG AG AG
VAC VAC VAC
UNKN UNKN
SFDR = Single-family detached residential; MMR = Missing middle residential; MFR = Multi-family residential; COM = Commercial; MU = Mixed
use; PUB = Public/institutional/cultural; IND = Industrial; TCU = Transportation/communications/utilities; VAC = Vacant/undeveloped/open
space; AG = Agriculture; UNKN = Unknown
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Table 3 also shows the rules by which a land use is assigned when there are
stacked parcels that are either all residential or all non-residential.  In general, if there
are multiple types of residential uses on the same parcel, the parcel is classified into
either the MMR or MFR category, depending on the estimated number of units.  If
the number of units is less than or equal to four, then the parcel is coded as MMR.  If
greater than four, then the parcel is assigned to the MFR category.  Stacked non-
residential parcels are generally assigned the use most likely to produce negative
externalities.
Using the schemas shown in Table 2 and Table 3, the various local land use
codes were reclassified to create uniformly coded land use designations for all the
study cities.272  In addition, several geoprocessing operations were performed to
ensure the topological correctness of the data; specifically, to eliminate small areas of
overlaps or gaps between parcels due to poor digitization (drawing) of the parcel
boundaries in the GIS.273  Correcting such issues is important for ensuring that the
land use metrics calculated for this study, many of which rely heavily on the spatial
relationships between individual parcels, are as accurate as possible. Maps showing
the reclassified and topologically corrected land use data for each city can be found in
Appendix A.
To the extent practicable, checks were made to ensure that the locally defined
land use designations were associated with the most appropriate classes shown in
272 A lookup table showing how each local land use class was reclassified can be obtained by
contacting the author.
273 Details on the techniques that were used for the topological corrections are available from the
author upon request.
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Table 2.  This involved spot checks of parcels in Google Earth Street View to check
accuracy.  Despite these checks, erroneous data and slight differences in land use
definitions amongst the cities undoubtedly result in some parcels being incorrectly
classified.  That said, it is felt that the reclassified datasets are of high enough
accuracy to enable meaningful comparisons to be drawn between the study cities.
Land Use Metrics
Land use metrics are the variables used to measure the spatial relationships
amongst land uses in each study city.  The metrics are, essentially, the way in which
land use relationships are quantified and therefore represent a very important
component of this study.  The metrics were selected based on their ability to address
the research question; specifically, their ability to help ascertain if the spatial
arrangement of land uses in Houston is unique.  Given data availability, metrics that
address other dimensions of land use patterns (density, building setbacks, building
heights, etc.) are not included here.  That said, one additional set of metrics that was
relatively easy to calculate with available data is included; the average parcel size by
land use class. However, this set of metrics is for general reference only and was not
used in the comparative statistical analysis described later.
The process of identifying metrics began with a literature review of studies
quantifying landscape patterns.  It was hoped that the review would reveal metrics
that could be used directly in this study.  The literature review revealed an extensive
literature on the topic.  Unfortunately, however, few studies have developed metrics
focused on measuring urban development patterns within cities.   Instead, much of the
research has been focused either on understanding ecosystem structure within natural
104
areas or on the interplay between developed and undeveloped land at the urban
periphery (part of the large literature attempting to quantify urban ?sprawl?).
While most of the metrics encountered could not be used ?off-the-shelf,? the
general spatial concepts behind them proved insightful and helped inform the
development of metrics more in line with the needs of this study.  For example, a
study by Edward A. Cook assessing urban ecological networks included a metric
called a matrix utility index.  The index considers the proportion of each ecological
unit?s perimeter that borders on other types of ecological units and the compatibility
of these neighboring ecological units. 274  The index helped inspire a metric for this
study that considers the proportions of each land use class? perimeter that are adjacent
to different land uses.275
Another example, cited in a summary of ecological metrics undertaken by
Eric J. Gustafson, is a measure that considers the frequency of different ecological
units being adjacent.276  This informed the development of several metrics in this
study that consider the proportion of parcels near or adjacent to different land uses.
Another measure mentioned by Gustafson considered the average distance from one
type of ecological unit to the next nearest unit of a different type.277  This inspired a
proximity measure for this study that identifies the average distance between different
land uses.  Gustafson also noted a measure that involved buffering each ecological
274 Cook, ?Landscape structure indices,? 272.
275 Unlike with Cook?s metric, the compatibility of land uses was not included in the metric developed
for this study due to the somewhat subjective nature of compatibility as applied to land uses.
276 Gustafson, ?Quantifying Landscape Spatial Pattern,? 147.
277 Gustafson, 147.
105
unit polygon and finding the proportion of ecological unit types within that buffer.278
This motivated several metrics for this study that buffer each parcel and summarize
the land uses within those buffers.
In all, 13 sets of metrics279 were developed to measure land use relationships
in this study.  Table 4 lists these metrics, provides an example of each, and shows
how each is normalized.  Normalization is needed because each city has different
proportions of each land use.  This could bias the findings of many metrics.  For
example, when compared to a less industrial city, a highly industrial city would have
a greater chance of IND land uses bordering other land uses, simply because it has
more land in IND use.  Normalization helps correct for this bias and facilitates a
clearer understanding of the actual land use relationships.  Mathematically, the items
listed in the ?Normalized By? column in Table 4 are the variables each metric is
divided by to obtain a normalized value.  Both the normalized and raw (non-
normalized) values are reported for each metric in the results, as the raw values are
more tangible and helpful for understanding the actual on-the-ground land use
relationships in each city.
278 Gustafson, 148.
279 ?Sets of metrics? is used because most of the items described below actually represent several
individual metrics measuring the same type of spatial relationship but amongst different land use
classes.
106
Table 4: Land Use Metrics
Metric Example Normalized By
Land Use Composition Metrics
? Proportion of total parcel 60% of total citywide
area280 devoted to each land parcel area is devoted -
use class to SFDR
? Average parcel size by land The average size of
use class SFDR parcels is one -
acre
Land Use Relationship Metrics
Adjacency Metrics281
For each land use class, the?
? Proportion of shared parcel 10% of the shared Proportion of the city-
perimeter bordering on each perimeter of SFDR wide shared parcel
land use282 parcels borders on perimeter length made
COM uses up by the adjacent land
use class
? Proportion of parcels 20% of all SFDR Proportion of the city-
bordering each land use282 parcels border on COM wide shared parcel
uses perimeter length made
up by the adjacent land
use class
? Proportion of parcels that 75% of SFDR parcels Proportion of the city-
border only the same land border only on other wide shared parcel
use SFDR uses perimeter length made
up by the subject land
use class
280 Total parcel area excludes right-of-way.
281 Adjacency is defined here as two parcels sharing a common border.  The portion of parcel perimeter
bordering on street right-of-way, major waterbodies, or neighboring jurisdictions was not included in
the perimeter calculations.  Thus, for purposes of this study, parcels across the street from each other
were not considered adjacent and such relationships were not included in the adjacency metrics.
282 Values are not reported for the UNKN land use class.
107
Metric Example Normalized By
Neighborhood Metrics
For each land use class, the?
? Proportional area of each 10% of the land area For like combinations of
land use within 500 feet283 within 500 feet of land use (e.g., MU to
SFDR parcels is MU), the metric is
devoted to COM uses divided by the proportion
of city-wide parcel area
devoted to that land use
class plus the average
parcel size for that land
use class.  For differing
combinations of land
use (e.g., MU to AG),
the average parcel size
of the subject land use
class is first added to
the metric then divided
by the proportion city-
wide parcel area
devoted to the
neighboring land use
class284
? Proportion of parcels that 15% of SFDR parcels Proportion of city-wide
have each land use within have a COM parcel parcel area devoted to
500 feet285 within 500 feet the nearby land use
class
? Proportion of parcels that 15% of SFDR parcels For the zero nearby land
have zero, one, two, three, have two other land uses metric, the
four, five, six, seven, eight, or uses within 500 ft proportion of city-wide
nine other land uses within parcel area devoted to
500 feet286 the subject land use
class. For the one or
more nearby land uses
metrics, the proportion
of city-wide parcel area
devoted to all land use
classes other than the
subject land use class.
283 Excludes right-of-way area and area outside the city limits.  Inclusive of the area of the subject
parcels.
284 Post-processing was done to ensure the normalized metric value remained zero for any land uses
that did not appear within 500 feet of any other land use.
285 Values are not reported for the UNKN land use class.
286 Number of other land uses did not consider the UNKN land use class nor are the results reported for
the UNKN land use class.
108
Metric Example Normalized By
Proximity Metrics
For each land use class, the?
? Average distance to the The average distance The inverse of the
nearest parcel of each land from SFDR parcels to proportion of city-wide
use287 the nearest COM parcel area devoted to
parcel is 1,000 feet both land use classes
involved in the distance
calculation
Transportation-Land Use
Relationship Metrics
? Proportional area of each 10% of the parcel area The proportion of city-
land use within 200 feet of within 200 feet of non- wide parcel area
non-access controlled access controlled devoted to the subject
arterial roadway centerlines arterial roadway land use class
or rail lines centerlines is SFDR
? Proportional area of each 85% of the parcel area The proportion of city-
land use within a half mile of within a half mile of wide parcel area
a limited access highway exits is COM devoted to the subject
exit288 land use class
? Average distance from IND The average distance The inverse of the
parcels to the nearest rail of IND parcels to the citywide rail line or
line or limited access nearest rail line is limited access highway
highway 1,000 feet density (length of
infrastructure within the
city / area of the city)
Land Use Clustering Metrics
? Average nearest neighbor The average nearest
index for each of the land neighbor index for -
uses289 SFDR uses is 0.5
As Table 4 shows, like metrics are grouped into four categories: (1) land use
composition metrics, (2) land use relationship metrics, (3) transportation-land use
287 Values are not reported for the UNKN land use class.
288 Available data required that highway exists represent the locations of egress from the limited access
highway (not the center of the interchange, as would be ideal).  Thus, a typical highway interchange
included two exit point features from which half mile buffers were drawn (one for each direction of the
highway).
289 Values are not reported for the UNKN land use class.
109
relationship metrics, and (4) land use clustering metrics.    Together, these categories
represent the key elements of urban structure that formed the basis of comparison
amongst the study cities.  Each of the categories and their associated metrics are
discussed in detail within the sections that follow.
Land Use Composition Metrics
Land use composition describe the overall land use makeup of each study city.
Two sets of metrics were computed for this category: (1) the proportion of total parcel
area (excluding right-of-way) devoted to each land use class and (2) the average
parcel size by land use class.  The proportional area of each land use class provides an
initial basis of comparison amongst the study cities, revealing, in some ways, the
economic focus of each city (e.g., cities with more of a manufacturing-based
economy would be expected to have a greater proportion of industrial uses).  This set
of metrics is also used to normalize some of the other metrics.
The average parcel size metrics provide information on whether lot sizes for
various land uses tend to be different in Houston than in other cities. This set of
metrics can help ascertain whether Houston?s lack of zoning results in notable
differences in lot size.  Although Houston?s subdivision ordinance has long specified
minimum lot sizes,290 Siegan observed that single-family residential lots in Houston
tended to be smaller than in zoned cities (possibly due to lack of rear and side yard
290 Recall also per Chapter 2 that lot size minimums in Houston are much more permissive (smaller)
than in many zoned communities.
110
setback requirements).291 This set of metrics enables quantitative evaluation of his
observation.  These metrics are also used for normalization of other metrics.
Land Use Relationship Metrics
Land use relationships refer to the spatial relationships amongst each of the
various land use classes.  The metrics in this group measure the land uses that are
next to or near each other, a focus of zoning.  The land use relationship metrics are
broken out into three sub-categories based on the spatial scale they consider.  These
include adjacency metrics, neighborhood metrics, and proximity metrics.  Each of
these sub-categories, and the metrics within them, are described in the sections below.
Adjacency Metrics
Adjacency metrics focus on the land uses bordering directly upon each other
(i.e., those sharing a common parcel boundary).  Adjacent land uses present the
greatest opportunity for spillover of externalities and are, therefore, particularly
relevant to whether the patterns observed in Houston are like other cities with zoning.
Three sets of adjacency metrics were included in this study.
The first set of metrics, the proportion of shared parcel perimeter of each land
use class bordering on each other land use (i.e., the proportion of the parcel
perimeters that share a boundary with neighboring parcels), both enumerates the land
uses that share a common border and describes the extent of that shared boundary.
Per this study?s hypothesis, one would expect that each land use class in Houston
291 Siegan, ?Land Use Without Zoning?, 50 and 59.
111
would have a greater proportion of other types of land uses bordering it (when
compared to zoned cities), indicating greater land use mixing.  Each metric in this set
was normalized by the proportion of the total city-wide shared parcel perimeter length
(i.e., the total length of the boundaries shared between parcels) made up by the land
use class adjacent to the one being evaluated.  The normalized values that result are
unitless measures that control for differences in land use composition across cities.
A second set of metrics, the proportion of parcels in each land use class
bordering each other land use, also looks at adjacent land uses.  This set of metrics,
however, considers the share of parcels that border different land uses instead of the
share of each land use?s total perimeter.  Thus, this set of metrics represents a more
property owner-centric perspective than the perimeter-based metrics.  When
compared with zoned cities, this study hypothesizes that Houston will show a greater
proportion of parcels bordering other land uses.  As with the perimeter-based metrics,
the normalization of the parcel-based metric used the proportion of the total city-wide
shared parcel perimeter length made up by the adjacent land use class.
The final set of adjacency metrics, the proportion of parcels in each land use
class that border only the same land use, also considers the proportion of parcels
exhibiting a relationship to other land uses.  Thus, it too brings a property owner?s
perspective to the analysis.  However, unlike the previously described metrics, this
metric considers the proportion of parcels in a given land use class that border only
parcels of the same land use.  Thus, it is a measure of the degree to which parcels in
each land use class are isolated from other land uses.  Traditional zoning tends to
cluster like land uses together thereby increasing the proportion of parcels that would
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not border on other uses.  Thus, per this study?s hypothesis, one would expect
Houston to have a smaller value for these metrics than zoned cities.  The
normalization factor for this metric was the proportion of the city-wide shared parcel
perimeter length made up by the subject land use class (the one being evaluated)
since, unlike with the other measures, this metric does not focus on an adjacent land
use.
Neighborhood Metrics
Three sets of neighborhood metrics were included in this study.  Compared to
the adjacency metrics, the neighborhood metrics look slightly further afield and focus
on the land uses in the general vicinity of each land use class.  An important
consideration with the neighborhood metrics was how to define the neighborhood
(i.e., what distance to consider).  Ideally, one would look far enough out to consider
all the parcels that could conceivably produce externalities towards the parcel being
evaluated.  However, this is a challenging to put into practice because each land use
class (and even each specific use type within it) will have its own set of externalities
with their own extents.  Indeed, each specific property, even those of the same
specific use type, may have different externality ranges depending on how the owner
manages them.
Given the uncertainties involved, the literature was consulted to determine the
average range of externalities.  Unfortunately, such a measure proved elusive.  The
most thorough treatment of the topic found was in a summary of urban economics
written by Edwin S. Mills.  Mills noted the paucity of studies looking at the spatial
extent of property impacts of negative externalities from one land use on another.
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What Mills did find generally indicated the effects are surprisingly weak and
localized.292  Given this, 500 feet (as measured from the parcel boundary) was chosen
as the geographic range over which the neighborhood metrics would be evaluated for
each land use class.   This corresponds to approximately one or two city blocks in
traditional gridded street networks.
The first set of neighborhood metrics evaluates, for each land use class, the
proportional area of each land use that lies within 500 feet of each other land use.  Per
this study?s hypothesis, the expectation is that Houston will show a greater proportion
of different land uses within this distance, indicative of greater land use mixing.  The
metrics were normalized as follows.  For like land use combinations (e.g., MU to
MU), the metrics were divided by the sum of (1) the proportion of city-wide parcel
area devoted to the given land use class and (2) the average parcel size of that land
use class.293  For differing land use combinations (e.g., MU to AG), the metrics were
added to the average parcel size of the subject land use class then divided by the
proportion of city-wide parcel area devoted to the adjacent land use class.  Post-
processing was done to ensure the normalized metric value remained zero for any
land uses that did not appear within 500 feet of any other land use.  The differing
treatment of the average parcel size between these types of land use combinations
ensured that, all else being equal, each like land use combination?s metric was
292 Mills, ?Economic Analysis of Urban Land-Use Controls,? 525.
293 The average parcel size was included to correct for a potential bias introduced by the way the
buffers are created in GIS.  Standard GIS tools available for this research include the area of the
subject parcels (the parcels being buffered) within the buffers being drawn around them.  Since
average parcel sizes differ amongst the cities for each land use class, the inclusion of the area of the
subject parcels could bias the results of the analysis due to parcel size alone (instead of the parcel
relationships intended).  Including average parcel size in the normalization corrects for this issue.
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normalized downward if the subject land use class had unusually large parcel sizes in
a given city (relative to other cities) and that the proportional area metrics of the other
land use classes were, correspondingly, normalized upwards (necessary because,
being proportions, the values of all the metrics are interdependent).
As with the proportional perimeter measure in the adjacency metrics, the
proportional area metrics do not consider land use relationships from the property
owner?s perspective.  To bring that perspective into consideration, another set of
metrics was developed to indicate the proportion of parcels that have each land use
within 500 feet.  When compared to zoned cities, it is expected that Houston will
have a higher proportion of parcels having different land uses within this envelope.
This metric was normalized by the proportion of city-wide parcel area devoted to
each adjacent land use class.
The final set of neighborhood metrics captures the proportion of parcels that
have zero, one, two, three, four, five, six, seven, eight, or nine other land use classes
within 500 feet.  Unlike the other neighborhood measures, this one is not focused on
the types of land uses nearby but instead on how much mixing of uses has occurred
near different land uses.  When compared with zoned cities, it is hypothesized that
Houston will exhibit larger proportions of parcels with more mixing and lower
proportions of parcels with less mixing.  These metrics were normalized differently
depending on how many different land uses are nearby.  For the zero adjacent land
uses metrics, normalization was by the proportion of city-wide parcel area devoted to
the land use class being evaluated. For the one or more adjacent land uses metrics,
normalization was by the proportion of city-wide parcel area devoted to all land use
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classes other than the subject land use class (since any land use class other than the
one being evaluated may be counted).
Proximity Metrics
Unlike the adjacency and neighborhood metrics, the proximity metrics do not
set a distance over which to assess spatial relationships a priori.  Instead, the
proximity metrics are driven by the actual distribution of the land uses.  The
proximity metrics measure the average distance from the land use class being
evaluated to the nearest parcel of each other land use class.  Per this study?s
hypothesis, these distances are expected to be shorter in Houston, reflecting the
likelihood of more land use intermixing.  These metrics were normalized by the
inverse of (i.e., multiplied by) the proportion of city-wide parcel area devoted to both
land use classes involved in the distance calculation.  Both land use classes need to be
considered for normalization because the proportion of either use within the city
could bias the results (e.g., two uses that are highly prevalent are much more likely to
have shorter average distances between them than two uses that are not or one use
that is highly prevalent and another that is not).
Transportation-Land Use Relationship Metrics
Transportation facilities are one of the primary drivers of urban development
patterns.  The accessibility they provide can induce growth and shape the land uses
that occur in their vicinity.  Transportation facilities can also bring about negative
externalities for certain land uses.  Recognizing this, planners often zone land with
transportation facilities in mind.  Thus, zoning has the potential to affect the spatial
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distribution of land uses, not only in relation to themselves (as captured by the land
use relationship metrics above), but also in relation to transportation facilities.  As
with other aspects of zoning and land use patterns, whether this has actually been the
case has not been definitively measured.
In his observations of Houston, Siegan provides mixed views.  In support of
zoning being binding, he mentions that Houston tends to have more commercial
development along major thoroughfares than do zoned cities.294  This could be
because cities designate single-family zones along major thoroughfares whereas the
highest and best use (as determined by the market) may be commercial (due to the
high visibility of those parcels to passing motorists).  On the other hand, Siegan finds
that zoning is largely redundant with respect to the location of industrial uses because
planners typically place most of them near railroads, waterways, and major
highways.295  He argues this is where they would locate themselves anyway due to
the accessibility those transportation facilities provide and cites Houston?s land use
patterns as evidence of this.
The transportation-land use metrics developed for this study aim to evaluate
Siegan?s observations and, more generally, consider zoning?s influence on the
transportation land use nexus.  The first set of metrics measure the proportion of
parcels in each land use class within 200 feet of non-access controlled arterial
roadway centerlines296 or rail lines (separate measures will be provided for each type
294 Siegan, ?Land Use Without Zoning?, 46.
295 Siegan, 62.
296 Access controlled highways are not included in this set of metrics because the access controls limit
the ability of the highway to influence land use patterns along the entirety of its length.
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of facility).  The hypothesis of this study is that zoned cities will exhibit a different
pattern than Houston.  Per Siegan, it is expected that Houston will exhibit a greater
proportion of COM uses along its arterial roadways when compared with zoned
cities.  Along rail lines, Houston is expected to have a higher proportion of residential
uses than in zoned cities since planners might take into consideration the externalities
of train noise and the hazard of derailments when establishing residential zones.  Both
the road and rail metrics were normalized by the proportion of city-wide parcel area
devoted to each land use class being evaluated.
A second set of metrics considers the land uses in the vicinity (a half mile) of
limited access highway interchanges.  Limited access highways strongly influence
land use patterns because of the accessibility they provide and the volume of traffic
they carry (an important consideration in the location decisions of certain commercial
services where high visibility is important to a successful business [e.g., gas
stations]).  Since access to such highways is, by definition, limited, market forces
tend to make the areas around interchanges locations of intensive commercial
activity.  The hypothesis of this study is that there will be a greater proportional area
of COM uses around interchanges in Houston.   In zoned cities, there may be a
tendency to try and reign in commercial development around interchanges as some
may view this as unsightly.  The set of interchange metrics were normalized by the
proportion of city-wide parcel area devoted to each land use class being evaluated.
A third set of metrics addresses directly Siegan?s observation that the location
of IND uses (often, the use of greatest concern with respect to externalities) can be
predicted by their proximity to transportation facilities.  The metrics measure the
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average distance from IND parcels to the nearest rail line or limited access highway
(once again, separate measures will be provided for each type of facility).297  The
hypothesis of this study (that land use relationships in Houston differ) contradicts
Siegan?s observations in this case.  Thus, it is hypothesized that the average distance
from IND parcels to rail lines or highways will be greater in Houston than in zoned
cities, due to the greater freedom IND uses have to locate wherever meets their
needs.298  This metric was normalized by the inverse of (i.e., multiplied by) the
citywide rail line or limited access highway density (calculated by dividing the length
of each type of infrastructure within the city limits by the city area) since cities with a
greater density of rail lines or highways may inherently exhibit shorter distances to
IND uses.
Land Use Clustering Metrics
The final set of metrics measures the degree of clustering for different land
use classes.  This was accomplished by calculating the average nearest neighbor
index for each of the land use classes.  The average nearest neighbor index is
computed by first determining the average distance between each parcel in a given
land use class and its nearest neighboring parcel in the same land use class.  This
value is then divided by the average distance between parcels in a hypothetical
scenario where all the parcels in the given land use class are spread out randomly
297 The average distance to the nearest navigable waterway is not included in the metric due to the
difficulty in creating a national dataset representing all navigable waterways.
298 Trucks offers this flexibility to many industrial uses.
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across the study domain.299  The unitless value that results provides an indication of
the degree of clustering of each land use class: the smaller the value, the greater the
amount of clustering.  Since traditional zoning explicitly seeks to cluster like land
uses, it is hypothesized that the nearest neighbor index will be higher in Houston than
in zoned cities for all land use classes. Note that the nearest neighbor indices need not
be normalized like the other metrics.
Comparative Techniques
After all the metrics had been computed, the data were summarized to
determine if Houston is an outlier amongst the study cities.  Two comparative
techniques were used for this: (1) bar charts of each metric and (2) a principal
component analysis (PCA) across the normalized metrics.  Descriptions of each
technique are provided in the sections that follow.
Bar Charts
Bar charts are provided to enable comparisons amongst the cities for each
individual metric.  A separate chart is provided for each metric.  Where applicable,
separate charts are provided for the raw and normalized values of each metric.
On the charts, each city is represented by a bar whose height corresponds with
that city?s value for the given metric.   The bars (cities) are ordered from the highest
to lowest values for each metric.  This enables a quick visual comparison of the
299 In the case of this analysis, the study domain was the area within the city limits of each study city.
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relative ranking of each city and, through comparing the heights of the bars, a rapid
identification of outlier values.
Furthermore, to enable identification of any regional patterns amongst the
metrics, each of the cities was colored based on the geographic region of the country
it falls within.  The color schema corresponds to the classification of cities by region
shown in Figure 7.  The city of Houston was provided its own individual color so that
its relative ranking could be readily identified amongst all the others.
Principle Component Analysis
PCA is a statistical technique for consolidating several correlated variables
into a few uncorrelated variables (the principal components) that succinctly capture
the essential elements of the phenomena being measured.  Particularly relevant to this
study, PCA can also be used to identify multivariate outliers and clusters of related
observations.  Whereas the bar charts are helpful for determining whether Houston is
an outlier for individual metrics, PCA can determine if Houston is an outlier across
all the metrics simultaneously. Thus, PCA provides the holistic cross-metric
perspective needed to answer the research question and determine if land use
relationships in Houston are, on the whole, unique.
PCA has been used before on studies of urban development patterns.  For
example, a study by Jackie Cutsinger and others used PCA to evaluate several
interrelated metrics measuring urban sprawl across 50 American metropolitan areas.
The results of their study helped to better characterize the various dimensions of
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sprawl.300  Cutsinger et al. also used the principle components identified by the PCA
as a starting point for further analyses looking into whether there are regional patterns
to sprawl and whether the relative amount of sprawl can be predicted.301  Thus, the
Cutsinger et al. study demonstrates how the results of this study?s PCA could be used
in later follow-on research.
Not all the metrics described in the previous section were included in this
study?s PCA.  For instance, the PCA did not include the land use composition
metrics.  The land use composition metrics (the proportion of land in each land use
class and the average parcel size) were not included because they do not directly
address the research question which, again, is narrowly focused on zoning?s influence
on the spatial distribution of land uses (not the amount of land use in each city or
parcel size).  Amongst the remaining metrics, only the normalized version of each
were included in the PCA (the land use clustering metrics, which are not normalized,
are an exception and were included in the PCA in their raw non-normalized form).
Use of the normalized metrics ensured that biases in the prevalence of different land
use classes amongst the cities were, to the maximum extent possible, controlled for in
the analysis.  The PCA also excluded all metrics relating to the UNKN land use class
due to the uncertainty inherent to it.  This left a total of 599 individual metrics for use
in the PCA.
Complicating matters, standard outlier detection techniques have limitations
when analyzing so-called high dimensional data where, as is the case in this study, the
300 Cutsinger et al., ?Advancing the Understanding of Sprawl,? 247.
301 Cutsinger et al., 252.
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number of observations (50 cities) is smaller than the number of data fields (599
metrics).  Standard PCA can also be sensitive to outliers in the dataset and can give
misleading results if not accounted for.  Addressing these shortcomings with the
standard PCA approach to multivariate outlier detection has been the focus of several
articles in the statistical literature in recent years.  One of the more advanced
techniques, ROBPCA (short for robust PCA), was first introduced by Hubert,
Rousseeuw, and Vanden Branden in 2005.302  In a 2019 article, Hubert and
Rousseeuw went on to generalize this technique by also making it applicable to
datasets with missing data values.303  This newer technique, called MacroPCA, is the
PCA technique that was used for this study since there are, indeed, missing values
amongst the land use metrics.304  MacroPCA is also capable of flagging cellwise
outliers (i.e., for this study, anomalous data values by city for individual metrics) in
addition to rowwise outliers (i.e., outliers amongst the cities).  The MacroPCA
algorithm was operationalized for this study using version 2.2.5 of the cellWise
package in R statistical software.  The details of the PCA (including the statistical
tests applied to determine how many components were retained) are provided in the
following chapter.
302 Hubert, Rousseeuw, and Vanden Branden, ?ROBPCA: A New Approach to Robust Principal
Component Analysis,? 65.
303 Hubert, Rousseeuw, and Van den Bossche, ?MacroPCA: An All-in-One PCA Method Allowing for
Missing Values as Well as Cellwise and Rowwise Outliers,? 460.
304 Missing values occur because not all cities contain all land uses.  Specifically, New York,
Philadelphia, San Francisco, Detroit, Baltimore, Boston, Seattle, Washington, Milwaukee, Las Vegas,
Long Beach, Omaha, Oakland, and Minneapolis contained no AG uses.  Furthermore, Louisville, Las
Vegas, and Sacramento contained no MU uses (due to the original classification schemas not including
this category).  Lastly, Detroit and Nashville contained no UNKN uses although that is moot for the
PCA because, as noted previously, UNKN related metrics were not included in the analysis.
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The determination of whether Houston is an outlier is made through a visual
inspection of a PCA outlier map.  A PCA outlier map is a graphic that denotes how
far various observations (in this case, cities) are from the PCA subspace and from
other observations.  The right-hand image in Figure 9 provides an example of an
outlier map for the (hypothetical) three-dimensional (i.e., three variable) data shown
in the left-hand image.  The left-hand image also illustrates how the original three-
dimensional data have been reduced through PCA to two dimensions (principle
components) with the rectangle representing the new two-dimensional PCA subspace.
No matter how many variables one analyzes or how many principle components one
retains, the outlier map is always two-dimensional, thereby providing a powerful
technique for multivariate outlier detection.  As one can see, most of the mapped
values are clustered in the center of the subspace but some, the (numbered) outlier
observations, are farther afield.  The outlier map in the right-hand image shows the
regular observations in the lower left quadrant of the graphic and the (numbered)
outliers in the other quadrants.
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Figure 9: Example Outlier Map for Hypothetical Three-Dimensional Data Reduced to Two
Principal Components305
The outliers can be further classified into different types depending on which
quadrant they fall in (see Figure 10).  Orthogonal outliers (e.g., point three in Figure
9) are located far from the PCA subspace but have scores close to the regular
observations.  Good leverage points306 are outliers that are close to the PCA subspace
but whose scores are very different from the regular observations.  Bad leverage
points307 are outliers that are both far removed from the PCA subspace and whose
scores are very different from the regular observations.  The vertical and horizontal
lines bounding the quadrants and defining what observations are considered outliers
are defined such that each have an exceedance probability of 2.5%, assuming a
standard normal distribution.  A visual assessment of the outlier map is used to
answer this study?s research question.  If Houston is an outlier on the plot, it can be
305 Rousseeuw and Hubert, ?Anomaly detection by robust statistics,? 8.
306 The word ?good? is used because these observations can help improve the definition of the PCA
subspace.
307 The word ?bad? is used because these are the outlier observations that can bias a standard PCA
analysis if robust PCA techniques like MacroPCA are not used.
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concluded that its land use relationships are unique compared with the other study
cities.
Figure 10: Classification of Observations on an Outlier Map308
308 Goueguel, ?Multivariate Outlier Detection in High-Dimensional Spectral Data.?
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Chapter 5: Results and Analysis
This chapter discusses the results of the statistical analyses described in the
last chapter.  The chapter begins by showing values of the individual land use metrics
for each study city.  Following this, the PCA outputs are presented and analyzed with
respect to the research question.
Land Use Metrics by City
This section presents the land use metrics computed for each city using the bar
charts described in the last chapter.  The discussion begins with the land use
composition metrics followed by discussions of the land use relationship metrics, the
transportation-land use relationship metrics, and the land use clustering metrics.
Land Use Composition Metrics
The first set of metrics that were analyzed were the land use composition
metrics.  This includes (1) the proportion of total parcel area devoted to each land use
class and (2) the average parcel size by land use class.  Each of these sets of metrics is
discussed in the sections that follow.  Since these metrics do not explicitly address the
topic of land use relationships covered by the research question, they are not analyzed
against the alternative hypothesis.  Nonetheless, the results are interesting and notable
patterns are called out in the text.
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Proportion of Total Parcel Area Devoted to Each Land Use Class
Bar charts showing the proportion of total parcel area devoted to each land use
within each study city can be found in Figure 11 through Figure 21.   Comparing
Houston to other cities, the following patterns are notable:
? For most (but not all) land uses, Houston is not an outlier.  In fact, it
often appears near the middle of the distributions.
? Houston does lead all the study cities in proportion of parcel area
devoted to COM uses (19.2%; see Figure 12).
? Houston has a lower proportion of parcel area devoted to SFDR uses
than most study cities (see Figure 18).  In fact, Houston?s proportion
(23.6%) is lower than any of its peer cities in the South Central region.
? Houston has the greatest proportion of parcel area devoted to TCU
uses (6.7%) amongst its peer cities in the South Central region (see
Figure 19), likely due to the large area devoted to its port facilities.
With respect to regional differences, the following patterns stand out:
? Cities in the Midwest tend to have a greater proportion of parcel area
devoted to IND uses than cities in other parts of the country (see
Figure 13).  This is not unexpected given the manufacturing legacy of
many Midwestern cities.
? Northeastern cities tend to have a greater proportion of parcel area
devoted to MMR uses than cities in other regions (see Figure 14) and a
smaller proportion devoted to SFDR uses (see Figure 18).  This is
unsurprising given the older age of these cities and the fact that a more
significant share of their development occurred prior to the advent of
the automobile and the decentralizing forces it brought about.  Many
residential areas of these cities are characterized by row homes, a
housing form included in the MMR category.
? Northeastern and Midwestern cities tend to have a higher proportion of
MU uses than cities in other regions (see Figure 15).  This too is as
expected given the older and denser nature of these cities.  The greater
spatial proportion of these cities that was built out prior to the
widespread implementation of Euclidean zoning may also contribute
to this pattern.
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Figure 11: Proportion of Total Parcel Area Devoted to AG Uses in Each Study City
Figure 12: Proportion of Total Parcel Area Devoted to COM Uses in Each Study City
129
Figure 13: Proportion of Total Parcel Area Devoted to IND Uses in Each Study City
Figure 14: Proportion of Total Parcel Area Devoted to MMR Uses in Each Study City
130
Figure 15: Proportion of Total Parcel Area Devoted to MU Uses in Each Study City
Figure 16: Proportion of Total Parcel Area Devoted to MFR Uses in Each Study City
131
Figure 17: Proportion of Total Parcel Area Devoted to PUB Uses in Each Study City
Figure 18: Proportion of Total Parcel Area Devoted to SFDR Uses in Each Study City
132
Figure 19: Proportion of Total Parcel Area Devoted to TCU Uses in Each Study City
Figure 20: Proportion of Total Parcel Area Devoted to UNKN Uses in Each Study City
133
Figure 21: Proportion of Total Parcel Area Devoted to VAC Uses in Each Study City
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? VAC uses tend to comprise a greater proportion of parcel area in
Southwestern cities and a lower proportion in Midwestern cities (see
Figure 21).  The greater preponderance of VAC uses in Southwestern
cities seems to be attributable to several of these cities annexing
extensive areas of undeveloped (non-AG) desert lands (e.g., El Paso,
Tucson, Albuquerque, Las Vegas, and San Diego).  Cities in the
Midwest, on the other hand, are more likely to be built out and
surrounded by incorporated suburbs that limit their capacity to annex
new undeveloped lands (e.g., Cleveland and Chicago).  While some
Midwestern cities do encompass significant undeveloped lands, being
in the nation?s agricultural heartland, these lands are more likely to be
AG uses than VAC uses.
Average Parcel Size by Land Use Class
Bar charts showing the average parcel size of each land use class within each
study city can be found in Figure 22 through Figure 32.   Comparing Houston to other
cities, the following patterns are notable:
? For most (but not all) land uses, Houston is not an outlier.  In fact, it
often appears near the middle of the distributions.
? Houston does have, on average, smaller COM, MU, SFDR, and VAC
parcels than all its peer cities in the South Central region, although it is
in the middle of these distributions when compared to all study cities
(see Figure 23, Figure 28, Figure 29, and Figure 32).  This finding
does not support Siegan?s claim that single-family detached residential
lot sizes are smaller in Houston than in other cities (that said, it is
possible that conditions have changed since he made his observations
several decades ago).
? Houston has, on average, larger IND parcels (10.6 acres) than cities in
other regions (see Figure 23).
? Houston has, on average, smaller MMR parcels (0.1 acres) than cities
in other regions and the smallest MMR parcel size amongst its peer
cities in the South Central region (see Figure 25).
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Figure 22: Average Size of AG Parcels in Each Study City
Figure 23: Average Size of COM Parcels in Each Study City
136
Figure 24: Average Size of IND Parcels in Each Study City
Figure 25: Average Size of MMR Parcels in Each Study City
137
Figure 26: Average Size of MU Parcels in Each Study City
Figure 27: Average Size of MFR Parcels in Each Study City
138
Figure 28: Average Size of PUB Parcels in Each Study City
Figure 29: Average Size of SFDR Parcels in Each Study City
139
Figure 30: Average Size of TCU Parcels in Each Study City
Figure 31: Average Size of UNKN Use Parcels in Each Study City
140
Figure 32: Average Size of VAC Parcels in Each Study City
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With respect to regional differences, the following patterns stand out:
? Cities in the Southeast and South Central regions have, on average,
larger COM parcel sizes than cities in other regions (see Figure 23).
? Cities in the Northeast tend to have, on average, smaller MMR parcels
than cities in other regions (see Figure 25).  This could be due, in part,
to a comparatively greater area of these cities developing prior to the
advent of zoning and minimum lot size provisions.
? The largest MU parcel sizes are, generally, amongst cities in the
Midwest and South Central regions and the smallest amongst cities in
the Northeast (see Figure 26).  Note that not all cities in the Midwest
and South Central regions follow this trend (e.g. Chicago and
Indianapolis).  The cities with the largest values for this metric (e.g.,
Kansas City and Arlington) have relatively few MU parcels and the
average acreage is easily brought up by a few large parcels.
? The largest MFR parcel sizes tend to be amongst cities in the
Southeast and South Central regions (see Figure 27).
? The largest PUB parcel sizes tend to be amongst cities in the
Southeast, South Central, and Southwest regions (see Figure 28).  This
is not surprising given that cities in these regions tend to be built more
recently with ample room set aside for schools, churches, and other
large public and quasi-public uses.  In some cities (e.g., Virginia
Beach) large military bases skew this metric higher.
? With the notable exception of Miami, Southeastern cities tend to have
the largest SFDR parcel sizes (see Figure 29).  This is followed closely
by South Central cities.
? Cities in the Southeast, South Central, and Southwest regions have, on
average, the largest VAC parcels (see Figure 32).
Land Use Relationship Metrics
As discussed in the previous chapter, the land use relationship metrics focus
on each land use?s locations relative to all the other land uses.  Three categories of
relationship metrics were computed for the study cities: (1) adjacency metrics, (2)
neighborhood metrics, and (3) proximity metrics.  The results for each group are
discussed in the sections below.
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Adjacency Metrics
The adjacency metrics measure which land uses directly border on each other
land use in each study city.  Specific metrics computed and discussed in the sections
that follow include (1) the proportion of shared parcel perimeter of each land use
class bordering on each other land use, (2) the proportion of parcels in each land use
class bordering each other land use, and (3) the proportion of parcels in each land use
class that border only the same land use.  Prior to presenting these metrics, however,
the values used for normalizing these metrics, the percent of citywide shared parcel
perimeter for each land use class, are described and presented.
Percent of Citywide Shared Parcel Perimeter for Each Land Use Class
Per Table 4, the adjacency metrics have their own unique set of values used
for their normalization; the percent of citywide shared parcel perimeter for each land
use class.  These values are calculated by looking at all the line segments where two
parcels abut each other and finding the proportion of their total length (throughout the
city for all land use classes) attributable to each land use class.  Note that in this
calculation, each adjoining length is counted twice, once for each adjoining land use.
For example, if a COM parcel is adjacent to an SFDR parcel, there are two shared
parcel boundary lines; one assigned the COM designation and the other designated
SFDR.  The total citywide shared parcel perimeter length involves tallying up the
(duplicate) lengths of each of these values.
Bar charts showing the percent of citywide shared parcel perimeter for each
land use class can be found in Figure 33 through Figure 43.   As one might expect, the
findings are similar (but not identical) to the proportion of total parcel area metrics
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described above.  Comparing Houston to other cities, the following patterns are
notable:
? For most (but not all) land uses, Houston is not an outlier.  In fact, it
often appears near the middle of the distributions.
? Houston has the highest percent of citywide shared parcel perimeter
involving the COM land use class of any city (11.4%, see Figure 34).
? Houston has a lower proportion of shared perimeter length devoted to
SFDR uses than most study cities (see Figure 40).  In fact, Houston?s
proportion (55.0%) is lower than any of its peer cities in the South
Central region.
? Houston has a greater proportion of shared parcel perimeter length
devoted to TCU uses (2.5%) than most cities and has the highest value
amongst its peer cities in the South Central region (see Figure 41).
? Houston has a greater proportion of shared parcel perimeter length
devoted to VAC uses (19.8%) than most cities (see Figure 43).
With respect to regional differences, the following patterns stand out:
? Northeastern cities tend to have a greater proportion of shared parcel
perimeter involving MMR uses than cities in other regions (see Figure
36) and a smaller proportion involving SFDR uses (see Figure 40).
? Northeastern and Midwestern cities tend to have a greater proportion
of shared parcel perimeter involving MU uses than cities in other
regions (see Figure 37).
144
Figure 33: Proportion of the Shared Parcel Perimeter Bordering AG Uses in Each Study City
Figure 34: Proportion of the Shared Parcel Perimeter Bordering COM Uses in Each Study City
145
Figure 35: Proportion of the Shared Parcel Perimeter Bordering IND Uses in Each Study City
Figure 36: Proportion of the Shared Parcel Perimeter Bordering MMR Uses in Each Study City
146
Figure 37: Proportion of the Shared Parcel Perimeter Bordering MU Uses in Each Study City
Figure 38: Proportion of the Shared Parcel Perimeter Bordering MFR Uses in Each Study City
147
Figure 39: Proportion of the Shared Parcel Perimeter Bordering PUB Uses in Each Study City
Figure 40: Proportion of the Shared Parcel Perimeter Bordering SFDR Uses in Each Study City
148
Figure 41: Proportion of the Shared Parcel Perimeter Bordering TCU Uses in Each Study City
Figure 42: Proportion of the Shared Parcel Perimeter Bordering UNKN Uses in Each Study City
149
Figure 43: Proportion of the Shared Parcel Perimeter Bordering VAC Uses in Each Study City
150
Proportion of Shared Parcel Perimeter of Each Land Use Class Bordering on Each
Other Land Use
There are a total of 121 individual metrics capturing the proportion of shared
parcel perimeter of each land use class bordering on each other land use (11 land use
classes * 11 land use classes = 121 land use relationships).   Note that, per Table 4,
non-normalized metrics for the UNKN land use class are not presented as this land
use class is not used in subsequent analyses.  That leaves 110 individual metrics for
which bar charts were produced showing the distribution of values amongst the study
cities.  As inclusion of these charts requires several pages, they have been placed in
appendices rather than in the main text.  Appendix B shows the bar charts for the non-
normalized values of these metrics and Appendix C shows the bar charts for their
normalized values.  Per Table 4, the normalized values were calculated by taking the
non-normalized values for each land use class and dividing them by the percent of
citywide shared parcel perimeter (see the section prior) of the adjacent land use
classes.
Also, for this set of metrics, it is important to recognize that the normalized
metrics shown in Appendix C are reciprocal amongst the two land uses involved in a
relationship.  In other words, the normalized value of the COM to SFDR relationship
is the same as the normalized value of the SFDR to COM relationship.  Thus, to
economize on space, only the 65 unique values for each land use combination are
151
included in Appendix C.309  Table 5 and Table 6 at the start of Appendices B and C,
respectively, provide page number indices to enable efficient referencing of specific
land use relationships.
Since the normalized values control for the disparate land use proportions in
each study city and are the metrics used in the PCA, the discussion of key patterns
that follows will focus on them as opposed to the non-normalized metrics.  That said,
interested readers are encouraged to study the non-normalized values as well.  While
not normalized, they can be more relatable as the units show the actual proportion of
each land use class? shared perimeter bordering other land uses.
To interpret the normalized values, recognize that a higher value represents a
greater tendency for the two land uses in question to be adjacent to each other relative
to other cities and a lower value just the opposite.  Using the COM-SFDR
relationship shown in Figure 290 as an example, Philadelphia has an inordinately
high tendency for COM and SFDR parcels to be adjacent to each other whereas San
Diego has an inordinately low tendency for COM and SFDR parcels to be adjacent to
each other (relative to the other study cities).
Keeping this in mind, the following patterns are notable when comparing
Houston to the other study cities:
? Houston is not a consistent outlier amongst these metrics (there are a
few exceptions, see below).  In fact, it often appears near the middle of
the distributions.  This observation does not support the alternative
309 65 values are shown, not 55 (half of the 110 possible combinations sans the UNKN class), because
the relationship of each land use class to itself (e.g., COM to COM) is also included as a unique metric.
This adds 10 additional metrics to the total (55 + 10 = 65) as there are 10 land use classes to relate to
themselves (again, not including the UNKN class as it is not used in subsequent analyses).
152
hypothesis that land use patterns in Houston are unique amongst large
American cities.
? Houston does exhibit the lowest tendency for COM uses to be adjacent
to other COM uses amongst all the study cities (see Figure 284).
? Houston has the highest tendency for MMR and UNKN adjacency (see
Figure 309), being a dramatic outlier in this regard.  This is likely
because many of the UNKN parcels in Houston were coded that way
because they are in the process of being developed and many of these
tend to be in rapidly redeveloping inner neighborhoods in which there
is a high amount of MMR development.  Note that Houston?s zoned
suburbs exhibit a similarly high value for this metric.
? Houston also has the highest tendency for MU and SFDR adjacency
(see Figure 314) of all the study cities.
? Houston has a higher tendency for AG and COM, AG and IND, and
COM and SFDR uses to be adjacent to each other compared with most
other study cities (see Figure 274, Figure 275, and Figure 290,
respectively).
? Houston has a lower tendency for COM and IND and MMR and PUB
uses to be adjacent to each other compared with most other study cities
(see Figure 285 and Figure 306, respectively) and all peer cities in the
South Central region.
? Houston has a lower tendency for TCU uses to be adjacent to each
other compared to most study cities (see Figure 333).
? Houston has the lowest tendency for COM and PUB uses to be
adjacent to each other amongst peer cities in the South Central region
(see Figure 289).
With respect to regional differences, the following patterns stand out:
? AG and SFDR adjacency tends to be greatest for cities in the Southeast
(see Figure 280).
? COM and MU adjacency tends to be greatest for cities in the
Southwest (see Figure 287).
? IND and MU adjacency and MU and SFDR adjacency tends to be
greatest for cities in the South Central region (see Figure 296 and
Figure 314, respectively).
? MMR and MFR adjacency tends to be lowest for cities in the
Northeast (see Figure 305).
? MMR adjacency to other MMR uses tends to be greatest in the South
Central region (see Figure 303).
? PUB adjacency to other PUB uses tends to be greatest amongst cities
in the Southwest (see Figure 324).
? SFDR adjacency to other SFDR uses tends to be greatest amongst
cities in the Northeast (see Figure 329).
153
? TCU adjacency to VAC uses tends to be greatest amongst cities in the
Northeast (see Figure 335).
? VAC adjacency to other VAC uses tends to be greatest amongst cities
in the Southwest (see Figure 337).
Proportion of Parcels in Each Land Use Class Bordering Each Other Land Use
There are a total of 121 individual metrics capturing the proportion of parcels
in each land use class bordering each other land use although, as with the previous set
of metrics, only 110 are featured here as UNKN is not used in subsequent analyses.
Given the large number of individual metrics, bar charts comparing them amongst
cities are relegated to appendices.  Appendix D features the bar charts for the raw
(non-normalized) metrics while Appendix E provides bar charts showing the
normalized metrics.
When interpreting the normalized metrics, higher values indicate a greater
tendency for the land uses shown to be bordering each other, from the perspective of
the subject land use.  It is important to recognize that these metrics are not reciprocals
of each other.  In other words, a greater tendency for SFDR uses to border COM uses
is not the same thing as a greater tendency for COM uses to border SFDR uses.  This
is because the metrics are calculated as proportions of each subject land use.  A high
tendency for SFDR uses to border COM uses means a high proportion of SFDR uses
border COM.  This does not necessarily mean the reciprocal is true; that a high
proportion of COM uses border SFDR.
Focusing in on the normalized metrics, the following patterns are notable
when comparing Houston to other cities:
? For most (but not all) land uses, Houston is not an outlier.  In fact, it
often appears near the middle of the distributions.  This does not
154
support the alternative hypothesis proposed in the methodology
chapter that Houston should be an outlier with a greater proportion of
parcels bordering other land uses due to its lack of zoning.
? Houston has the lowest tendency of all the study cities for COM
parcels to border other COM parcels (see Figure 459).
? Houston has a higher tendency than most study cities for SFDR
parcels to border COM parcels (see Figure 465).  This tendency is
greater than in any other peer city in the South Central region and
more akin to older denser cities in the Northeast and San Francisco
that experienced a greater proportion of development prior to zoning.
? Houston has a lower tendency for TCU parcels to border COM parcels
than most study cities and the lowest tendency for peer cities in the
South Central region (see Figure 466).
? Houston has a lower tendency for COM parcels to border IND parcels
than most study cities and the lowest tendency for peer cities in the
South Central region (see Figure 469).
? Houston has a lower tendency for COM parcels to border MFR parcels
than most study cities (see Figure 499).
? Houston has the lowest tendency for MMR parcels to border SFDR
parcels amongst peer cities in the South Central region (see Figure
521).
? Houston has a greater tendency for MFR parcels to border TCU
parcels than most study cities, although it is not as notable as in
Houston?s zoned suburbs (see Figure 533).
? Houston has one of the highest tendencies for SFDR uses to border
TCU uses amongst the study cities (see Figure 535), higher than all its
peer cities in the South Central region.
? Houston has a lower tendency for TCU parcels to border other TCU
parcels than most study cities (see Figure 536), including all peer cities
in the South Central region.
With respect to regional differences, the following patterns stand out:
? There is a greater tendency for COM, MFR, PUB, and TCU parcels to
border AG parcels in cities within the South Central region (see Figure
449, Figure 453, Figure 454, and Figure 456, respectively).
? There is a greater tendency for MU parcels to border COM parcels in
cities in the Southwest (see Figure 462).
? There is a greater tendency for MFR parcels to border COM parcels
amongst cities in the South Central region (see Figure 463).
? There is a greater tendency for SFDR parcels to border COM parcels
in Northeastern cities (see Figure 465).
? There is a greater tendency for MU parcels to border IND parcels in
Southwestern and South Central cities (see Figure 472).
155
? There is a greater tendency for COM, IND, PUB, and SFDR parcels to
border MMR parcels in Northeastern cities (see Figure 479, Figure
480, Figure 484, and Figure 485, respectively).
? There is a greater tendency for MMR parcels to border MMR parcels
in South Central cities (see Figure 481).
? There is a greater tendency for MU parcels to border MMR parcels in
South Central and Southwestern cities (see Figure 482).
? There is a greater tendency for COM and SFDR parcels to border MU
parcels in Northeastern and Midwestern cities (see Figure 489 and
Figure 495, respectively).
? There is a greater tendency for TCU parcels to border MU parcels in
Northeastern cities (see Figure 496).
? There is a greater tendency for PUB parcels to border MFR parcels in
Southwestern cities (see Figure 504).
? There is a greater tendency for SFDR parcels to border MFR parcels in
Northeastern cities (see Figure 505).
? There is a greater tendency for COM parcels to border PUB parcels in
Northeastern and Southeastern cities (see Figure 509).
? There is a greater tendency for MFR parcels to border PUB parcels in
South Central cities (see Figure 513).
? There is a greater tendency for PUB parcels to border PUB parcels in
Southwestern cities (see Figure 514).
? There is a greater tendency for SFDR parcels to border PUB parcels in
Northeastern cities (see Figure 515).
? There is a greater tendency for COM parcels to border SFDR parcels
in Southeastern and Midwestern cities and less of a tendency for this in
Northeastern cities (see Figure 519).
? There is a greater tendency for MMR parcels to border SFDR parcels
in South Central cities (see Figure 521).
? There is a greater tendency for SFDR parcels to border SFDR parcels
in Northeastern cities (see Figure 525).
? There is a greater tendency for SFDR parcels to border TCU parcels in
Northeastern cities (see Figure 526).
? There is a greater tendency for SFDR parcels to border VAC parcels in
Northeastern cities (see Figure 555).
Proportion of Parcels in Each Land Use Class that Border Only the Same Land Use
Bar charts showing normalized values for the proportion of parcels in each
land use class that border only the same land use can be found in Figure 44 through
156
Figure 54.  Bar charts showing the non-normalized values for these metrics can be
found in Appendix F.
Higher values for the normalized metrics indicate a greater tendency for
parcels to border only the same land use.  Focusing in on these normalized metrics,
the following patterns are notable when comparing Houston to other cities:
? For most (but not all) land uses, Houston is not an outlier.  In fact, it
often appears near the middle of the distributions.  This does not
support the alternative hypothesis proposed in the methodology
chapter that Houston should be an outlier and have a low value for
each of the land uses.
? Amongst all the study cities, Houston does have the least tendency for
COM parcels to border only other COM parcels (see Figure 45).
With respect to regional differences, the following patterns stand out:
? Cities in the South Central region have the greatest tendency for MMR
uses to border only other MMR uses (see Figure 47).
? Cities in the Northeast have the greatest tendency for SFDR uses to
border only other SFDR uses (see Figure 51) after controlling for the
relatively small proportions of these uses in those cities.
Neighborhood Metrics
The neighborhood metrics measure which land uses are near each other
(within 500 feet) in each study city.  Specific metrics include (1) the proportional area
of land uses within 500 feet of each land use; (2) the proportion of parcels in each
land use class that have each land use within 500 feet; and (3) the proportion of
parcels in each land use class that have zero, one, two, three, four, five, six, seven,
eight, or nine other land uses within 500 feet.  Results for each of these sets of metrics
are discussed in the sections that follow.
157
Figure 44: Proportion of AG Parcels Bordering Only Other AG Parcels (Normalized)
Figure 45: Proportion of COM Parcels Bordering Only Other COM Parcels (Normalized)
158
Figure 46: Proportion of IND Parcels Bordering Only Other IND Parcels (Normalized)
Figure 47: Proportion of MMR Parcels Bordering Only Other MMR Parcels (Normalized)
159
Figure 48: Proportion of MU Parcels Bordering Only Other MU Parcels (Normalized)
Figure 49: Proportion of MFR Parcels Bordering Only Other MFR Parcels (Normalized)
160
Figure 50: Proportion of PUB Parcels Bordering Only Other PUB Parcels (Normalized)
Figure 51: Proportion of SFDR Parcels Bordering Only Other SFDR Parcels (Normalized)
161
Figure 52: Proportion of TCU Parcels Bordering Only Other TCU Parcels (Normalized)
Figure 53: Proportion of UNKN Parcels Bordering Only Other UNKN Parcels (Normalized)
162
Figure 54: Proportion of VAC Parcels Bordering Only Other VAC Parcels (Normalized)
163
Proportional Area of Land Uses Within 500 Feet of Each Land Use
There are a total of 121 individual metrics capturing the proportional area of
land uses within 500 feet of each land use.  Given the large number of individual
metrics, bar charts comparing them amongst cities are relegated to appendices.
Appendix G features the bar charts for the raw (non-normalized) metrics while
Appendix H provides bar charts showing the normalized metrics.
When interpreting the normalized metrics, higher values indicate a greater
tendency for a given land use to be close to the subject land use in high quantities.  As
these metrics are based on proportions derived from buffers of each land use class,
they are not reciprocals.  Thus, a greater tendency for COM uses to be near SFDR
uses does not mean the same thing as a greater tendency for SFDR uses to be near
COM uses.
Focusing in on the normalized metrics, the following patterns are notable
when comparing Houston to other cities:
? For most (but not all) land uses, Houston is not an outlier.  In fact, it
often appears near the middle of the distributions.  This does not
support the alternative hypothesis proposed in the methodology
chapter that Houston should be a consistent outlier amongst the study
cities.
? Houston has a lower proportional area of COM uses near COM uses
than most study cities and the lowest value amongst peer cities in the
South Central region (see Figure 702).
? Houston has a lower proportional area of COM uses near IND uses
than most study cities and the lowest value amongst peer cities in the
South Central region (see Figure 713).
? Houston has a higher proportional area of SFDR uses near IND uses
than most study cities (see Figure 719).
? Houston has a lower proportional area of COM uses near MU uses
than most study cities and the lowest value amongst peer cities in the
South Central region (see Figure 735).
164
? Houston has a higher proportional area of SFDR uses near MU uses
than most study cities, including all peer cities in the South Central
region (see Figure 741).
? Houston has a lower proportional area of COM uses near TCU uses
than most study cities (see Figure 779).
With respect to regional differences, the following patterns stand out:
? Cities in the Northeast have a lower proportional area of COM uses
near COM uses (see Figure 702).
? Cities in the Northeast and Midwest have a lower proportional area of
MFR uses near COM uses (see Figure 706).
? Cities in the Southwest have a lower proportional area of VAC uses
near COM uses while cities in the Midwest have a higher proportional
area (see Figure 711).
? Cities in the Southwest have a lower proportional area of VAC uses
near IND uses while cities in the Midwest have a higher proportional
area (see Figure 722).
? Cities in the Southwest have a higher proportional area of COM and
MFR uses near MMR uses (see Figure 724 and Figure 728,
respectively).
? Cities in the Southeast and Northeast have a higher proportional area
of IND uses near MMR uses (see Figure 725).
? Cities in the Midwest have a higher proportional area of VAC uses
near MMR uses and cities in the Southwest the opposite (see 674).
? Cities in the Southeast and Southwest have a higher proportional area
of COM uses near MU uses (see Figure 735).
? Cities in the South Central region have a higher proportional area of
IND and MMR uses near MU uses (see Figure 736 and Figure 737,
respectively)
? Cities in the Southwest have a lower proportional area of VAC uses
near MU uses (see Figure 744).
? Cities in the Southeast and South Central regions have a higher
proportional area of MMR uses near MFR uses whereas cities in the
Northeast have a lower proportional area (see Figure 748).
? Cities in the Southeast and Southwest have a higher proportional area
of MU uses near MFR uses (see Figure 749).
? Cities in the Northeast have a lower proportional area of MFR uses
near MFR uses (see Figure 750).
? Cities in the Midwest have a higher proportional area of VAC uses
near MFR uses whereas cities in the Southwest have a lower
proportional area (see Figure 755).
? Cities in the Southeast and Southwest have a higher proportional area
of COM uses near PUB uses (see Figure 757).
165
? Cities in the Southeast have a higher proportional area of IND uses
near PUB uses (see Figure 758).
? Cities in the Southeast and South Central regions have a higher
proportional area of MMR uses near PUB uses whereas cities in the
Northeast have the opposite (see Figure 759).
? Cities in the Southeast and Southwest have a higher proportional area
of MU uses near PUB uses (see Figure 760).
? Cities in the Northeast and Midwest have a lower proportional area of
MFR uses near PUB uses (see Figure 761).
? Cities in the Northeast have a lower proportional area of PUB uses
near PUB uses (see Figure 762).
? Cities in the Midwest have a higher proportional area of VAC uses
near PUB uses whereas cities in the Southwest have a lower
proportional area (see Figure 766).
? Cities in the Southwest and Northeast have a higher proportional area
of SFDR uses near SFDR uses whereas cities in the Midwest and
Southeast have a lower proportional area (see Figure 774).
? Cities in the Southwest have a lower proportional area of VAC uses
near PUB uses (see Figure 777).
? Cities in the Southwest have a higher proportional area of PUB uses
near VAC uses (see Figure 806).
Proportion of Parcels in Each Land Use Class that Have Each Land Use Within 500
Feet
There are a total of 110 individual metrics capturing the proportion of parcels
in each land class that have each land use within 500 feet.  Given the large number of
individual metrics, bar charts comparing them amongst cities are relegated to
appendices.  Appendix I features the bar charts for the raw (non-normalized) metrics
while Appendix J provides bar charts showing the normalized metrics.
When interpreting the normalized metrics, higher values indicate a greater
tendency for a given land use to be close to the subject land use.  As these metrics are
based on proportions of the total number of parcels in each land use class, they are
not reciprocals.  Thus, a greater tendency for COM uses to be near SFDR uses does
not mean the same thing as a greater tendency for SFDR uses to be near COM uses.
166
Focusing in on the normalized metrics, the following patterns are notable
when comparing Houston to other cities:
? For most (but not all) land uses, Houston is not an outlier.  In fact, it
often appears near the middle of the distributions.  This does not
support the alternative hypothesis proposed in the methodology
chapter that Houston should be a consistent outlier amongst the study
cities.
? Houston has the lowest tendency amongst all study cities for COM and
MU uses to be near COM uses (see Figure 932 and Figure 935).
? Houston has the second lowest tendency amongst all study cities for
IND uses to be near COM uses and the lowest value amongst all peer
cities in the South Central region (see Figure 933).
? Houston has the third lowest tendency amongst all study cities for
MFR uses to be near COM uses and the lowest value amongst all peer
cities in the South Central region (see Figure 936).
? Houston has the fourth lowest tendency amongst all study cities for
PUB uses to be near COM uses (see Figure 937).
? Houston has the second lowest tendency amongst all study cities for
TCU uses to be near COM uses (see Figure 939).
? Houston has the fourth lowest tendency amongst all study cities for
COM uses to be near IND uses and the lowest value amongst all peer
cities in the South Central region (see Figure 942).
? Houston has a lower tendency amongst all study cities for MFR uses to
be near IND uses and the lowest value amongst all peer cities in the
South Central region (see Figure 946).
? Houston has the highest tendency for SFDR uses to be near MU uses
amongst all peer cities in the South Central region (see Figure 968).
? Houston has the highest tendency for MMR, MU, MFR, PUB, SFDR,
TCU, and VAC uses to be near SFDR uses amongst all peer cities in
the South Central region (see Figure 994 through Figure 1000).
? Houston has the lowest tendency for TCU uses to be near TCU uses
amongst all peer cities in the South Central region (see Figure 1009).
With respect to regional differences, the following patterns stand out:
? Cities in the South Central and Southwest regions have a greater
tendency for AG uses to be near COM uses (see Figure 931).
? Cities in the Southeast have a greater tendency for COM, IND, and
PUB uses to be near COM uses (see Figure 932, Figure 933, and
Figure 937).
? Cities in the Southwest have a lower tendency for VAC uses to be near
COM uses (see Figure 940).
167
? Cities in the Northeast have a lower tendency for COM and MFR uses
to be near MMR uses (see Figure 952 and Figure 956).
? Cities in the South Central and Southeast regions have a higher
tendency for IND and MMR uses to be near MMR uses (see Figure
953 and Figure 954).
? Cities in the Southwest and Northeast have a lower tendency for IND
uses to be near MMR uses (see Figure 953).
? Cities in the South Central region have a higher tendency for MU,
PUB, SFDR, and TCU uses to be near MMR uses (see Figure 955 and
Figure 957 through Figure 959).
? Cities in the Northeast have a lower tendency for MMR, MU, PUB,
SFDR, TCU, and VAC uses to be near MMR uses (see Figure 954,
Figure 955, and Figure 958 through Figure 960).
? Cities in the Southwest and Southeast have a higher tendency for
COM, IND, MMR, MU, MFR, PUB, TCU, and VAC uses to be near
MU uses (see Figure 962 through Figure 967, Figure 969, and Figure
970).
? Cities in the Southwest have a lower tendency for COM, IND, and
VAC uses to be near PUB uses (see Figure 982, Figure 983, and
Figure 990).
? Cities in the Southwest and Midwest have a higher tendency for MU
uses to be near PUB uses (see Figure 985).
? Cities in the Midwest have a higher tendency for VAC uses to be near
PUB uses (see Figure 990).
? Cities in the Southwest have a lower tendency for AG uses to be near
SFDR uses (see Figure 991).
? Cities in the Southwest and Northeast have a higher tendency for
COM, IND, MMR, MFR, and PUB uses to be near SFDR uses (see
Figure 992 through Figure 997).
? Cities in the Southeast have a lower tendency for COM and MFR uses
to be near SFDR uses (see Figure 992 and Figure 996).
? Cities in the Northeast have a higher tendency for SFDR, TCU, and
VAC uses to be near SFDR uses (see Figure 998 through Figure
1000).
? Cities in the Northwest have the lowest tendency for TCU uses to be
near SFDR uses (see Figure 999).
? Cities in the Southwest have the lowest tendency for IND uses to be
near TCU uses (see Figure 1003).
? Cities in the Midwest have a higher tendency for AG, COM, IND,
MMR, MU, MFR, PUB, TCU, and VAC uses to be near VAC uses
(see Figure 1021 through Figure 1027, Figure 1029, and Figure 1030).
? Cities in the Southwest have a lower tendency for COM, IND, MMR,
MU, MFR, PUB, SFDR, TCU, and VAC uses to be near VAC uses
(see Figure 1022 through Figure 1030).
168
? Cities in the Southeast have a lower tendency for TCU uses to be near
VAC uses (see Figure 1029).
Proportion of Parcels in Each Land Use Class that Have Zero, One, Two, Three,
Four, Five, Six, Seven, Eight, or Nine Other Land Uses Within 500 Feet
There are a total of 92 individual metrics capturing the proportion of parcels
in each land use class that have zero, one, two, three, four, five, six, seven, eight, or
nine other land uses within 500 feet.310  Given the large number of individual metrics,
bar charts comparing them amongst cities are relegated to appendices.  Appendix K
features the bar charts for the raw (non-normalized) metrics while Appendix L
provides bar charts showing the normalized metrics.  When interpreting the
normalized metrics, higher values indicate a greater tendency for a land use to have
the given number of other land uses nearby.
Focusing in on the normalized metrics, the following patterns are notable
when comparing Houston to other cities:
? For most (but not all) land uses, parcels in Houston generally do not
have more other land uses nearby than in other cities.  This does not
support the hypothesis proposed in the methodology chapter that
Houston should have a greater variety of land uses near each other
(i.e., more land use mixing).
? Houston tends to have a greater variety of other land uses nearby AG
parcels than other cities and the greatest tendency for this amongst
peer cities in the South Central region.
? Houston is the only city with nine other land uses near TCU parcels
but this is an anomaly attributable to a single parcel with this
relationship. When looking more broadly at the other metrics showing
a high number of other land uses near TCU uses (i.e., the metrics for
six, seven, and either other land uses), Houston is not an outlier.
310 The number of metrics is less than the 100 that are possible (recall that results are not reported for
the UNKN land use class) because there were no cities with nine other land uses nearby for eight of the
ten land use classes studied.
169
With respect to regional differences, the following patterns stand out:
? Cities in the Southwest tend to have the fewest other land uses near
AG parcels.
? Cities in the Southwest tend to have the fewest other land uses near
COM, IND, SFDR, and VAC parcels whereas cities in the Northeast
and Midwest tend to have the most other land uses near these parcels.
? Cities in the Northeast and Midwest tend to have the most other land
uses near MMR and MFR parcels.
? Cities in the Southwest and South Central regions tend to have the
fewest other land uses near MU parcels.
? Cities in the Southwest and South Central regions tend to have the
fewest other land uses near PUB parcels whereas cities in the
Northeast and Midwest tend to have the most other land uses near
these parcels.
? Cities in the Southeast tend to have the fewest other land uses near
TCU parcels whereas cities in the Northeast and Midwest tend to have
the most other land uses near these parcels.
Proximity Metrics
The proximity metrics systematically measure, for each land use class, the
average distance to the nearest parcel of each land use.  A total of 110 individual
metrics are needed to capture these relationships for all land use classes (except
UNKN).  Given the large number of individual metrics, bar charts comparing them
amongst cities are relegated to appendices.  Appendix M features the bar charts for
the raw (non-normalized) metrics while Appendix N provides bar charts showing the
normalized metrics.
When interpreting the normalized metrics, higher values indicate a greater
tendency for the given land uses to be farther apart.  As these metrics are averages
amongst all the parcels in each land use class, they are not reciprocals, although they
are closely related.  Thus, a greater tendency for COM uses to be near SFDR uses
170
does not mean the same thing as a greater tendency for SFDR uses to be near COM
uses.
Focusing in on the normalized metrics, the following patterns are notable
when comparing Houston to other cities:
? Houston is not a consistent outlier amongst study cities or amongst
cities in its region, thereby not supporting the hypothesis stated in the
methodology chapter that it should be.  That said, it is a more frequent
outlier for these metrics than for some of the other metrics in the study.
These instances are highlighted below.
? Houston has the second highest average distance between COM
parcels amongst all study cities and the highest average distance
amongst peer cities in the South Central region (see Figure 1336).
? Houston has one of the higher average distances from COM parcels to
the nearest IND parcel amongst the study cities (see Figure 1337).
? Houston has the shortest average distance from COM parcels to the
nearest SFDR and VAC parcels amongst its peer cities in the South
Central region (see Figure 1342 and Figure 1344).
? Houston has the third greatest average distance from COM parcels to
the nearest IND parcel amongst all study cities and the highest average
distance amongst peer cities in the South Central region (see Figure
1346).
? Houston has one of the higher average distances from TCU parcels to
the nearest IND parcel and the highest average distance amongst peer
cities in the South Central region (see Figure 1353).
? Houston has the second greatest average distance from COM parcels
to the nearest MFR parcel amongst all study cities (see Figure 1356).
? Houston has one of the highest average distances from MFR parcels to
the nearest MMR parcel amongst all study cities and the highest
average distance amongst peer cities in the South Central region (see
Figure 1360).
? Houston has the longest average distance from TCU parcels to the
nearest MMR parcel amongst its peer cities in the South Central region
(see Figure 1363).
? Houston has one of the lower average distances from MMR parcels to
the nearest MU parcel (see Figure 1368).
? Houston has the shortest average distance from SFDR parcels to the
nearest MU parcel amongst its peer cities in the South Central region
(see Figure 1372).
? Houston has the shortest average distance from AG and SFDR parcels
to the nearest MFR parcel amongst its peer cities in the South Central
region (see Figure 1375 and Figure 1382).
171
? Houston has the second greatest average distance from COM parcels
to the nearest MFR parcel amongst all study cities (see Figure 1376).
? Houston has the second greatest average distance between MFR
parcels amongst all study cities and the greatest average distance
amongst its peer cities in the South Central region (see Figure 1380).
? Houston has the greatest average distance from COM parcels to the
nearest PUB parcel amongst all study cities (see Figure 1386).
? Houston has the shortest average distance from SFDR and VAC
parcels to the nearest PUB parcel amongst its peer cities in the South
Central region (see Figure 1392 and Figure 1394).
? Houston has the greatest average distance from COM parcels to the
nearest SFDR parcel amongst all study cities (see Figure 1396).
? Houston has one of the lower average distances from MU parcels to
the nearest SFDR parcel (see Figure 1399).
? Houston has the second greatest average distance from COM parcels
to the nearest TCU parcel amongst all study cities (see Figure 1406).
? Houston has the greatest average distance from MU parcels to the
nearest TCU parcel amongst its peer cities in the South Central region
(see Figure 1409).
? Houston has the shortest average distance from SFDR parcels to the
nearest TCU parcel amongst its peer cities in the South Central region
(see Figure 1412).
With respect to regional differences, the following patterns stand out:
? Cities in the Southwest have a tendency for COM, SFDR, and VAC
uses to be located further away from AG uses (see Figure 1326, Figure
1332, and Figure 1334).
? Cities in the Midwest have a tendency for COM uses to be located
further away from other COM uses (see Figure 1336).
? Cities in the Southwest have a tendency for MU uses to be located
closer to COM uses (see Figure 1339).
? Cities in the Southeast have a tendency for SFDR use to be located
further from COM uses whereas cities in the Northeast have a
tendency for SFDR uses to be located closer to COM uses (see Figure
1342).
? Cities in the Southwest have a tendency for TCU uses to be located
further from COM uses (see Figure 1343).
? Cities in the Southwest and Southeast have a tendency for VAC uses
to be located further from COM uses (see Figure 1344).
? Cities in the South Central region have a tendency for IND uses to be
located further from other IND uses (see Figure 1347).
172
? Cities in the Southwest have a tendency for MU, SFDR, TCU, and
VAC uses to be located further from IND uses (see Figure 1349,
Figure 1352, Figure 1353, and Figure 1354).
? Cities in the South Central region have a tendency for COM uses to be
located further from MMR uses (see Figure 1356).
? Cities in the Midwest have a tendency for MMR uses to be located
further away from other MMR uses (see Figure 1358).
? Cities in the Southwest have a tendency for TCU uses to be located
further away from MMR uses whereas cities in the Southeast have a
tendency for TCU uses to be located closer to MMR uses (see Figure
1363).
? Cities in the Southwest, Southeast, and South Central regions have a
tendency for VAC uses to be located further away from MMR uses
(see Figure 1364).
? Cities in the Southwest and Northeast have a tendency for IND uses to
be closer to MU uses (see Figure 1367)
? Cities in the Midwest and South Central regions have a tendency for
MU uses to be located further away from other MU uses (see Figure
1369).
? Cities in the South Central region have a tendency for COM, MU,
MFR, and SFDR uses to be located further from MFR uses (see Figure
1376, Figure 1379, Figure 1380, and Figure 1382).
? Cities in the Northeast have a tendency for MMR uses to be located
further from MFR uses (see Figure 1378) and SFDR uses to be located
closer to MFR uses (see Figure 1382).
? Cities in the Northwest have a tendency for PUB uses to be located
closer to MFR uses (see Figure 1381).
? Cities in the Southwest and South Central regions have a tendency for
VAC uses to be located further from MFR uses (see Figure 1384).
? Cities in the Southwest and South Central regions have a tendency for
COM and PUB uses to be located further away from PUB uses
whereas cities in the Northeast have a tendency for COM uses to be
located closer to PUB uses (see Figure 1386 and Figure 1391).
? Cities in the Southwest and Southeast regions have a tendency for
MFR uses to be located further away from PUB uses (see Figure
1390).
? Cities in the Southwest, Southeast, and South Central regions have a
tendency for SFDR and VAC uses to be located further away from
PUB uses and cities in the Northeast have a tendency for SFDR and
VAC uses to be located closer to PUB uses (see Figure 1392 and
Figure 1394).
? Cities in the Northeast have a tendency for MMR uses to be located
further away from SFDR uses and cities in the Midwest have a
tendency for MMR uses to be located closer to SFDR uses (see Figure
1398).
173
? Cities in the Northeast have a tendency for MFR uses to be located
further away from SFDR uses and cities in the Southwest have a
tendency for MFR uses to be located closer to SFDR uses (see Figure
1400).
? Cities in the Northeast have a tendency for PUB uses to be located
further away from SFDR uses (see Figure 1401).
? Cities in the Southwest and South Central regions have a tendency for
SFDR uses to be located closer to other SFDR uses (see Figure 1402).
? Cities in the Northwest have a tendency for TCU uses to be located
further from SFDR uses (see Figure 1403).
? Cities in the Northeast and Southwest have a tendency for VAC uses
to be located further from SFDR uses whereas cities in the Midwest
have a tendency for VAC uses to be located closer to SFDR uses (see
Figure 1404).
? Cities in the Northeast and Southeast have a tendency for COM uses to
be located closer to TCU uses (see Figure 1406).
? Cities in the Southwest have a tendency for MMR, MFR, and PUB
uses to be located further from TCU uses (see Figure 1408, Figure
1410, and Figure 1411).
? Cities in the Northeast have a tendency for SFDR uses to be located
closer to TCU uses (see Figure 1412).
? Cities in the Southwest have a tendency for COM, IND, MMR, MU,
MFR, PUB, SFDR, and VAC uses to be located further from VAC
uses (see Figure 1426, Figure 1427,Figure 1428, Figure 1429, Figure
1430, Figure 1431, Figure 1432, and Figure 1434).
? Cities in the Midwest have a tendency for MMR uses to be located
closer to VAC uses (see Figure 1428).
? Cities in the Northeast have a tendency for SFDR uses to be located
closer to VAC uses (see Figure 1432).
Transportation-Land Use Relationship Metrics
The transportation-land use relationship metrics explore the connections
between transportation infrastructure and land use.  Specific metrics computed and
discussed in the sections that follow include (1) the proportional area of each land use
within 200 feet of non-access controlled arterial roadway centerlines or rail lines, (2)
the proportional area of each land use within a half mile of a limited access highway
174
exit, and (3) the average distance of industrial parcels to the nearest rail line or limited
access highway.
Proportional Area of Each Land Use Within 200 Feet of Non-Access Controlled
Arterial Roadway Centerlines or Rail Lines
This set of metrics considers the land use composition near arterial roadways
and rail lines.  The results for arterial roadways are discussed first followed by those
for rail lines.
Arterials
There are a total of 11 metrics showing the proportion of total parcel area
devoted to each land use within 200 feet of an arterial roadway; one for each land use
class.  Bar charts for the normalized version of each of these metrics can be found in
Figure 55 through Figure 65.   Bar charts for the non-normalized version of these
metrics can be found in Appendix O.  Higher values for the normalized metrics
indicate a greater tendency for that land use type to be found near arterial roadways.
Focusing in on the normalized metrics, the following patterns are notable
when comparing Houston to other cities:
? Houston is generally not an outlier amongst the study cities for any of
the metrics.  This does not support the hypothesis proposed in the
methodology chapter that Houston should have a greater proportion of
COM uses along arterial roadways than zoned cities.  In fact, Houston
ranks near the lower end of study cities when considering the
normalized proportion of area devoted to COM uses within 200 feet of
arterials (that said, it does have the third highest value for this metric
prior to normalization).
? Houston has the lowest proportion of land near arterials devoted to
PUB uses amongst its peer cities in the South Central region (see
Figure 61).
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Figure 55: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to AG Uses (Normalized)
Figure 56: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to COM Uses (Normalized)
176
Figure 57: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to IND Uses (Normalized)
Figure 58: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MMR Uses (Normalized)
177
Figure 59: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MU Uses (Normalized)
Figure 60: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MFR Uses (Normalized)
178
Figure 61: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to PUB Uses (Normalized)
Figure 62: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to SFDR Uses (Normalized)
179
Figure 63: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to TCU Uses (Normalized)
Figure 64: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to UNKN Uses (Normalized)
180
Figure 65: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to VAC Uses (Normalized)
181
With respect to regional differences, the following patterns stand out:
? Cities in the Southwest tend to have a greater proportion of land near
arterials devoted to AG uses (see Figure 55).
? Cities in the Southeast tend to have a greater proportion of land near
arterials devoted to COM uses whereas cities in the Northeast have a
lower proportion (see Figure 56).
? Cities in the Southwest tend to have a greater proportion of land near
arterials devoted to MFR uses whereas cities in the Midwest have a
lower proportion (see Figure 57).
? Cities in the Southwest and Northwest tend to have a lower proportion
of land near arterials devoted to PUB uses (see Figure 61).
? Cities in the Southwest tend to have a greater proportion of land near
arterials devoted to SFDR uses whereas cities in the Midwest and
Southeast have a lower proportion (see Figure 62).
? One contingent of cities in the Southwest tend to have a greater
proportion of land near arterials devoted to TCU uses whereas another
contingent along with Midwest cities has a lower proportion (see
Figure 63).
? Cities in the Midwest tend to have a greater proportion of land near
arterials devoted to VAC uses whereas cities in the Southwest have a
lower proportion (see Figure 65).
Rail Lines
As with arterials, there are a total of 11 metrics showing the proportion of
total parcel area devoted to each land use within 200 feet of a rail line.  Bar charts for
the normalized version of each of these metrics can be found in Figure 66 through
Figure 76.   Bar charts for the non-normalized version of these metrics can be found
in Appendix P.  Higher values for the normalized metrics indicate a greater tendency
for that land use type to be found near rail lines.
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Figure 66: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to AG Uses (Normalized)
Figure 67: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to COM Uses (Normalized)
183
Figure 68: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to IND Uses (Normalized)
Figure 69: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MMR Uses (Normalized)
184
Figure 70: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MU Uses (Normalized)
Figure 71: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MFR Uses (Normalized)
185
Figure 72: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to PUB Uses (Normalized)
Figure 73: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to SFDR Uses (Normalized)
186
Figure 74: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to TCU Uses (Normalized)
Figure 75: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to UNKN Uses (Normalized)
187
Figure 76: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to VAC Uses (Normalized)
188
Focusing in on the normalized metrics, the following patterns are notable
when comparing Houston to other cities:
? Houston is generally not an outlier amongst the study cities for any of
the metrics.  This does not support the hypothesis proposed in the
methodology chapter that Houston should have a greater proportion of
SFDR uses along rail lines than zoned cities.
? Houston has a higher proportion of land near rail lines devoted to
MMR uses compared to most study cities (see Figure 69).
? Houston has one of the lowest proportions of land near rail lines
devoted to MU uses amongst the study cities (see Figure 70).
With respect to regional differences, the following patterns stand out:
? Cities in the Southeast tend to have a greater proportion of land near
rail lines devoted to AG uses (see Figure 66).
? Cities in the Southwest tend to have a greater proportion of land near
rail lines devoted to COM uses (see Figure 67).
? Cities in the Northeast and Southwest tend to have a greater proportion
of land near rail lines devoted to MFR uses (see Figure 71).
? Cities in the Southwest tend to have a smaller proportion of land near
rail lines devoted to PUB uses (see Figure 72).
? Cities in the Southwest and Southeast tend to have a greater proportion
of land near rail lines devoted to TCU uses (see Figure 74).
? Cities in the Midwest tend to have a greater proportion of land near
rail lines devoted to VAC uses whereas cities in the Southwest have
less (see Figure 76).
Proportional Area of Each Land Use Within a Half Mile of a Limited Access
Highway Exit
There are a total of 11 metrics showing the proportional area of each land use
within a half mile of a limited access highway exit.  Bar charts for the normalized
version of each of these metrics can be found in Figure 77 through Figure 87.   Bar
charts for the non-normalized version of these metrics can be found in Appendix Q.
Higher values for the normalized metrics indicate a greater tendency for that land use
type to be found near highway exits.
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Figure 77: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to AG Uses (Normalized)
Figure 78: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to COM Uses (Normalized)
190
Figure 79: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to IND Uses (Normalized)
Figure 80: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to MMR Uses (Normalized)
191
Figure 81: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to MU Uses (Normalized)
Figure 82: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to MFR Uses (Normalized)
192
Figure 83: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to PUB Uses (Normalized)
Figure 84: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to SFDR Uses (Normalized)
193
Figure 85: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to TCU Uses (Normalized)
Figure 86: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to UNKN Uses (Normalized)
194
Figure 87: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to VAC Uses (Normalized)
195
Focusing in on the normalized metrics, the following patterns are notable
when comparing Houston to other cities:
? Houston is generally not an outlier amongst the study cities for any of
the metrics.  This does not support the hypothesis proposed in the
methodology chapter that Houston should have a greater proportion of
COM uses near highway exits (that said, it does have the highest value
for this metric amongst all study cities prior to normalization).
? Houston has the highest proportion of land near highway exits devoted
to AG uses amongst its peer cities in the South Central region (see
Figure 77).
With respect to regional differences, the following patterns stand out:
? Cities in the Southeast tend to have a greater proportion of land near
highway exits devoted to MMR uses and cities in the Northeast a
lower proportion (see Figure 80).
? Cities in the Southwest and Southeast tend to have a smaller
proportion of land near highway exits devoted to MU uses and a
greater proportion of land near highway exits devoted to MFR uses
(see Figure 81 and Figure 82).
? Cities in the Northeast tend to have a smaller proportion of land near
highway exits devoted to SFDR uses (see Figure 84).
? Cities in the Southwest tend to have a smaller proportion of land near
highway exits devoted to VAC uses (see Figure 87).
Average Distance of Industrial Parcels to the Nearest Rail Line or Limited Access
Highway
This set of metrics considers the average distance of industrial parcels to the
nearest rail line or limited access highway.  Results for rail lines are discussed first
followed by results for limited access highways.
Rail Lines
Bar charts showing the non-normalized and normalized metrics for rail lines
are shown in Figure 88 and Figure 89, respectively.  Larger normalized values mean
longer distances between IND parcels and rail lines.
196
Figure 88: Average Distance Between IND Parcels and the Nearest Rail Line
Figure 89: Average Distance Between IND Parcels and the Nearest Rail Line (Normalized)
197
It was hypothesized in the methodology chapter that the distances from IND
parcels to rail lines would be greater in Houston than other study cities.  It is clear
from the bar charts that this is not the case.  Considering either the original or
normalized metrics, Houston is located towards the middle of the distribution and is
clearly not an outlier amongst the study cities.  After normalization, Houston does
skew a bit higher than other study cities, including most of its peers in the South
Central region, however, there are still several cities that rank higher than it.   There
are also no discernable regional patterns to the normalized results.
Limited Access Highways
Bar charts showing the non-normalized and normalized metrics for limited
access highways are shown in Figure 90 and Figure 91, respectively.   As with rail
lines, it was hypothesized that the distances between IND parcels and the nearest
limited access highway would be greater in Houston than in other study cities.  Once
again, the data generally do not support the hypothesis that Houston is an outlier.
That said, when considering the normalized version of the metric, Houston does skew
more towards the upper end of the distribution (i.e., has the longest distances between
IND parcels and limited access highways).  Notably, it also has the highest
normalized value for this metric amongst all peer cities in the South Central region.
Considering regional patterns, the normalized metrics indicate a tendency for
distances to be greater in Northeastern cities and shorter in Southwestern cities.
198
Figure 90: Average Distance Between IND Parcels and the Nearest Limited Access Highway
Figure 91: Average Distance Between IND Parcels and the Nearest Limited Access Highway (Normalized)
199
Land Use Clustering Metrics
The final set of metrics considers the degree of clustering of each land use
class as determined by the nearest neighbor index.  Altogether, there are 10 nearest
neighbor index metrics, one for each land use class except UNKN.  The indices are
inherently normalized by the area of each study city so require no further
normalization.  Bar charts for each of the metrics can be found in Figure 92 through
Figure 101.   Recall that the smaller the value of the index, the greater the degree of
clustering.
The following patterns are notable when comparing Houston to other cities:
? Houston is not a consistent outlier amongst the study cities for all the
metrics.  However, there are some notable exceptions (see below).
This generally does not support the hypothesis proposed in the
methodology chapter that Houston should have the lowest amount of
clustering for all land use types.
? Houston does exhibit the least amount of clustering for COM uses
amongst all study cities (see Figure 93).
? Houston does tend to exhibit a higher degree of MMR clustering than
many of the study cities (see Figure 95).
? Houston exhibits the third least amount of clustering for MFR uses and
the least amount amongst peer cities in the South Central region (see
Figure 97).
With respect to regional differences, the following patterns stand out:
? Cities in the Southwest tend to have the highest degree of clustering
for AG uses (see Figure 92).
? Cities in the Southeast tend to have the highest degree of clustering for
COM uses (see Figure 92).
? Cities in the Northeast and Midwest tend to have the most dispersed
distribution of IND uses whereas cities in the Southwest tend to
exhibit the most clustering for this use (see Figure 93).
? Cities in the Midwest and South Central regions tend to exhibit the
least amount of clustering for MU uses (see Figure 96).
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Figure 92: Average Nearest Neighbor Index for AG Uses
Figure 93: Average Nearest Neighbor Index for COM Uses
201
Figure 94: Average Nearest Neighbor Index for IND Uses
Figure 95: Average Nearest Neighbor Index for MMR Uses
202
Figure 96: Average Nearest Neighbor Index for MU Uses
Figure 97: Average Nearest Neighbor Index for MFR Uses
203
Figure 98: Average Nearest Neighbor Index for PUB Uses
Figure 99: Average Nearest Neighbor Index for SFDR Uses
204
Figure 100: Average Nearest Neighbor Index for TCU Uses
Figure 101: Average Nearest Neighbor Index for VAC Uses
205
? Cities in the Midwest exhibit a split distribution for the clustering of
PUB uses with one contingent of cities showing the highest degree of
clustering amongst the study cities and another contingent the lowest
(see Figure 98).
? Cities in the Northeast exhibit the highest degree of SFDR clustering
whereas cities in the Northwest have the most disbursed pattern for
this land use (see Figure 99).
Summary
The individual land use metrics do not show Houston to be a consistent outlier
amongst the cities study or even amongst its peer cities in the South Central region.
That said, there were several metrics where Houston does appear to be anomalous.
Several of these relate to COM uses and their distribution.  In general, it appears that
COM uses appear to be more dispersed in Houston relative to other cities, leading to
patterns of unusual mixing with other uses.  Some of the dispersion appears to be due
to the city?s annexation policies which seem to favor the acquisition of COM parcels
along arterial roadways, oftentimes far from the core area of the city (see, in
particular, the northwest portion of Houston in Figure 130 in Appendix A).  This,
however, does not explain some of the unusual mixing of COM with other uses
indicating that other factors, including ,perhaps, the city?s lack of zoning, could be
responsible for the dispersion of COM uses.
Principal Component Analysis
The preceding section highlighted several interesting patterns amongst the
study cities for each of the individual land use metrics.  However, it is hard to develop
a holistic view of the results across the hundreds of individual metrics given the large
amount of data.  Furthermore, whether an observation (e.g., a city like Houston) can
206
be considered an outlier is not always immediately apparent from looking at its values
for individual metrics. This is because it is theoretically possible for an observation to
be an outlier even if it is not an outlier amongst its component variables.311    To
reliably detect whether a city is an outlier in terms of land use relationships and
answer this study?s research question, one needs to employ robust multivariate
statistical methods like MacroPCA that consider the entirety of the dataset.
PCA based techniques are most applicable when there is correlation amongst
the variables in the dataset.  If correlation is limited, then the opportunity to reduce
the dataset to fewer principle components will also be limited.  To evaluate the degree
of correlation amongst metrics in the land use dataset, Pearson correlation coefficients
were computed amongst the 599 metrics to be used in the PCA.  The calculations
showed that 20.2% of the metric combinations exhibited a moderate or higher degree
of correlation (i.e., had a Pearson correlation coefficient greater than or equal to 0.3)
and 5.4% exhibited a high degree of correlation (i.e., had a Pearson correlation
coefficient greater than or equal to 0.5).  Given the relatively significant proportion of
metrics indicating moderate to high correlation, it was felt that PCA would, indeed,
be valuable for reducing the land use dataset into a few principal components for
multivariate outlier detection.
Prior to running MacroPCA, it is also best practice to ensure that none of the
input variables have (1) a skewed (non-normal [non-Gaussian]) distribution, (2) too
few unique values, or (3) too narrow a range of values.  Skewed variables should be
311 Rousseeuw and Van Den Bossche, ?Detecting Deviating Data Cells,? 136.
207
transformed to a more normal distribution prior to the analysis while those with too
few unique values or too narrow a range of values should be dropped from the
analysis.   To address the skew amongst the land use metrics, a transformation
algorithm was run in R (transfo in the cellWise package) that picked the optimal
transformation method (either the Box-Cox or Yeo-Johnson technique) for each
metric.  Different methods were found optimal for different fields so both techniques
were used on the dataset.  Data filtering was also conducted to identify the metrics
with too few unique values or too narrow a range of values.  The filtering identified
four metrics that had too few unique values and six metrics with too narrow a
range.312  These ten metrics were dropped from the PCA leaving a total of 589
metrics to be analyzed.
With this preprocessing complete, the dataset could now be analyzed using
MacroPCA.  When running MacroPCA, it is recommended that one do so in two
stages.  In the first stage, one leaves the number of principal components to retain
open (meaning that there could be, theoretically, as many principal components as
variables in the dataset).  Run in this mode, the software outputs a scree plot and
312 The four metrics with too few unique values were all within the family of neighborhood metrics
measuring the proportion of parcels that have zero, one, two, three, four, five, six, seven, eight, or nine
other land uses within 500 feet.  The specific metrics included the normalized proportions of (1) AG
parcels with eight other uses nearby, (2) MU parcels with zero other uses nearby, (3) PUB uses with
nine other uses nearby, and (4) TCU uses with nine other uses nearby.  There was somewhat more
variety to the six metrics found to have too small a range of values.  Three of the metrics were within
the same family as above including the normalized proportions of (1) MFR parcels with zero other
uses nearby, (2) MMR parcels with zero other uses nearby, and (3) MU parcels with one other use
nearby.  The other three metrics were all adjacency metrics.  Two of these were part of the proportion
of parcels bordering each land use family of metrics: specifically, the proportion of (1) MU parcels
bordering AG and (2) AG parcels bordering MU. The last metric with a small data range, the
proportion of AG perimeter bordering MU uses, was part of the proportion of shared parcel perimeter
bordering on each land use family of metrics.
208
cumulative percentage of variability explained by the components, both of which can
be used to select the number of principal components to retain.  In the second stage,
MacroPCA is run again with the selected number of principal components specified
in order to produce the final outputs.  For both runs, MacroPCA requires that a user
specify the fraction of observations that the algorithm should give full weight to
(alpha), a value that is allowed to range between 0.5 and one.  An initial alpha value
of one was selected for this analysis (sensitivity tests using alternate alpha values
were also conducted and are described later).
The initial MacroPCA run successfully reduced the dataset from 589 original
variables to only 49 principal components that cumulatively explained all of the
dataset variability.  While that was itself a significant simplification of the dataset, it
still constituted a significant number of variables that could be reduced further.  This
is because, as is typically the case, the first few principal components explain most of
the dataset variability whereas the other components explain just a small fraction.
This is illustrated by the scree plot in Figure 102 showing the eigenvalues for each
principal component.  An eigenvalue is a number representing the amount of variance
explained by each principal component; larger eigenvalues mean that principal
component explains a greater proportion of the variation in the dataset.  As one can
see, the first principal component explains, by far, the most variation in the dataset
(nearly 26%) with subsequent components explaining successively lesser amounts of
variation.
209
Figure 102: Scree Plot of the Initial MacroPCA Run
There is no consensus on how to decide on the number of principle
components to retain.  One method is to use the scree plot to find the component
number where there is a pronounced flattening of the values (i.e., retaining further
components explains limited additional variability).313  Other recommendations state
that the selected components should retain at least 70-80% of the variability in the
dataset with some even suggesting that values as low as 50% are adequate for social
science research.314  Another recommendation states that the number of observations
be at least five times the number of principal components to avoid the curse of
dimensionality.315  Given the debate on the subject, a best practice is to consider
multiple criteria when making the selection and to conduct sensitivity tests of the
results against different numbers of retained components.
313 University of California, ?Principal Components.?
314 University of California.
315 Hubert, Rousseeuw, and Vanden Branden, ?ROBPCA: A New Approach to Robust Principal
Component Analysis,? 69.
210
Considering both the scree plot and cumulative percentage of variability
explained, an initial selection of nine principal components was made for the analysis
(sensitivity tests retaining alternate numbers of components were also conducted and
are described later).  The first nine components explain nearly 70% of the variation in
the dataset (69.1%) and the scree plot levels off notably past this point.  Nine
components also ensure that the number of observations (50) exceeds five times the
number of principal components retained (9 * 5 = 45), thereby helping avoid the
curse of dimensionality.
MacroPCA was then run again using the same parameters as the initial run but
this time with nine principle components specified as opposed to letting this remain
open.  Factor scores were calculated for each city on each principal component and
are shown in Figure 103 through Figure 111.  These scores can be used, along with
the loadings of each variable on each principle component, to help explain the
meaning of each of the components (i.e., in essence, what aspects of the original 589
variables each of the nine components is picking up on).  That said, it is not always
possible to draw firm conclusions on each component?s meaning and there is a certain
degree of subjectivity involved in their interpretation.
The outputs suggest that the first principle component is picking up on the
degree of urbanization (i.e., density as being captured indirectly through parcel size)
of the various study cities (see Figure 103).  Larger scores seem to be associated with
newer, less dense cities (e.g., the Houston suburbs, Virginia Beach, Las Vegas,
Jacksonville, and Mesa) whereas smaller scores seem to be associated with older,
denser cities (e.g., New York, Boston, Philadelphia, and San Francisco).  There is a
211
clear regional trend to the scores with the cities of the Southwest and South Central
region tending to have larger (less urbanized) scores and cities in the Northeast and
Midwest tending to have smaller (more urbanized) scores.  Houston is in the middle
of the distribution.  Notably, it has the smallest (most urbanized) scores amongst its
peer cities in the South Central region.
The remaining principal components which, individually, explain much less
variation in the dataset, are more difficult to interpret.  However, several of these
components do pick up on distinct regional patterns in the metrics and/or patterns in
loadings amongst the land uses:
? Midwestern cities tend to have lower scores for the second principle
component (see Figure 104).  Several of the variables that load most
highly on this component relate to metrics involving AG uses
suggesting that this component may be picking up on patterns in AG
use relationships amongst the cities.  AG uses tend to be more
prevalent in Midwestern cities.  That said, the fifth principle
component (see Figure 107) also shows high loadings on AG-related
metrics and it exhibits no notable regional relationships.
? Scores on the third principle component (see Figure 105) show no
strong regional tendencies.  The loadings for this principle component,
however, tend to be highest for metrics related to COM uses
suggesting that this component may be picking up on patterns in COM
use relationships amongst the cities.
? For the fourth principle component (see Figure 106), cities in the
Southwest tend to have higher scores and cities in the South Central
region tending to have lower scores.  Several of the variables that load
most highly on this component relate to metrics involving VAC uses
suggesting that this component may be picking up on patterns in VAC
use relationships amongst the cities.  It is notable that VAC uses tend
to be more prevalent in Southwestern cities.
? There is a tendency for Southeastern cities to have higher scores on
principal component six (see Figure 108) and Southwestern cities to
have lower scores.  Several of the variables that load most highly on
this component relate to MU uses suggesting that this component may
be picking up on patterns in MU use relationships.
212
Figure 103: Scores for Principal Component One
Figure 104: Scores for Principal Component Two
213
Figure 105: Scores for Principal Component Three
Figure 106: Scores for Principal Component Four
214
Figure 107: Scores for Principal Component Five
Figure 108: Scores for Principal Component Six
215
Figure 109: Scores for Principal Component Seven
Figure 110: Scores for Principal Component Eight
216
Figure 111: Scores for Principal Component Nine
217
? Houston has the highest score for principal component seven (Figure
109).  Several of the variables that load most highly on this component
relate to SFDR uses suggesting that this component may be picking up
on patterns in SFDR use relationships.
? Scores on the ninth principle component (see Figure 111) show no
strong regional tendencies.  The loadings for this principle component,
however, tend to be highest for metrics related to TCU uses suggesting
that this component may be picking up on patterns in TCU use
relationships amongst the cities.
Principal component eight exhibited no discernable regional patterns in the scores or
amongst the land uses for the loadings.
Recall that an outlier map can be generated from PCA results to help identify
outlier observations: in this case, cities with land use relationships that stand out
relative to those in other cities.  The outlier map for the MacroPCA run is shown in
Figure 112.  Recall that the lower-left quadrant of the graphic encompasses regular
observations with outliers falling in the top-left (orthogonal outliers), top-right (bad
leverage points), or lower-right (good leverage points) quadrants.  From the figure, it
is clear that Houston, located deeply within the lower-left quadrant, is not considered
an outlier.  In fact, the city can be considered one of the most regular cases amongst
the study cities.  Houston has the lowest orthogonal distance to the PCA subspace
(i.e., the point is the lowest amongst all the cities) and a score distance very close to
the average (i.e., it is in the middle of the distribution horizontally).  This finding does
not support the alternative hypothesis of this study that land use relationships in
Houston are unique amongst large American cities.
218
Figure 112: MacroPCA Outlier Map316
Interestingly, one of the closer points to Houston in the dataset are the
Houston Suburbs indicating that land use relationships in these jurisdictions share
many characteristics.  That said, the two points closest to Houston are actually the
Midwestern cities of Columbus and Indianapolis.   What might all these cities have in
common?  Columbus and Indianapolis were, like Houston, originally founded in the
316 Explanation of abbreviations: CO Springs = Colorado Springs, EP = El Paso, KC = Kansas City,
LA = Los Angeles, LB = Long Beach, Mem = Memphis, NY = New York, OKC = Oklahoma City, SD
= San Diego, SF = San Francisco, VA Beach = Virginia Beach.
219
early 19th century and all expanded out onto a relatively flat agricultural landscape
devoid of prominent geographic features.   The land use maps shown in Appendix A
reveal a common spatial pattern amongst these cities.  All exhibit a fairly dense
(small parcel) urban core characterized by a fine-grained mixing of land uses.  In each
city, this urban core comprises around a quarter of the total city area.  In all three
cities, the core is surrounded by a more expansive coarser-grained suburban
landscape characterized by larger parcels and greater land use clustering.  This is true
of most of the study cities but the patterns of land use mixing amongst the three cities
are less regular than in several other cities.  For example, COM uses aren?t as neatly
clustered or linear as in several other cities.  Furthermore, annexation policies have
allowed all three cities to expand in some cases to the edge of the urban periphery
where the suburban landscape transitions into a mix of mainly SFDR, VAC, and AG
parcels.
While Houston is not considered an outlier, many other cities are, although
most of these just barely so.  All but one of these outliers is an orthogonal outlier with
the exception, Virginia Beach, being considered a bad leverage point.  The most
notable outlier amongst the study cities is Miami which has a very high orthogonal
distance from the PCA subspace.  There are several reasons why Miami is an outlier
including (1) several unusual relationships involving AG uses (likely influenced by
there being only a single AG parcel in the city); (2) a higher than typical proportion of
SFDR parcels near COM uses; (3) a lower tendency for SFDR uses to be near other
SFDR uses; (4) a tendency for COM and PUB uses to be closer to VAC uses; (5) a
higher degree of isolation of TCU, MU, and IND uses from other uses; (6) a higher
220
than typical distance between IND parcels and the nearest railroad; and, lastly, (7) a
higher amount of COM uses lining arterials than in other cities.   Other notable
orthogonal outliers include Philadelphia, Cleveland, and San Francisco.
In general, there is no strong regional pattern to the data.  That said, there does
appear to be some degree of clustering of Southwestern cities in the center of the
distribution indicating that many of them share common characteristics.  Some of
these common characteristics include (1) expansive areas of relatively ?pure? SFDR
land uses; (2) well-defined clusters/strips of COM, MFR, and IND uses; and (3) large
VAC tracts.
To explore whether the findings of the PCA are robust to the specifications
used, several sensitivity tests were performed that systematically varied the number of
principal components retained and the alpha value.  MacroPCA was run successively
retaining nine, ten, and 11 principal components and, for each number of retained
components, for alpha values of 0.5, 0.75, and one (recall that alpha must range
between 0.5 and one).  In all cases, Houston was never an outlier and retained its
position as being one of the most typical values amongst the study cities.  While some
outliers did change amongst the different specifications, Miami was always found to
be the largest outlier.  Virginia Beach, Cleveland, San Francisco, and Philadelphia
were also found to remain outliers across all the tests performed.
In conclusion, the individual land use metrics and the PCA results indicate
that Houston is not, on the whole, an outlier amongst large American cities with
respect to its land use relationships (although there are some exceptions, particularly
with respect to COM uses).  Houston cannot even be considered an outlier when
221
compared with its peer cities in the South Central region, including its own zoned
suburbs.  These findings argue in favor of retaining the null hypothesis that land use
relationships in Houston are not unique amongst large American cities, despite its
lack of zoning.
222
Chapter 6:  Conclusions and Next Steps
This chapter begins by attempting to draw some overarching conclusions from
the analysis.  Following this, some ideas for future research are offered that could be
used to expand and improve on this study.
Conclusions
A fundamental conclusion that can be drawn from this study is that, at a
macro (city-wide) level, Houston?s approach to managing land use relationships
(reliance on market forces, government supported private residential covenants, and
limited context-sensitive use prohibitions) appears capable of producing land use
relationship outcomes that do not differ significantly from those produced by zoning.
Thus, the analysis supports the observations from Siegan several decades ago that
land use patterns in Houston do not differ substantially from those in other large
American cities.  This lends credence to Siegan?s theory that built-in market
incentives exert a certain degree of control over land use relationships that largely
mirrors how American zoning has traditionally been practiced and that zoning in the
United States may, at some level, be redundant to market forces.  After all, if land use
relationships in Houston, a city that has never had zoning, are not substantively
different than in cities that have had zoning in place for around a century, then what
has zoning really achieved?
Of course, there are important caveats that must be kept in mind when
attempting to draw broader conclusions from this study.  Most importantly:
223
?    The analysis was not a pure comparison of a city that completely lacked
land use regulations to cities that were built out entirely under zoning.
As discussed at length earlier in this report, Houston is not entirely free
of land use regulation.  Likewise, substantial portions of the territories
of the other study cities were built out prior to zoning having been
instituted.  Thus, one should think of the results more as a comparison
amongst different approaches to managing land use as opposed to a
regulation versus no regulation comparison.
?     The conclusions are based solely on considering the spatial patterns
between land uses and their distribution with respect to transportation
infrastructure.  Several other very important elements of zoning codes
such as density, building heights, building setbacks, etc. were not
assessed as part of this study due to a paucity of data.  It could very well
be that Houston exhibits similar land use relationships to other large
American cities but differs substantially from them when considering
these other important dimensions of urban development patterns.
?    The results presented in this report are based on a city-wide view of the
outcomes.  There could very well be cases at the neighborhood scale
where the outcomes differ substantially from the city-wide values.
These may get ?washed out? in the city-wide report featured in this
study.
?     The study focused on large cities.  The findings may be different for
smaller cities, suburban communities, etc.
   These caveats aside, what can policymakers take from these results to
inform the ongoing debate about liberalizing various aspects of zoning policies?  On
the one hand, the results of this study suggest that some of the worst fears about land
use mixing from loosening zoning protections may not be realized.317  On the other
hand, the results also suggest that some of the hoped for changes to be brought about
through zoning reform (e.g., mixing of housing types in single-family neighborhoods)
may not be broadly achieved simply by removing zoning restrictions and that further
policy changes may be required (for example, limiting the ability of private covenants
317 Although, as noted, individual neighborhoods or cases may stand out from the city-wide pattern.
The importance of individual cases should not be underestimated as they can have an outsized
influence on public perceptions and, in turn, political decisions, even if they are rare exceptions to a
broader rule.  The aforementioned Ashby High Rise case in Houston is a prime example of this.
224
to restrict housing types).  While this study cannot definitively answer the policy
question on whether zoning rules should be relaxed or even abolished altogether,
Houston does suggest that there may be room for some degree of liberalization
without dramatic adverse effects.  Further research will be needed to develop more
specific policy recommendations.  The next section discusses some potentially
helpful ideas.
Next Steps
This section presents a series of research ideas to expand on this study and
address some of its limitations. The ideas are broken down into two groups: (1) those
that specifically address how zoning influences these relationships and (2) those that
would enhance the general understanding of land use relationships within urbanized
areas.  Ideas that specifically address how zoning influences urban land use
relationships include:
? Conduct in-depth qualitative research to further describe
Houston?s approach to land use management and understand how
it can create land use outcomes similar to traditional zoning:
Rigorous qualitative research into the land development process in
Houston is needed to develop a better understanding of how land use
patterns in Houston are determined.  This research could entail
interviews with city staff, real estate professionals, lenders, property
owners, neighborhood groups, and others.  Developing a better
understanding of the city?s system of private covenants and their
enforcement would be particularly beneficial.  An exploration of the
customs and practices amongst land developers could also be quite
revealing (especially with regards to what degree they consider
existing nearby land uses when searching for sites/uses to develop).
Case studies on specific projects and the evolution of neighborhoods
over time could be used to add additional depth.  The findings could
ultimately help to explain exactly how land use development patterns
in Houston can come to replicate those observed in other large
American cities.  This research could also be used to better understand
and explain exceptions to this broader trend (e.g., with COM uses).
225
? Conduct in-depth qualitative research to better understand the
outliers in this analysis: The PCA revealed several cities with zoning
that were outliers (e.g., Miami, Philadelphia, etc.).  Rigorous
qualitative research could be undertaken to gain a better understanding
of why land use patterns in these cities are unique.  Are these patterns
a result of specific zoning policies or a legacy of distinctive pre-zoning
land use patterns?  If a product of policy, why were those policies
instituted?  What have been the implications of those policies?
Historical analyses, interviews, and case studies could all help to shed
light on these potentially interesting questions.
? Break out the land use metrics for Houston by covenant protected
and non-covenant protected areas: One of the key caveats
mentioned above was that this study, being done on a city-wide basis,
could not address to what degree the Houston?s support for private
covenants might be responsible for it having similar metrics to zoned
cities.  Were the results from the large proportion of covenant-
protected areas swamping unusual results for the non-covenant
protected areas?   It would be useful to understand whether the same
outcomes for the metrics could be achieved without covenants.
Breaking out the results in Houston by whether an area is protected by
covenants could shed light on this.  Conceptually, this is a relatively
simple task, however, it would require a laborious effort to research,
document, and map the complex landscape of private covenants within
the city.
? Break out the land use metrics for all cities by initial year of
neighborhood development and whether it occurred pre- or post-
zoning: This follow-on research would involve reporting out the land
use metrics by the initial year each neighborhood was developed and
determining whether that was pre- or post-zoning in each city.  It
might be useful to also consider the average age of structures in the
neighborhood to account for redevelopment.  This cross-sectional
study might reveal interesting patterns within and amongst the study
cities with respect to the era of development.
? Conduct a longitudinal study of city-wide land use metrics pre-
and post-zoning: This study used a cross-sectional approach to
investigating land use relationships amongst several cities and
compared the results to a city without zoning to determine if its lack of
zoning resulted in radically different patterns.  A more definitive
analysis of zoning?s potential impacts on various cities could be
achieved by taking a longitudinal approach to the analysis and
analyzing how land use metrics evolved in each city pre- and post-
zoning.  One of the biggest challenges with implementing this research
design would be generating historic parcel level land use data
stretching back prior to the advent of zoning in the early 20th century.
This data is available in Sanborn fire insurance maps but these are
currently available only as raster-based scans of hard copy maps.
226
Vectorizing the data and assigning it land use attributes would need to
be done to enable the calculation of historical land use metrics akin to
those used in this study.  Although modern vectorization technologies
may be able to speed this process up, this would likely be a large
undertaking, even for just one city.
? Develop new metrics for capturing elements of zoning other than
land use relationships: As noted above, this study only considered
land use relationships; an important facet of zoning policy but not the
only one.  Other metrics could be developed for each study city to look
at the relationships between parcels with respect to density, building
heights, building setbacks, vegetal screens, etc.  The biggest challenge
for doing this would be data availability.  Parcel level household and
employment density information is not widely available but could
likely be estimated using a combination of sources.  Building footprint
data, which could be used to obtain setbacks and, possibly, building
heights, has become widely available in the past few years.  However,
the accuracy of much of the publicly available data vis-?-vis the parcel
data may not yet be at the level required to measure setbacks from the
parcel line.  First return light detection and ranging (LiDAR) data
might provide a useful data source to obtain sufficiently precise
building footprints and heights along with vegetal buffers.  Plans for a
coordinated national effort to collect such data are underway.
Ideas that would further understanding of urban land use relationships
generally include:
? Conduct additional statistical exploration to help explain the
observed patterns in the metrics amongst the study cities and their
geographic regions: Further statistical analyses could be performed to
help identify and explain patterns amongst the study cities.  For
example, the principal component scores along with other variables
like date of city founding, date of zoning adoption, fraction of the city
developed post-zoning, geographic region, etc. could be used in a
regression analysis to attempt to explain the positioning of various
cities on the outlier map in Figure 112.
? Break out the land use metrics for all cities by different socio-
economic groups: Another interesting analysis that could be run with
the dataset would involve combining the land use metrics dataset with
census data to break out the metrics by different socioeconomic groups
(e.g., race, ethnicity, income, etc.).  Such an analysis might reveal
interesting differences in land use relationships amongst demographic
groups within and among cities that could inform future policy
debates; an important consideration given recent interest in equity.
227
? Expand the work to additional cities: The 49 largest cities that had
publicly available parcel level land use data at reasonable cost were
included in this study (along with Houston?s zoned suburbs).  This
captures the largest cities in the United States but future efforts could
expand the analysis to smaller cities and additional suburban
jurisdictions.  To the extent that parcel level land use data is available,
the analysis could also be expanded outside the United States to
investigate differences in patterns of land use relationships globally.
? Increase the number/detail of land use classes used for the metrics:
This study used 10 basic land use classes (plus the UNKN class) to
describe the plethora of different individual land uses that comprise the
urban landscape.  This high level classification was necessary to create
a common classification system across the disparate local systems
used in each of the study cities.  It was, in essence, a lowest common
denominator across the various systems.  However, several of the
study cities provided more detailed land use descriptions (e.g., for the
COM use, breaking it out into office buildings, gas stations, etc.).
Thus, a separate more detailed classification could be developed and
used to run an analysis for the subset of cities that have the data.  This
would provide an even richer and deeper understanding of land use
relationships amongst these cities.
? Set up a continuous monitoring and reporting system to re-
calculate the metrics on a regular basis as land uses evolve and
new parcel data becomes available: This study constituted an initial
inquiry into urban land use relationships for purposes of a static -
comparison of the study cities at a single point in time.  Land uses are,
however, constantly evolving and parcel data is continuously being
updated to reflect this.  This presents the opportunity to create a
reporting system using the metrics described in this study (and others)
to track and compare, in detail, how cities are evolving.  Are all cities
evolving in the same way or are some evolving differently than others?
Are different parts of cities evolving in different ways from others?  A
system set up to continuously monitor and report out changes in land
use relationship metrics (both for all of the parcels and amongst only
those that changed) through a dashboard type interface could help
answer these questions and many more, giving the planning field and
practitioners a deeper understanding of how urban form is changing
over time.
This long list of research ideas makes clear that there is still much work to be
done to better understand urban development patterns.   While much focus has been
given to specific topics like sprawl, this study and these research ideas demonstrate
228
that there are many insights to be gained from understanding land use patterns within
already developed areas, not just on the urban periphery.  Such knowledge is arguably
elemental to the field of urban planning and zoning practice yet it has been strikingly
absent from the discourse, both in the academy and in practice.  While challenges
remain, advancements in data availability, GIS technology, and processing power
provide the tools needed to answer questions that heretofore might have seemed too
complex or too big to answer.   Whereas just a few years ago it was lamented in the
literature that, ?a rigorous comparison of land-use patterns [between Houston and
other cities] may be impossible,?318 it is now done.  What more could be
accomplished in the years ahead?
318 O?Sullivan, Urban Economics, 239.
229
Appendix A: Land Use Maps
This appendix shows the parcel-level land use data used in the calculation of
the land use metrics for each study city.  The maps are presented in alphabetical order
by city name.  The data are the result of the reclassification routine and topological
corrections described in Chapter 4.  To aid in the visualization of land use patterns,
the boundaries of individual parcels are not shown on these maps (including the
boundaries at the scale of these maps would make them too difficult to read).  The
land use codes used on all the maps correspond to those used throughout the study.
For ease of reference, these are:
? SFDR: Single-family detached residential
? MMR: Missing middle residential
? MFR: Multi-family residential
? COM: Commercial
? MU: Mixed use
? PUB: Public/institutional/cultural
? IND: Industrial
? TCU: Transportation/communications/utilities
? VAC: Vacant/undeveloped/open space
? AG: Agriculture
? UNKN: Unknown
230
Figure 113: Land Use in Albuquerque
231
Figure 114: Land Use in Arlington
232
Figure 115: Land Use in Atlanta
233
Figure 116: Land Use in Austin
234
Figure 117: Land Use in Baltimore
235
Figure 118: Land Use in Boston
236
Figure 119: Land Use in Charlotte
237
Figure 120: Land Use in Chicago
238
Figure 121: Land Use in Cleveland
239
Figure 122: Land Use in Colorado Springs
240
Figure 123: Land Use in Columbus
241
Figure 124: Land Use in Dallas
242
Figure 125: Land Use in Denver
243
Figure 126: Land Use in Detroit
244
Figure 127: Land Use in El Paso
245
Figure 128: Land Use in Fort Worth
246
Figure 129: Land Use in Fresno
247
Figure 130: Land Use in Houston
248
Figure 131: Land Use in Houston's Zoned Suburbs
249
Figure 132: Land Use in Indianapolis
250
Figure 133: Land Use in Jacksonville
251
Figure 134: Land Use in Kansas City
252
Figure 135: Land Use in Las Vegas
253
Figure 136: Land Use in Long Beach
254
Figure 137: Land Use in Los Angeles
255
Figure 138: Land Use in Louisville
256
Figure 139: Land Use in Memphis
257
Figure 140: Land Use in Mesa
258
Figure 141: Land Use in Miami
259
Figure 142: Land Use in Milwaukee
260
Figure 143: Land Use in Minneapolis
261
Figure 144: Land Use in Nashville
262
Figure 145: Land Use in New York
263
Figure 146: Land Use in Oakland
264
Figure 147: Land Use in Oklahoma City
265
Figure 148: Land Use in Omaha
266
Figure 149: Land Use in Philadelphia
267
Figure 150: Land Use in Phoenix
268
Figure 151: Land Use in Portland
269
Figure 152: Land Use in Raleigh
270
Figure 153: Land Use in Sacramento
271
Figure 154: Land Use in San Antonio
272
Figure 155: Land Use in San Diego
273
Figure 156: Land Use in San Francisco
274
Figure 157: Land Use in Seattle
275
Figure 158: Land Use in Tucson
276
Figure 159: Land Use in Tulsa
277
Figure 160: Land Use in Virginia Beach
278
Figure 161: Land Use in Washington
279
Figure 162: Land Use in Wichita
280
Appendix B: Bar Charts Showing the Proportion of Shared Parcel Perimeter Bordering on
Each Land Use
This appendix provides bar charts showing the proportion of shared parcel perimeter bordering on each land use.  For ease of
reference, an index with the page number of each land use combination?s chart is provided in Table 5.
Table 5: Bar Chart Index, Proportion of Shared Parcel Perimeter Bordering on Each Land Use
Bordering?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 282 Pg. 282 Pg. 283 Pg. 283 Pg. 284 Pg. 284 Pg. 285 Pg. 285 Pg. 286 Pg. 286 Pg. 287
COM Pg. 287 Pg. 288 Pg. 288 Pg. 289 Pg. 289 Pg. 290 Pg. 290 Pg. 291 Pg. 291 Pg. 292 Pg. 292
IND Pg. 293 Pg. 293 Pg. 294 Pg. 294 Pg. 295 Pg. 295 Pg. 296 Pg. 296 Pg. 297 Pg. 297 Pg. 298
MMR Pg. 298 Pg. 299 Pg. 299 Pg. 300 Pg. 300 Pg. 301 Pg. 301 Pg. 302 Pg. 302 Pg. 303 Pg. 303
MU Pg. 304 Pg. 304 Pg. 305 Pg. 305 Pg. 306 Pg. 306 Pg. 307 Pg. 307 Pg. 308 Pg. 308 Pg. 309
MFR Pg. 309 Pg. 310 Pg. 310 Pg. 311 Pg. 311 Pg. 312 Pg. 312 Pg. 313 Pg. 313 Pg. 314 Pg. 314
PUB Pg. 315 Pg. 315 Pg. 316 Pg. 316 Pg. 317 Pg. 317 Pg. 318 Pg. 318 Pg. 319 Pg. 319 Pg. 320
SFDR Pg. 320 Pg. 321 Pg. 321 Pg. 322 Pg. 322 Pg. 323 Pg. 323 Pg. 324 Pg. 324 Pg. 325 Pg. 325
TCU Pg. 326 Pg. 326 Pg. 327 Pg. 327 Pg. 328 Pg. 328 Pg. 329 Pg. 329 Pg. 330 Pg. 330 Pg. 331
UNKN
VAC Pg. 331 Pg. 332 Pg. 332 Pg. 333 Pg. 333 Pg. 334 Pg. 334 Pg. 335 Pg. 335 Pg. 336 Pg. 336
281
 % Shared Parcel Perimeter of?
Figure 163: Proportion of Shared AG Parcel Perimeter Bordering on AG Uses
Figure 164: Proportion of Shared AG Parcel Perimeter Bordering on COM Uses
282
Figure 165: Proportion of Shared AG Parcel Perimeter Bordering on IND Uses
Figure 166: Proportion of Shared AG Parcel Perimeter Bordering on MMR Uses
283
Figure 167: Proportion of Shared AG Parcel Perimeter Bordering on MU Uses
Figure 168: Proportion of Shared AG Parcel Perimeter Bordering on MFR Uses
284
Figure 169: Proportion of Shared AG Parcel Perimeter Bordering on PUB Uses
Figure 170: Proportion of Shared AG Parcel Perimeter Bordering on SFDR Uses
285
Figure 171: Proportion of Shared AG Parcel Perimeter Bordering on TCU Uses
Figure 172: Proportion of Shared AG Parcel Perimeter Bordering on UNKN Uses
286
Figure 173: Proportion of Shared AG Parcel Perimeter Bordering on VAC Uses
Figure 174: Proportion of Shared COM Parcel Perimeter Bordering on AG Uses
287
Figure 175: Proportion of Shared COM Parcel Perimeter Bordering on COM Uses
Figure 176: Proportion of Shared COM Parcel Perimeter Bordering on IND Uses
288
Figure 177: Proportion of Shared COM Parcel Perimeter Bordering on IND Uses
Figure 178: Proportion of Shared COM Parcel Perimeter Bordering on MU Uses
289
Figure 179: Proportion of Shared COM Parcel Perimeter Bordering on MFR Uses
Figure 180: Proportion of Shared COM Parcel Perimeter Bordering on PUB Uses
290
Figure 181: Proportion of Shared COM Parcel Perimeter Bordering on SFDR Uses
Figure 182: Proportion of Shared COM Parcel Perimeter Bordering on TCU Uses
291
Figure 183: Proportion of Shared COM Parcel Perimeter Bordering on UNKN Uses
Figure 184: Proportion of Shared COM Parcel Perimeter Bordering on VAC Uses
292
Figure 185: Proportion of Shared IND Parcel Perimeter Bordering on AG Uses
Figure 186: Proportion of Shared IND Parcel Perimeter Bordering on COM Uses
293
Figure 187: Proportion of Shared IND Parcel Perimeter Bordering on IND Uses
Figure 188: Proportion of Shared IND Parcel Perimeter Bordering on MMR Uses
294
Figure 189: Proportion of Shared IND Parcel Perimeter Bordering on MU Uses
Figure 190: Proportion of Shared IND Parcel Perimeter Bordering on MFR Uses
295
Figure 191: Proportion of Shared IND Parcel Perimeter Bordering on PUB Uses
Figure 192: Proportion of Shared IND Parcel Perimeter Bordering on SFDR Uses
296
Figure 193: Proportion of Shared IND Parcel Perimeter Bordering on TCU Uses
Figure 194: Proportion of Shared IND Parcel Perimeter Bordering on UNKN Uses
297
Figure 195: Proportion of Shared IND Parcel Perimeter Bordering on VAC Uses
Figure 196: Proportion of Shared MMR Parcel Perimeter Bordering on AG Uses
298
Figure 197: Proportion of Shared MMR Parcel Perimeter Bordering on COM Uses
Figure 198: Proportion of Shared MMR Parcel Perimeter Bordering on IND Uses
299
Figure 199: Proportion of Shared MMR Parcel Perimeter Bordering on MMR Uses
Figure 200: Proportion of Shared MMR Parcel Perimeter Bordering on MU Uses
300
Figure 201: Proportion of Shared MMR Parcel Perimeter Bordering on MFR Uses
Figure 202: Proportion of Shared MMR Parcel Perimeter Bordering on PUB Uses
301
Figure 203: Proportion of Shared MMR Parcel Perimeter Bordering on SFDR Uses
Figure 204: Proportion of Shared MMR Parcel Perimeter Bordering on TCU Uses
302
Figure 205: Proportion of Shared MMR Parcel Perimeter Bordering on UNKN Uses
Figure 206: Proportion of Shared MMR Parcel Perimeter Bordering on VAC Uses
303
Figure 207: Proportion of Shared MU Parcel Perimeter Bordering on AG Uses
Figure 208: Proportion of Shared MU Parcel Perimeter Bordering on COM Uses
304
Figure 209: Proportion of Shared MU Parcel Perimeter Bordering on IND Uses
Figure 210: Proportion of Shared MU Parcel Perimeter Bordering on MMR Uses
305
Figure 211: Proportion of Shared MU Parcel Perimeter Bordering on MU Uses
Figure 212: Proportion of Shared MU Parcel Perimeter Bordering on MFR Uses
306
Figure 213: Proportion of Shared MU Parcel Perimeter Bordering on PUB Uses
Figure 214: Proportion of Shared MU Parcel Perimeter Bordering on SFDR Uses
307
Figure 215: Proportion of Shared MU Parcel Perimeter Bordering on TCU Uses
Figure 216: Proportion of Shared MU Parcel Perimeter Bordering on UNKN Uses
308
Figure 217: Proportion of Shared MU Parcel Perimeter Bordering on VAC Uses
Figure 218: Proportion of Shared MFR Parcel Perimeter Bordering on AG Uses
309
Figure 219: Proportion of Shared MFR Parcel Perimeter Bordering on COM Uses
Figure 220: Proportion of Shared MFR Parcel Perimeter Bordering on IND Uses
310
Figure 221: Proportion of Shared MFR Parcel Perimeter Bordering on MMR Uses
Figure 222: Proportion of Shared MFR Parcel Perimeter Bordering on MU Uses
311
Figure 223: Proportion of Shared MFR Parcel Perimeter Bordering on MFR Uses
Figure 224: Proportion of Shared MFR Parcel Perimeter Bordering on PUB Uses
312
Figure 225: Proportion of Shared MFR Parcel Perimeter Bordering on SFDR Uses
Figure 226: Proportion of Shared MFR Parcel Perimeter Bordering on TCU Uses
313
Figure 227: Proportion of Shared MFR Parcel Perimeter Bordering on UNKN Uses
Figure 228: Proportion of Shared MFR Parcel Perimeter Bordering on VAC Uses
314
Figure 229: Proportion of Shared PUB Parcel Perimeter Bordering on AG Uses
Figure 230: Proportion of Shared PUB Parcel Perimeter Bordering on COM Uses
315
Figure 231: Proportion of Shared PUB Parcel Perimeter Bordering on IND Uses
Figure 232: Proportion of Shared PUB Parcel Perimeter Bordering on MMR Uses
316
Figure 233: Proportion of Shared PUB Parcel Perimeter Bordering on MU Uses
Figure 234: Proportion of Shared PUB Parcel Perimeter Bordering on MFR Uses
317
Figure 235: Proportion of Shared PUB Parcel Perimeter Bordering on PUB Uses
Figure 236: Proportion of Shared PUB Parcel Perimeter Bordering on SFDR Uses
318
Figure 237: Proportion of Shared PUB Parcel Perimeter Bordering on TCU Uses
Figure 238: Proportion of Shared PUB Parcel Perimeter Bordering on UNKN Uses
319
Figure 239: Proportion of Shared PUB Parcel Perimeter Bordering on VAC Uses
Figure 240: Proportion of Shared SFDR Parcel Perimeter Bordering on AG Uses
320
Figure 241: Proportion of Shared SFDR Parcel Perimeter Bordering on COM Uses
Figure 242: Proportion of Shared SFDR Parcel Perimeter Bordering on IND Uses
321
Figure 243: Proportion of Shared SFDR Parcel Perimeter Bordering on MMR Uses
Figure 244: Proportion of Shared SFDR Parcel Perimeter Bordering on MU Uses
322
Figure 245: Proportion of Shared SFDR Parcel Perimeter Bordering on MFR Uses
Figure 246: Proportion of Shared SFDR Parcel Perimeter Bordering on PUB Uses
323
Figure 247: Proportion of Shared SFDR Parcel Perimeter Bordering on SFDR Uses
Figure 248: Proportion of Shared SFDR Parcel Perimeter Bordering on TCU Uses
324
Figure 249: Proportion of Shared SFDR Parcel Perimeter Bordering on UNKN Uses
Figure 250: Proportion of Shared SFDR Parcel Perimeter Bordering on VAC Uses
325
Figure 251: Proportion of Shared TCU Parcel Perimeter Bordering on AG Uses
Figure 252: Proportion of Shared TCU Parcel Perimeter Bordering on COM Uses
326
Figure 253: Proportion of Shared TCU Parcel Perimeter Bordering on IND Uses
Figure 254: Proportion of Shared TCU Parcel Perimeter Bordering on MMR Uses
327
Figure 255: Proportion of Shared TCU Parcel Perimeter Bordering on MU Uses
Figure 256: Proportion of Shared TCU Parcel Perimeter Bordering on MFR Uses
328
Figure 257: Proportion of Shared TCU Parcel Perimeter Bordering on PUB Uses
Figure 258: Proportion of Shared TCU Parcel Perimeter Bordering on SFDR Uses
329
Figure 259: Proportion of Shared TCU Parcel Perimeter Bordering on TCU Uses
Figure 260: Proportion of Shared TCU Parcel Perimeter Bordering on UNKN Uses
330
Figure 261: Proportion of Shared TCU Parcel Perimeter Bordering on VAC Uses
Figure 262: Proportion of Shared VAC Parcel Perimeter Bordering on AG Uses
331
Figure 263: Proportion of Shared VAC Parcel Perimeter Bordering on COM Uses
Figure 264: Proportion of Shared VAC Parcel Perimeter Bordering on IND Uses
332
Figure 265: Proportion of Shared VAC Parcel Perimeter Bordering on MMR Uses
Figure 266: Proportion of Shared VAC Parcel Perimeter Bordering on MU Uses
333
Figure 267: Proportion of Shared VAC Parcel Perimeter Bordering on MFR Uses
Figure 268: Proportion of Shared VAC Parcel Perimeter Bordering on PUB Uses
334
Figure 269: Proportion of Shared VAC Parcel Perimeter Bordering on SFDR Uses
Figure 270: Proportion of Shared VAC Parcel Perimeter Bordering on TCU Uses
335
Figure 271: Proportion of Shared VAC Parcel Perimeter Bordering on UNKN Uses
Figure 272: Proportion of Shared VAC Parcel Perimeter Bordering on VAC Uses
336
Appendix C: Bar Charts Showing the Normalized Proportion of Shared Parcel Perimeter
Bordering on Each Land Use
This appendix provides bar charts showing normalized values for the proportion of shared parcel perimeter bordering on each
land use.  For ease of reference, an index with the page number of each land use combination?s chart is provided in Table 6.
Table 6: Bar Chart Index, Normalized Proportion of Shared Parcel Perimeter Bordering on Each Land Use
Bordering?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 338 Pg. 338 Pg. 339 Pg. 339 Pg. 340 Pg. 340 Pg. 341 Pg. 341 Pg. 342 Pg. 342 Pg. 343
COM Pg. 343 Pg. 344 Pg. 344 Pg. 345 Pg. 345 Pg. 346 Pg. 346 Pg. 347 Pg. 347 Pg. 348
IND Pg. 348 Pg. 349 Pg. 349 Pg. 350 Pg. 350 Pg. 351 Pg. 351 Pg. 352 Pg. 352
MMR Pg. 353 Pg. 353 Pg. 354 Pg. 354 Pg. 355 Pg. 355 Pg. 356 Pg. 356
MU Pg. 357 Pg. 357 Pg. 358 Pg. 358 Pg. 359 Pg. 359 Pg. 360
MFR Pg. 360 Pg. 361 Pg. 361 Pg. 362 Pg. 362 Pg. 363
PUB Pg. 363 Pg. 364 Pg. 364 Pg. 365 Pg. 365
SFDR Pg. 366 Pg. 366 Pg. 367 Pg. 367
TCU Pg. 368 Pg. 368 Pg. 369
UNKN Pg. 369
VAC Pg. 370
337
% Shared Parcel Perimeter of?
Figure 273: Proportion of Shared AG Parcel Perimeter Bordering on AG Uses (Normalized)
Figure 274: Proportion of Shared AG/COM Parcel Perimeter Bordering on COM/AG Uses (Normalized)
338
Figure 275: Proportion of Shared AG/IND Parcel Perimeter Bordering on IND/AG Uses (Normalized)
Figure 276: Proportion of Shared AG/MMR Parcel Perimeter Bordering on MMR/AG Uses (Normalized)
339
Figure 277: Proportion of Shared AG/MU Parcel Perimeter Bordering on MU/AG Uses (Normalized)
Figure 278: Proportion of Shared AG/MFR Parcel Perimeter Bordering on MFR/AG Uses (Normalized)
340
Figure 279: Proportion of Shared AG/PUB Parcel Perimeter Bordering on PUB/AG Uses (Normalized)
Figure 280: Proportion of Shared AG/SFDR Parcel Perimeter Bordering on SFDR/AG Uses (Normalized)
341
Figure 281: Proportion of Shared AG/TCU Parcel Perimeter Bordering on TCU/AG Uses (Normalized)
Figure 282: Proportion of Shared AG/UNKN Parcel Perimeter Bordering on UNKN/AG Uses (Normalized)
342
Figure 283: Proportion of Shared AG/VAC Parcel Perimeter Bordering on VAC/AG Uses (Normalized)
Figure 284: Proportion of Shared COM Parcel Perimeter Bordering on COM Uses (Normalized)
343
Figure 285: Proportion of Shared COM/IND Parcel Perimeter Bordering on IND/COM Uses (Normalized)
Figure 286: Proportion of Shared COM/MMR Parcel Perimeter Bordering on MMR/COM Uses (Normalized)
344
Figure 287: Proportion of Shared COM/MU Parcel Perimeter Bordering on MU/COM Uses (Normalized)
Figure 288: Proportion of Shared COM/MFR Parcel Perimeter Bordering on MFR/COM Uses (Normalized)
345
Figure 289: Proportion of Shared COM/PUB Parcel Perimeter Bordering on PUB/COM Uses (Normalized)
Figure 290: Proportion of Shared COM/SFDR Parcel Perimeter Bordering on SFDR/COM Uses (Normalized)
346
Figure 291: Proportion of Shared COM/TCU Parcel Perimeter Bordering on TCU/COM Uses (Normalized)
Figure 292: Proportion of Shared COM/UNKN Parcel Perimeter Bordering on UNKN/COM Uses (Normalized)
347
Figure 293: Proportion of Shared COM/VAC Parcel Perimeter Bordering on VAC/COM Uses (Normalized)
Figure 294: Proportion of Shared IND Parcel Perimeter Bordering on IND Uses (Normalized)
348
Figure 295: Proportion of Shared IND/MMR Parcel Perimeter Bordering on MMR/IND Uses (Normalized)
Figure 296: Proportion of Shared IND/MU Parcel Perimeter Bordering on MU/IND Uses (Normalized)
349
Figure 297: Proportion of Shared IND/MFR Parcel Perimeter Bordering on MFR/IND Uses (Normalized)
Figure 298: Proportion of Shared IND/PUB Parcel Perimeter Bordering on PUB/IND Uses (Normalized)
350
Figure 299: Proportion of Shared IND/SFDR Parcel Perimeter Bordering on SFDR/IND Uses (Normalized)
Figure 300: Proportion of Shared IND/TCU Parcel Perimeter Bordering on TCU/IND Uses (Normalized)
351
Figure 301: Proportion of Shared IND/UNKN Parcel Perimeter Bordering on UNKN/IND Uses (Normalized)
Figure 302: Proportion of Shared IND/VAC Parcel Perimeter Bordering on VAC/IND Uses (Normalized)
352
Figure 303: Proportion of Shared MMR Parcel Perimeter Bordering on MMR Uses (Normalized)
Figure 304: Proportion of Shared MMR/MU Parcel Perimeter Bordering on MU/MMR Uses (Normalized)
353
Figure 305: Proportion of Shared MMR/MFR Parcel Perimeter Bordering on MFR/MMR Uses (Normalized)
Figure 306: Proportion of Shared MMR/PUB Parcel Perimeter Bordering on PUB/MMR Uses (Normalized)
354
Figure 307: Proportion of Shared MMR/SFDR Parcel Perimeter Bordering on SFDR/MMR Uses (Normalized)
Figure 308: Proportion of Shared MMR/TCU Parcel Perimeter Bordering on TCU/MMR Uses (Normalized)
355
Figure 309: Proportion of Shared MMR/UNKN Parcel Perimeter Bordering on UNIKN/MMR Uses (Normalized)
Figure 310: Proportion of Shared MMR/VAC Parcel Perimeter Bordering on VAC/MMR Uses (Normalized)
356
Figure 311: Proportion of Shared MU Parcel Perimeter Bordering on MU Uses (Normalized)
Figure 312: Proportion of Shared MU/MFR Parcel Perimeter Bordering on MFR/MU Uses (Normalized)
357
Figure 313: Proportion of Shared MU/PUB Parcel Perimeter Bordering on PUB/MU Uses (Normalized)
Figure 314: Proportion of Shared MU/SFDR Parcel Perimeter Bordering on SFDR/MU Uses (Normalized)
358
Figure 315: Proportion of Shared MU/TCU Parcel Perimeter Bordering on TCU/MU Uses (Normalized)
Figure 316: Proportion of Shared MU/UNKN Parcel Perimeter Bordering on UNKN/MU Uses (Normalized)
359
Figure 317: Proportion of Shared MU/VAC Parcel Perimeter Bordering on VAC/MU Uses (Normalized)
Figure 318: Proportion of Shared MFR Parcel Perimeter Bordering on MFR Uses (Normalized)
360
Figure 319: Proportion of Shared MFR/PUB Parcel Perimeter Bordering on PUB/MFR Uses (Normalized)
Figure 320: Proportion of Shared MFR/SFDR Parcel Perimeter Bordering on SFDR/MFR Uses (Normalized)
361
Figure 321: Proportion of Shared MFR/TCU Parcel Perimeter Bordering on TCU/MFR Uses (Normalized)
Figure 322: Proportion of Shared MFR/UNKN Parcel Perimeter Bordering on UNKN/MFR Uses (Normalized)
362
Figure 323: Proportion of Shared MFR/VAC Parcel Perimeter Bordering on VAC/MFR Uses (Normalized)
Figure 324: Proportion of Shared PUB Parcel Perimeter Bordering on PUB Uses (Normalized)
363
Figure 325: Proportion of Shared PUB/SFDR Parcel Perimeter Bordering on SFDR/PUB Uses (Normalized)
Figure 326: Proportion of Shared PUB/TCU Parcel Perimeter Bordering on TCU/PUB Uses (Normalized)
364
Figure 327: Proportion of Shared PUB/UNKN Parcel Perimeter Bordering on UNKN/PUB Uses (Normalized)
Figure 328: Proportion of Shared PUB/VAC Parcel Perimeter Bordering on VAC/PUB Uses (Normalized)
365
Figure 329: Proportion of Shared SFDR Parcel Perimeter Bordering on SFDR Uses (Normalized)
Figure 330: Proportion of Shared SFDR/TCU Parcel Perimeter Bordering on TCU/SFDR Uses (Normalized)
366
Figure 331: Proportion of Shared SFDR/UNKN Parcel Perimeter Bordering on UNKN/SFDR Uses (Normalized)
Figure 332: Proportion of Shared SFDR/VAC Parcel Perimeter Bordering on VAC/SFDR Uses (Normalized)
367
Figure 333: Proportion of Shared TCU Parcel Perimeter Bordering on TCU Uses (Normalized)
Figure 334: Proportion of Shared TCU/UNKN Parcel Perimeter Bordering on UNKN/TCU Uses (Normalized)
368
Figure 335: Proportion of Shared TCU/VAC Parcel Perimeter Bordering on VAC/TCU Uses (Normalized)
Figure 336: Proportion of Shared VAC/UNKN Parcel Perimeter Bordering on UNKN/VAC Uses (Normalized)
369
Figure 337: Proportion of Shared VAC Parcel Perimeter Bordering on VAC Uses (Normalized)
370
Appendix D: Bar Charts Showing the Proportion of Parcels in Each Land Use Class Bordering
Each Land Use
This appendix provides bar charts showing the proportion of parcels in each land use class bordering each land use.  For ease
of reference, an index with the page number of each land use combination?s chart is provided in Table 7.
Table 7: Bar Chart Index, Proportion of Parcels in Each Land Use Class Bordering Each Land Use
% of Parcels with Land Use?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 372 Pg. 372 Pg. 373 Pg. 373 Pg. 374 Pg. 374 Pg. 375 Pg. 375 Pg. 376 Pg. 376
COM Pg. 377 Pg. 377 Pg. 378 Pg. 378 Pg. 379 Pg. 379 Pg. 380 Pg. 380 Pg. 381 Pg. 381
IND Pg. 382 Pg. 382 Pg. 383 Pg. 383 Pg. 384 Pg. 384 Pg. 385 Pg. 385 Pg. 386 Pg. 386
MMR Pg. 387 Pg. 387 Pg. 388 Pg. 388 Pg. 389 Pg. 389 Pg. 390 Pg. 390 Pg. 391 Pg. 391
MU Pg. 392 Pg. 392 Pg. 393 Pg. 393 Pg. 394 Pg. 394 Pg. 395 Pg. 395 Pg. 396 Pg. 396
MFR Pg. 397 Pg. 397 Pg. 398 Pg. 398 Pg. 399 Pg. 399 Pg. 400 Pg. 400 Pg. 401 Pg. 401
PUB Pg. 402 Pg. 402 Pg. 403 Pg. 403 Pg. 404 Pg. 404 Pg. 405 Pg. 405 Pg. 406 Pg. 406
SFDR Pg. 407 Pg. 407 Pg. 408 Pg. 408 Pg. 409 Pg. 409 Pg. 410 Pg. 410 Pg. 411 Pg. 411
TCU Pg. 412 Pg. 412 Pg. 413 Pg. 413 Pg. 414 Pg. 414 Pg. 415 Pg. 415 Pg. 416 Pg. 416
UNKN Pg. 417 Pg. 417 Pg. 418 Pg. 418 Pg. 419 Pg. 419 Pg. 420 Pg. 420 Pg. 421 Pg. 421
VAC Pg. 422 Pg. 422 Pg. 423 Pg. 423 Pg. 424 Pg. 424 Pg. 425 Pg. 425 Pg. 426 Pg. 426
371
 Bordering?
Figure 338: Proportion of AG Parcels Bordering AG Parcels
Figure 339: Proportion of COM Parcels Bordering AG Parcels
372
Figure 340: Proportion of IND Parcels Bordering AG Parcels
Figure 341: Proportion of MMR Parcels Bordering AG Parcels
373
Figure 342: Proportion of MU Parcels Bordering AG Parcels
Figure 343: Proportion of MFR Parcels Bordering AG Parcels
374
Figure 344: Proportion of PUB Parcels Bordering AG Parcels
Figure 345: Proportion of SFDR Parcels Bordering AG Parcels
375
Figure 346: Proportion of TCU Parcels Bordering AG Parcels
Figure 347: Proportion of VAC Parcels Bordering AG Parcels
376
Figure 348: Proportion of AG Parcels Bordering COM Parcels
Figure 349: Proportion of COM Parcels Bordering COM Parcels
377
Figure 350: Proportion of IND Parcels Bordering COM Parcels
Figure 351: Proportion of MMR Parcels Bordering COM Parcels
378
Figure 352: Proportion of MU Parcels Bordering COM Parcels
Figure 353: Proportion of MFR Parcels Bordering COM Parcels
379
Figure 354: Proportion of PUB Parcels Bordering COM Parcels
Figure 355: Proportion of SFDR Parcels Bordering COM Parcels
380
Figure 356: Proportion of TCU Parcels Bordering COM Parcels
Figure 357: Proportion of VAC Parcels Bordering COM Parcels
381
Figure 358: Proportion of AG Parcels Bordering IND Parcels
Figure 359: Proportion of COM Parcels Bordering IND Parcels
382
Figure 360: Proportion of IND Parcels Bordering IND Parcels
Figure 361: Proportion of MMR Parcels Bordering IND Parcels
383
Figure 362: Proportion of MU Parcels Bordering IND Parcels
Figure 363: Proportion of MFR Parcels Bordering IND Parcels
384
Figure 364: Proportion of PUB Parcels Bordering IND Parcels
Figure 365: Proportion of SFDR Parcels Bordering IND Parcels
385
Figure 366: Proportion of TCU Parcels Bordering IND Parcels
Figure 367: Proportion of VAC Parcels Bordering IND Parcels
386
Figure 368: Proportion of AG Parcels Bordering MMR Parcels
Figure 369: Proportion of COM Parcels Bordering MMR Parcels
387
Figure 370: Proportion of IND Parcels Bordering MMR Parcels
Figure 371: Proportion of MMR Parcels Bordering MMR Parcels
388
Figure 372: Proportion of MU Parcels Bordering MMR Parcels
Figure 373: Proportion of MFR Parcels Bordering MMR Parcels
389
Figure 374: Proportion of PUB Parcels Bordering MMR Parcels
Figure 375: Proportion of SFDR Parcels Bordering MMR Parcels
390
Figure 376: Proportion of TCU Parcels Bordering MMR Parcels
Figure 377: Proportion of VAC Parcels Bordering MMR Parcels
391
Figure 378: Proportion of AG Parcels Bordering MU Parcels
Figure 379: Proportion of COM Parcels Bordering MU Parcels
392
Figure 380: Proportion of IND Parcels Bordering MU Parcels
Figure 381: Proportion of MMR Parcels Bordering MU Parcels
393
Figure 382: Proportion of MU Parcels Bordering MU Parcels
Figure 383: Proportion of MFR Parcels Bordering MU Parcels
394
Figure 384: Proportion of PUB Parcels Bordering MU Parcels
Figure 385: Proportion of SFDR Parcels Bordering MU Parcels
395
Figure 386: Proportion of TCU Parcels Bordering MU Parcels
Figure 387: Proportion of VAC Parcels Bordering MU Parcels
396
Figure 388: Proportion of AG Parcels Bordering MFR Parcels
Figure 389: Proportion of COM Parcels Bordering MFR Parcels
397
Figure 390: Proportion of IND Parcels Bordering MFR Parcels
Figure 391: Proportion of MMR Parcels Bordering MFR Parcels
398
Figure 392: Proportion of MU Parcels Bordering MFR Parcels
Figure 393: Proportion of MFR Parcels Bordering MFR Parcels
399
Figure 394: Proportion of PUB Parcels Bordering MFR Parcels
Figure 395: Proportion of SFDR Parcels Bordering MFR Parcels
400
Figure 396: Proportion of TCU Parcels Bordering MFR Parcels
Figure 397: Proportion of VAC Parcels Bordering MFR Parcels
401
Figure 398: Proportion of AG Parcels Bordering PUB Parcels
Figure 399: Proportion of COM Parcels Bordering PUB Parcels
402
Figure 400: Proportion of IND Parcels Bordering PUB Parcels
Figure 401: Proportion of MMR Parcels Bordering PUB Parcels
403
Figure 402: Proportion of MU Parcels Bordering PUB Parcels
Figure 403: Proportion of MFR Parcels Bordering PUB Parcels
404
Figure 404: Proportion of PUB Parcels Bordering PUB Parcels
Figure 405: Proportion of SFDR Parcels Bordering PUB Parcels
405
Figure 406: Proportion of TCU Parcels Bordering PUB Parcels
Figure 407: Proportion of VAC Parcels Bordering PUB Parcels
406
Figure 408: Proportion of AG Parcels Bordering SFDR Parcels
Figure 409: Proportion of COM Parcels Bordering SFDR Parcels
407
Figure 410: Proportion of IND Parcels Bordering SFDR Parcels
Figure 411: Proportion of MMR Parcels Bordering SFDR Parcels
408
Figure 412: Proportion of MU Parcels Bordering SFDR Parcels
Figure 413: Proportion of MFR Parcels Bordering SFDR Parcels
409
Figure 414: Proportion of PUB Parcels Bordering SFDR Parcels
Figure 415: Proportion of SFDR Parcels Bordering SFDR Parcels
410
Figure 416: Proportion of TCU Parcels Bordering SFDR Parcels
Figure 417: Proportion of VAC Parcels Bordering SFDR Parcels
411
Figure 418: Proportion of AG Parcels Bordering TCU Parcels
Figure 419: Proportion of COM Parcels Bordering TCU Parcels
412
Figure 420: Proportion of IND Parcels Bordering TCU Parcels
Figure 421: Proportion of MMR Parcels Bordering TCU Parcels
413
Figure 422: Proportion of MU Parcels Bordering TCU Parcels
Figure 423: Proportion of MFR Parcels Bordering TCU Parcels
414
Figure 424: Proportion of PUB Parcels Bordering TCU Parcels
Figure 425: Proportion of SFDR Parcels Bordering TCU Parcels
415
Figure 426: Proportion of TCU Parcels Bordering TCU Parcels
Figure 427: Proportion of VAC Parcels Bordering TCU Parcels
416
Figure 428: Proportion of AG Parcels Bordering UNKN Parcels
Figure 429: Proportion of COM Parcels Bordering UNKN Parcels
417
Figure 430: Proportion of IND Parcels Bordering UNKN Parcels
Figure 431: Proportion of MMR Parcels Bordering UNKN Parcels
418
Figure 432: Proportion of MU Parcels Bordering UNKN Parcels
Figure 433: Proportion of MFR Parcels Bordering UNKN Parcels
419
Figure 434: Proportion of PUB Parcels Bordering UNKN Parcels
Figure 435: Proportion of SFDR Parcels Bordering UNKN Parcels
420
Figure 436: Proportion of TCU Parcels Bordering UNKN Parcels
Figure 437: Proportion of VAC Parcels Bordering UNKN Parcels
421
Figure 438: Proportion of AG Parcels Bordering VAC Parcels
Figure 439: Proportion of COM Parcels Bordering VAC Parcels
422
Figure 440: Proportion of IND Parcels Bordering VAC Parcels
Figure 441: Proportion of MMR Parcels Bordering VAC Parcels
423
Figure 442: Proportion of MU Parcels Bordering VAC Parcels
Figure 443: Proportion of MFR Parcels Bordering VAC Parcels
424
Figure 444: Proportion of PUB Parcels Bordering VAC Parcels
Figure 445: Proportion of SFDR Parcels Bordering VAC Parcels
425
Figure 446: Proportion of TCU Parcels Bordering VAC Parcels
Figure 447: Proportion of VAC Parcels Bordering VAC Parcels
426
Appendix E: Bar Charts Showing the Normalized Proportion of Parcels in Each Land Use
Class Bordering Each Land Use
This appendix provides bar charts showing normalized values for the proportion of parcels in each land use class bordering
each land use.  For ease of reference, an index with the page number of each land use combination?s chart is provided in Table 8.
Table 8: Bar Chart Index, Normalized Proportion of Parcels in Each Land Use Class Bordering Each Land Use
% of Parcels with Land Use?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 428 Pg. 428 Pg. 429 Pg. 429 Pg. 430 Pg. 430 Pg. 431 Pg. 431 Pg. 432 Pg. 432
COM Pg. 433 Pg. 433 Pg. 434 Pg. 434 Pg. 435 Pg. 435 Pg. 436 Pg. 436 Pg. 437 Pg. 437
IND Pg. 438 Pg. 438 Pg. 439 Pg. 439 Pg. 440 Pg.440 Pg. 441 Pg. 441 Pg. 442 Pg. 442
MMR Pg. 443 Pg. 443 Pg. 444 Pg. 444 Pg. 445 Pg. 445 Pg. 446 Pg. 446 Pg. 447 Pg. 447
MU Pg. 448 Pg. 448 Pg. 449 Pg. 449 Pg. 450 Pg. 450 Pg. 451 Pg. 451 Pg. 452 Pg. 452
MFR Pg. 453 Pg. 453 Pg. 454 Pg. 454 Pg. 455 Pg. 455 Pg. 456 Pg. 456 Pg. 457 Pg. 457
PUB Pg. 458 Pg. 458 Pg. 459 Pg. 459 Pg. 460 Pg. 460 Pg. 461 Pg. 461 Pg. 462 Pg. 462
SFDR Pg. 463 Pg. 463 Pg. 464 Pg. 464 Pg. 465 Pg. 465 Pg. 466 Pg. 466 Pg. 467 Pg. 467
TCU Pg. 468 Pg. 468 Pg. 469 Pg. 469 Pg. 470 Pg. 470 Pg. 471 Pg. 471 Pg. 472 Pg. 472
UNKN Pg. 473 Pg. 473 Pg. 474 Pg. 474 Pg. 475 Pg. 475 Pg. 476 Pg. 476 Pg. 477 Pg. 477
VAC Pg. 478 Pg. 478 Pg. 479 Pg. 479 Pg. 480 Pg. 480 Pg. 481 Pg. 481 Pg. 482 Pg. 482
427
 Bordering?
Figure 448: Proportion of AG Parcels Bordering AG Parcels (Normalized)
Figure 449: Proportion of COM Parcels Bordering AG Parcels (Normalized)
428
Figure 450: Proportion of IND Parcels Bordering AG Parcels (Normalized)
Figure 451: Proportion of MMR Parcels Bordering AG Parcels (Normalized)
429
Figure 452: Proportion of MU Parcels Bordering AG Parcels (Normalized)
Figure 453: Proportion of MFR Parcels Bordering AG Parcels (Normalized)
430
Figure 454: Proportion of PUB Parcels Bordering AG Parcels (Normalized)
Figure 455: Proportion of SFDR Parcels Bordering AG Parcels (Normalized)
431
Figure 456: Proportion of TCU Parcels Bordering AG Parcels (Normalized)
Figure 457: Proportion of VAC Parcels Bordering AG Parcels (Normalized)
432
Figure 458: Proportion of AG Parcels Bordering COM Parcels (Normalized)
Figure 459: Proportion of COM Parcels Bordering COM Parcels (Normalized)
433
Figure 460: Proportion of IND Parcels Bordering COM Parcels (Normalized)
Figure 461: Proportion of MMR Parcels Bordering COM Parcels (Normalized)
434
Figure 462: Proportion of MU Parcels Bordering COM Parcels (Normalized)
Figure 463: Proportion of MFR Parcels Bordering COM Parcels (Normalized)
435
Figure 464: Proportion of PUB Parcels Bordering COM Parcels (Normalized)
Figure 465: Proportion of SFDR Parcels Bordering COM Parcels (Normalized)
436
Figure 466: Proportion of TCU Parcels Bordering COM Parcels (Normalized)
Figure 467: Proportion of VAC Parcels Bordering COM Parcels (Normalized)
437
Figure 468: Proportion of AG Parcels Bordering IND Parcels (Normalized)
Figure 469: Proportion of COM Parcels Bordering IND Parcels (Normalized)
438
Figure 470: Proportion of IND Parcels Bordering IND Parcels (Normalized)
Figure 471: Proportion of MMR Parcels Bordering IND Parcels (Normalized)
439
Figure 472: Proportion of MU Parcels Bordering IND Parcels (Normalized)
Figure 473: Proportion of MFR Parcels Bordering IND Parcels (Normalized)
440
Figure 474: Proportion of PUB Parcels Bordering IND Parcels (Normalized)
Figure 475: Proportion of SFDR Parcels Bordering IND Parcels (Normalized)
441
Figure 476: Proportion of TCU Parcels Bordering IND Parcels (Normalized)
Figure 477: Proportion of VAC Parcels Bordering IND Parcels (Normalized)
442
Figure 478: Proportion of AG Parcels Bordering MMR Parcels (Normalized)
Figure 479: Proportion of COM Parcels Bordering MMR Parcels (Normalized)
443
Figure 480: Proportion of IND Parcels Bordering MMR Parcels (Normalized)
Figure 481: Proportion of MMR Parcels Bordering MMR Parcels (Normalized)
444
Figure 482: Proportion of MU Parcels Bordering MMR Parcels (Normalized)
Figure 483: Proportion of MFR Parcels Bordering MMR Parcels (Normalized)
445
Figure 484: Proportion of PUB Parcels Bordering MMR Parcels (Normalized)
Figure 485: Proportion of SFDR Parcels Bordering MMR Parcels (Normalized)
446
Figure 486: Proportion of TCU Parcels Bordering MMR Parcels (Normalized)
Figure 487: Proportion of VAC Parcels Bordering MMR Parcels (Normalized)
447
Figure 488: Proportion of AG Parcels Bordering MU Parcels (Normalized)
Figure 489: Proportion of COM Parcels Bordering MU Parcels (Normalized)
448
Figure 490: Proportion of IND Parcels Bordering MU Parcels (Normalized)
Figure 491: Proportion of MMR Parcels Bordering MU Parcels (Normalized)
449
Figure 492: Proportion of MU Parcels Bordering MU Parcels (Normalized)
Figure 493: Proportion of MFR Parcels Bordering MU Parcels (Normalized)
450
Figure 494: Proportion of PUB Parcels Bordering MU Parcels (Normalized)
Figure 495: Proportion of SFDR Parcels Bordering MU Parcels (Normalized)
451
Figure 496: Proportion of TCU Parcels Bordering MU Parcels (Normalized)
Figure 497: Proportion of VAC Parcels Bordering MU Parcels (Normalized)
452
Figure 498: Proportion of AG Parcels Bordering MFR Parcels (Normalized)
Figure 499: Proportion of COM Parcels Bordering MFR Parcels (Normalized)
453
Figure 500: Proportion of IND Parcels Bordering MFR Parcels (Normalized)
Figure 501: Proportion of MMR Parcels Bordering MFR Parcels (Normalized)
454
Figure 502: Proportion of MU Parcels Bordering MFR Parcels (Normalized)
Figure 503: Proportion of MFR Parcels Bordering MFR Parcels (Normalized)
455
Figure 504: Proportion of PUB Parcels Bordering MFR Parcels (Normalized)
Figure 505: Proportion of SFDR Parcels Bordering MFR Parcels (Normalized)
456
Figure 506: Proportion of TCU Parcels Bordering MFR Parcels (Normalized)
Figure 507: Proportion of VAC Parcels Bordering MFR Parcels (Normalized)
457
Figure 508: Proportion of AG Parcels Bordering PUB Parcels (Normalized)
Figure 509: Proportion of COM Parcels Bordering PUB Parcels (Normalized)
458
Figure 510: Proportion of IND Parcels Bordering PUB Parcels (Normalized)
Figure 511: Proportion of MMR Parcels Bordering PUB Parcels (Normalized)
459
Figure 512: Proportion of MU Parcels Bordering PUB Parcels (Normalized)
Figure 513: Proportion of MFR Parcels Bordering PUB Parcels (Normalized)
460
Figure 514: Proportion of PUB Parcels Bordering PUB Parcels (Normalized)
Figure 515: Proportion of SFDR Parcels Bordering PUB Parcels (Normalized)
461
Figure 516: Proportion of TCU Parcels Bordering PUB Parcels (Normalized)
Figure 517: Proportion of VAC Parcels Bordering PUB Parcels (Normalized)
462
Figure 518: Proportion of AG Parcels Bordering SFDR Parcels (Normalized)
Figure 519: Proportion of COM Parcels Bordering SFDR Parcels (Normalized)
463
Figure 520: Proportion of IND Parcels Bordering SFDR Parcels (Normalized)
Figure 521: Proportion of MMR Parcels Bordering SFDR Parcels (Normalized)
464
Figure 522: Proportion of MU Parcels Bordering SFDR Parcels (Normalized)
Figure 523: Proportion of MFR Parcels Bordering SFDR Parcels (Normalized)
465
Figure 524: Proportion of PUB Parcels Bordering SFDR Parcels (Normalized)
Figure 525: Proportion of SFDR Parcels Bordering SFDR Parcels (Normalized)
466
Figure 526: Proportion of TCU Parcels Bordering SFDR Parcels (Normalized)
Figure 527: Proportion of VAC Parcels Bordering SFDR Parcels (Normalized)
467
Figure 528: Proportion of AG Parcels Bordering TCU Parcels (Normalized)
Figure 529: Proportion of COM Parcels Bordering TCU Parcels (Normalized)
468
Figure 530: Proportion of IND Parcels Bordering TCU Parcels (Normalized)
Figure 531: Proportion of MMR Parcels Bordering TCU Parcels (Normalized)
469
Figure 532: Proportion of MU Parcels Bordering TCU Parcels (Normalized)
Figure 533: Proportion of MFR Parcels Bordering TCU Parcels (Normalized)
470
Figure 534: Proportion of PUB Parcels Bordering TCU Parcels (Normalized)
Figure 535: Proportion of SFDR Parcels Bordering TCU Parcels (Normalized)
471
Figure 536: Proportion of TCU Parcels Bordering TCU Parcels (Normalized)
Figure 537: Proportion of VAC Parcels Bordering TCU Parcels (Normalized)
472
Figure 538: Proportion of AG Parcels Bordering UNKN Parcels (Normalized)
Figure 539: Proportion of COM Parcels Bordering UNKN Parcels (Normalized)
473
Figure 540: Proportion of IND Parcels Bordering UNKN Parcels (Normalized)
Figure 541: Proportion of MMR Parcels Bordering UNKN Parcels (Normalized)
474
Figure 542: Proportion of MU Parcels Bordering UNKN Parcels (Normalized)
Figure 543: Proportion of MFR Parcels Bordering UNKN Parcels (Normalized)
475
Figure 544: Proportion of PUB Parcels Bordering UNKN Parcels (Normalized)
Figure 545: Proportion of SFDR Parcels Bordering UNKN Parcels (Normalized)
476
Figure 546: Proportion of TCU Parcels Bordering UNKN Parcels (Normalized)
Figure 547: Proportion of VAC Parcels Bordering UNKN Parcels (Normalized)
477
Figure 548: Proportion of AG Parcels Bordering VAC Parcels (Normalized)
Figure 549: Proportion of COM Parcels Bordering VAC Parcels (Normalized)
478
Figure 550: Proportion of IND Parcels Bordering VAC Parcels (Normalized)
Figure 551: Proportion of MMR Parcels Bordering VAC Parcels (Normalized)
479
Figure 552: Proportion of MU Parcels Bordering VAC Parcels (Normalized)
Figure 553: Proportion of MFR Parcels Bordering VAC Parcels (Normalized)
480
Figure 554: Proportion of PUB Parcels Bordering VAC Parcels (Normalized)
Figure 555: Proportion of SFDR Parcels Bordering VAC Parcels (Normalized)
481
Figure 556: Proportion of TCU Parcels Bordering VAC Parcels (Normalized)
Figure 557: Proportion of VAC Parcels Bordering VAC Parcels (Normalized)
482
Appendix F: Bar Charts Showing the Proportion of Parcels in Each Land Use Class Bordering
Only the Same Land Use
This appendix provides bar charts showing the (non-normalized) proportion of parcels in each land use class bordering only
the same land use.
Figure 558: Proportion of AG Parcels Bordering Only Other AG Parcels
483
Figure 559: Proportion of COM Parcels Bordering Only Other COM Parcels
Figure 560: Proportion of IND Parcels Bordering Only Other IND Parcels
484
Figure 561: Proportion of MMR Parcels Bordering Only Other MMR Parcels
Figure 562: Proportion of MU Parcels Bordering Only Other MU Parcels
485
Figure 563: Proportion of MFR Parcels Bordering Only Other MFR Parcels
Figure 564: Proportion of PUB Parcels Bordering Only Other PUB Parcels
486
Figure 565: Proportion of SFDR Parcels Bordering Only Other SFDR Parcels
Figure 566: Proportion of TCU Parcels Bordering Only Other TCU Parcels
487
Figure 567: Proportion of UNKN Parcels Bordering Only Other UNKN Parcels
Figure 568: Proportion of VAC Parcels Bordering Only Other VAC Parcels
488
Appendix G: Bar Charts Showing the Proportional Area of Land Uses Within 500 Feet of Each
Land Use
This appendix provides bar charts showing the proportional area of land uses within 500 feet of each land use.  For ease of
reference, an index with the page number of each land use combination?s chart is provided in Table 9.
Table 9: Bar Chart Index, Proportional Area of Land Uses Within 500 Feet of Each Land Use
Comprised of?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 490 Pg. 490 Pg. 491 Pg. 491 Pg. 492 Pg. 492 Pg. 493 Pg. 493 Pg. 494 Pg. 494 Pg. 495
COM Pg. 495 Pg. 496 Pg. 496 Pg. 497 Pg. 497 Pg. 498 Pg. 498 Pg. 499 Pg. 499 Pg. 500 Pg. 500
IND Pg. 501 Pg. 501 Pg. 502 Pg. 502 Pg. 503 Pg. 503 Pg. 504 Pg. 504 Pg. 505 Pg. 505 Pg. 506
MMR Pg. 506 Pg. 507 Pg. 507 Pg. 508 Pg. 508 Pg. 509 Pg. 509 Pg. 510 Pg. 510 Pg. 511 Pg. 511
MU Pg. 512 Pg. 512 Pg. 513 Pg. 513 Pg. 514 Pg. 514 Pg. 515 Pg. 515 Pg. 516 Pg. 516 Pg. 517
MFR Pg. 517 Pg. 518 Pg. 518 Pg. 519 Pg. 519 Pg. 520 Pg.520 Pg. 521 Pg. 521 Pg. 522 Pg. 522
PUB Pg. 523 Pg. 523 Pg. 524 Pg. 524 Pg. 525 Pg. 525 Pg. 526 Pg. 526 Pg. 527 Pg. 527 Pg. 528
SFDR Pg. 528 Pg. 529 Pg. 529 Pg. 530 Pg. 530 Pg. 531 Pg. 531 Pg. 532 Pg. 532 Pg. 533 Pg. 533
TCU Pg. 534 Pg. 534 Pg. 535 Pg. 535 Pg. 536 Pg. 536 Pg. 537 Pg. 537 Pg. 538 Pg. 538 Pg. 539
UNKN Pg. 539 Pg. 540 Pg. 540 Pg. 541 Pg. 541 Pg. 542 Pg. 542 Pg. 543 Pg. 543 Pg. 544 Pg. 544
VAC Pg. 545 Pg. 545 Pg. 546 Pg. 546 Pg. 547 Pg. 547 Pg. 548 Pg. 548 Pg. 549 Pg. 549 Pg. 550
489
 Proportion of Parcel Area Near?
Figure 569: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to AG Uses
Figure 570: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to COM Uses
490
Figure 571: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to IND Uses
Figure 572: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to MMR Uses
491
Figure 573: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to MU Uses
Figure 574: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to MFR Uses
492
Figure 575: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to PUB Uses
Figure 576: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to SFDR Uses
493
Figure 577: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to TCU Uses
Figure 578: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to UNKN Uses
494
Figure 579: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to VAC Uses
Figure 580: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to AG Uses
495
Figure 581: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to COM Uses
Figure 582: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to IND Uses
496
Figure 583: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to MMR Uses
Figure 584: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to MU Uses
497
Figure 585: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to MFR Uses
Figure 586: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to PUB Uses
498
Figure 587: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to SFDR Uses
Figure 588: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to TCU Uses
499
Figure 589: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to UNKN Uses
Figure 590: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to VAC Uses
500
Figure 591: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to AG Uses
Figure 592: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to COM Uses
501
Figure 593: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to IND Uses
Figure 594: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to MMR Uses
502
Figure 595: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to MU Uses
Figure 596: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to MFR Uses
503
Figure 597: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to PUB Uses
Figure 598: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to SFDR Uses
504
Figure 599: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to TCU Uses
Figure 600: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to UNKN Uses
505
Figure 601: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to VAC Uses
Figure 602: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to AG Uses
506
Figure 603: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to COM Uses
Figure 604: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to IND Uses
507
Figure 605: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to MMR Uses
Figure 606: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to MU Uses
508
Figure 607: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to MFR Uses
Figure 608: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to PUB Uses
509
Figure 609: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to SFDR Uses
Figure 610: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to TCU Uses
510
Figure 611: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to UNKN Uses
Figure 612: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to VAC Uses
511
Figure 613: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to AG Uses
Figure 614: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to COM Uses
512
Figure 615: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to IND Uses
Figure 616: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to MMR Uses
513
Figure 617: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to MU Uses
Figure 618: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to MFR Uses
514
Figure 619: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to PUB Uses
Figure 620: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to SFDR Uses
515
Figure 621: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to TCU Uses
Figure 622: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to UNKN Uses
516
Figure 623: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to VAC Uses
Figure 624: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to AG Uses
517
Figure 625: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to COM Uses
Figure 626: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to IND Uses
518
Figure 627: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to MMR Uses
Figure 628: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to MU Uses
519
Figure 629: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to MFR Uses
Figure 630: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to PUB Uses
520
Figure 631: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to SFDR Uses
Figure 632: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to TCU Uses
521
Figure 633: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to UNKN Uses
Figure 634: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to VAC Uses
522
Figure 635: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to AG Uses
Figure 636: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to COM Uses
523
Figure 637: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to IND Uses
Figure 638: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to MMR Uses
524
Figure 639: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to MU Uses
Figure 640: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to MFR Uses
525
Figure 641: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to PUB Uses
Figure 642: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to SFDR Uses
526
Figure 643: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to TCU Uses
Figure 644: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to UNKN Uses
527
Figure 645: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to VAC Uses
Figure 646: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to AG Uses
528
Figure 647: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to COM Uses
Figure 648: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to IND Uses
529
Figure 649: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to MMR Uses
Figure 650: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to MU Uses
530
Figure 651: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to MFR Uses
Figure 652: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to PUB Uses
531
Figure 653: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to SFDR Uses
Figure 654: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to TCU Uses
532
Figure 655: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to UNKN Uses
Figure 656: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to VAC Uses
533
Figure 657: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to AG Uses
Figure 658: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to COM Uses
534
Figure 659: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to IND Uses
Figure 660: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to MMR Uses
535
Figure 661: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to MU Uses
Figure 662: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to MFR Uses
536
Figure 663: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to PUB Uses
Figure 664: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to SFDR Uses
537
Figure 665: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to TCU Uses
Figure 666: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to UNKN Uses
538
Figure 667: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to VAC Uses
Figure 668: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to AG Uses
539
Figure 669: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to COM Uses
Figure 670: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to IND Uses
540
Figure 671: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to MMR Uses
Figure 672: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to MU Uses
541
Figure 673: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to MFR Uses
Figure 674: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to PUB Uses
542
Figure 675: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to SFDR Uses
Figure 676: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to TCU Uses
543
Figure 677: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to UNKN Uses
Figure 678: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to VAC Uses
544
Figure 679: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to AG Uses
Figure 680: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to COM Uses
545
Figure 681: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to IND Uses
Figure 682: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to MMR Uses
546
Figure 683: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to MU Uses
Figure 684: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to MFR Uses
547
Figure 685: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to PUB Uses
Figure 686: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to SFDR Uses
548
Figure 687: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to TCU Uses
Figure 688: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to UNKN Uses
549
Figure 689: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to VAC Uses
550
Appendix H: Bar Charts Showing the Normalized Proportional Area of Land Uses Within 500
Feet of Each Land Use
This appendix provides bar charts showing the normalized proportional areas of land uses within 500 feet of each other land
use.  For ease of reference, an index with the page number of each land use combination?s chart is provided in Table 10.
Table 10: Bar Chart Index, Normalized Proportional Area of Land Uses Within 500 Feet of Each Land Use
Comprised of?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 552 Pg. 552 Pg. 553 Pg. 553 Pg. 554 Pg. 554 Pg. 555 Pg. 555 Pg. 556 Pg. 556 Pg. 557
COM Pg. 557 Pg. 558 Pg. 558 Pg. 559 Pg. 559 Pg. 560 Pg. 560 Pg. 561 Pg. 561 Pg. 562 Pg. 562
IND Pg. 563 Pg. 563 Pg. 564 Pg. 564 Pg. 565 Pg. 565 Pg. 566 Pg. 566 Pg. 567 Pg. 567 Pg. 568
MMR Pg. 568 Pg. 569 Pg. 569 Pg. 570 Pg. 570 Pg. 571 Pg. 571 Pg. 572 Pg. 572 Pg. 573 Pg. 573
MU Pg. 574 Pg. 574 Pg. 575 Pg. 575 Pg. 576 Pg. 576 Pg. 577 Pg. 577 Pg. 578 Pg. 578 Pg. 579
MFR Pg. 579 Pg. 580 Pg. 580 Pg. 581 Pg. 581 Pg. 582 Pg. 582 Pg. 583 Pg. 583 Pg. 584 Pg. 584
PUB Pg. 585 Pg. 585 Pg. 586 Pg. 586 Pg. 587 Pg. 587 Pg. 588 Pg. 588 Pg. 589 Pg. 589 Pg. 590
SFDR Pg. 590 Pg. 591 Pg. 591 Pg. 592 Pg. 592 Pg. 593 Pg. 593 Pg. 594 Pg. 594 Pg. 595 Pg. 595
TCU Pg. 596 Pg. 596 Pg. 597 Pg. 597 Pg. 598 Pg. 598 Pg. 599 Pg. 599 Pg. 600 Pg. 600 Pg. 601
UNKN Pg. 601 Pg. 602 Pg. 602 Pg. 603 Pg. 603 Pg. 604 Pg. 604 Pg. 605 Pg. 605 Pg. 606 Pg. 606
VAC Pg. 607 Pg. 607 Pg. 608 Pg. 608 Pg. 609 Pg. 609 Pg. 610 Pg. 610 Pg. 611 Pg. 611 Pg. 612
551
 Proportion of Parcel Area Near?
Figure 690: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to AG Uses (Normalized)
Figure 691: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to COM Uses (Normalized)
552
Figure 692: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to IND Uses (Normalized)
Figure 693: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to MMR Uses (Normalized)
553
Figure 694: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to MU Uses (Normalized)
Figure 695: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to MFR Uses (Normalized)
554
Figure 696: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to PUB Uses (Normalized)
Figure 697: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to SFDR Uses (Normalized)
555
Figure 698: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to TCU Uses (Normalized)
Figure 699: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to UNKN Uses (Normalized)
556
Figure 700: Proportion of Parcel Area Within 500 Feet of AG Parcels Devoted to VAC Uses (Normalized)
Figure 701: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to AG Uses (Normalized)
557
Figure 702: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to COM Uses (Normalized)
Figure 703: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to IND Uses (Normalized)
558
Figure 704: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to MMR Uses (Normalized)
Figure 705: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to MU Uses (Normalized)
559
Figure 706: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to MFR Uses (Normalized)
Figure 707: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to PUB Uses (Normalized)
560
Figure 708: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to SFDR Uses (Normalized)
Figure 709: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to TCU Uses (Normalized)
561
Figure 710: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to UNKN Uses (Normalized)
Figure 711: Proportion of Parcel Area Within 500 Feet of COM Parcels Devoted to VAC Uses (Normalized)
562
Figure 712: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to AG Uses (Normalized)
Figure 713: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to COM Uses (Normalized)
563
Figure 714: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to IND Uses (Normalized)
Figure 715: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to MMR Uses (Normalized)
564
Figure 716: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to MU Uses (Normalized)
Figure 717: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to MFR Uses (Normalized)
565
Figure 718: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to PUB Uses (Normalized)
Figure 719: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to SFDR Uses (Normalized)
566
Figure 720: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to TCU Uses (Normalized)
Figure 721: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to UNKN Uses (Normalized)
567
Figure 722: Proportion of Parcel Area Within 500 Feet of IND Parcels Devoted to VAC Uses (Normalized)
Figure 723: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to AG Uses (Normalized)
568
Figure 724: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to COM Uses (Normalized)
Figure 725: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to IND Uses (Normalized)
569
Figure 726: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to MMR Uses (Normalized)
Figure 727: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to MU Uses (Normalized)
570
Figure 728: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to MFR Uses (Normalized)
Figure 729: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to PUB Uses (Normalized)
571
Figure 730: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to SFDR Uses (Normalized)
Figure 731: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to TCU Uses (Normalized)
572
Figure 732: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to UNKN Uses (Normalized)
Figure 733: Proportion of Parcel Area Within 500 Feet of MMR Parcels Devoted to VAC Uses (Normalized)
573
Figure 734: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to AG Uses (Normalized)
Figure 735: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to COM Uses (Normalized)
574
Figure 736: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to IND Uses (Normalized)
Figure 737: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to MMR Uses (Normalized)
575
Figure 738: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to MU Uses (Normalized)
Figure 739: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to MFR Uses (Normalized)
576
Figure 740: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to PUB Uses (Normalized)
Figure 741: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to SFDR Uses (Normalized)
577
Figure 742: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to TCU Uses (Normalized)
Figure 743: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to UNKN Uses (Normalized)
578
Figure 744: Proportion of Parcel Area Within 500 Feet of MU Parcels Devoted to VAC Uses (Normalized)
Figure 745: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to AG Uses (Normalized)
579
Figure 746: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to COM Uses (Normalized)
Figure 747: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to IND Uses (Normalized)
580
Figure 748: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to MMR Uses (Normalized)
Figure 749: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to MU Uses (Normalized)
581
Figure 750: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to MFR Uses (Normalized)
Figure 751: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to PUB Uses (Normalized)
582
Figure 752: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to SFDR Uses (Normalized)
Figure 753: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to TCU Uses (Normalized)
583
Figure 754: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to UNKN Uses (Normalized)
Figure 755: Proportion of Parcel Area Within 500 Feet of MFR Parcels Devoted to VAC Uses (Normalized)
584
Figure 756: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to AG Uses (Normalized)
Figure 757: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to COM Uses (Normalized)
585
Figure 758: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to IND Uses (Normalized)
Figure 759: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to MMR Uses (Normalized)
586
Figure 760: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to MU Uses (Normalized)
Figure 761: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to MFR Uses (Normalized)
587
Figure 762: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to PUB Uses (Normalized)
Figure 763: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to SFDR Uses (Normalized)
588
Figure 764: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to TCU Uses (Normalized)
Figure 765: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to UNKN Uses (Normalized)
589
Figure 766: Proportion of Parcel Area Within 500 Feet of PUB Parcels Devoted to VAC Uses (Normalized)
Figure 767: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to AG Uses (Normalized)
590
Figure 768: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to COM Uses (Normalized)
Figure 769: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to IND Uses (Normalized)
591
Figure 770: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to MMR Uses (Normalized)
Figure 771: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to MU Uses (Normalized)
592
Figure 772: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to MFR Uses (Normalized)
Figure 773: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to PUB Uses (Normalized)
593
Figure 774: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to SFDR Uses (Normalized)
Figure 775: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to TCU Uses (Normalized)
594
Figure 776: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to UNKN Uses (Normalized)
Figure 777: Proportion of Parcel Area Within 500 Feet of SFDR Parcels Devoted to VAC Uses (Normalized)
595
Figure 778: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to AG Uses (Normalized)
Figure 779: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to COM Uses (Normalized)
596
Figure 780: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to IND Uses (Normalized)
Figure 781: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to MMR Uses (Normalized)
597
Figure 782: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to MU Uses (Normalized)
Figure 783: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to MFR Uses (Normalized)
598
Figure 784: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to PUB Uses (Normalized)
Figure 785: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to SFDR Uses (Normalized)
599
Figure 786: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to TCU Uses (Normalized)
Figure 787: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to UNKN Uses (Normalized)
600
Figure 788: Proportion of Parcel Area Within 500 Feet of TCU Parcels Devoted to VAC Uses (Normalized)
Figure 789: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to AG Uses (Normalized)
601
Figure 790: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to COM Uses (Normalized)
Figure 791: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to IND Uses (Normalized)
602
Figure 792: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to MMR Uses (Normalized)
Figure 793: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to MU Uses (Normalized)
603
Figure 794: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to MFR Uses (Normalized)
Figure 795: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to PUB Uses (Normalized)
604
Figure 796: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to SFDR Uses (Normalized)
Figure 797: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to TCU Uses (Normalized)
605
Figure 798: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to UNKN Uses (Normalized)
Figure 799: Proportion of Parcel Area Within 500 Feet of UNKN Parcels Devoted to VAC Uses (Normalized)
606
Figure 800: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to AG Uses (Normalized)
Figure 801: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to COM Uses (Normalized)
607
Figure 802: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to IND Uses (Normalized)
Figure 803: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to MMR Uses (Normalized)
608
Figure 804: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to MU Uses (Normalized)
Figure 805: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to MFR Uses (Normalized)
609
Figure 806: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to PUB Uses (Normalized)
Figure 807: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to SFDR Uses (Normalized)
610
Figure 808: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to TCU Uses (Normalized)
Figure 809: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to UNKN Uses (Normalized)
611
Figure 810: Proportion of Parcel Area Within 500 Feet of VAC Parcels Devoted to VAC Uses (Normalized)
612
Appendix I: Bar Charts Showing the Proportion of Parcels that Have Each Land Use Within
500 Feet
This appendix provides bar charts showing the proportion of parcels that have each land use within 500 feet.  For ease of
reference, an index with the page number of each land use combination?s chart is provided in Table 11.
Table 11: Bar Chart Index, Proportion of Parcels that Have Each Land Use Within 500 Feet
% of Parcels with Land Use?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 614 Pg. 614 Pg. 615 Pg. 615 Pg. 616 Pg. 616 Pg. 617 Pg. 617 Pg. 618 Pg. 618
COM Pg. 619 Pg. 619 Pg. 620 Pg. 620 Pg. 621 Pg. 621 Pg. 622 Pg. 622 Pg. 623 Pg. 623
IND Pg. 624 Pg. 624 Pg. 625 Pg. 625 Pg. 626 Pg. 626 Pg. 627 Pg. 627 Pg. 628 Pg. 628
MMR Pg. 629 Pg. 629 Pg. 630 Pg. 630 Pg. 631 Pg. 631 Pg. 632 Pg. 632 Pg. 633 Pg. 633
MU Pg. 634 Pg. 634 Pg. 635 Pg. 635 Pg. 636 Pg. 636 Pg. 637 Pg. 637 Pg. 638 Pg. 638
MFR Pg. 639 Pg. 639 Pg. 640 Pg. 640 Pg. 641 Pg. 641 Pg. 642 Pg. 642 Pg. 643 Pg. 643
PUB Pg. 644 Pg. 644 Pg. 645 Pg. 645 Pg. 646 Pg. 646 Pg. 647 Pg. 647 Pg. 648 Pg. 648
SFDR Pg. 649 Pg. 649 Pg. 650 Pg. 650 Pg. 651 Pg. 651 Pg. 652 Pg. 652 Pg. 653 Pg.653
TCU Pg. 654 Pg. 654 Pg. 655 Pg. 655 Pg. 656 Pg. 656 Pg. 657 Pg. 657 Pg. 658 Pg. 658
UNKN Pg. 659 Pg. 659 Pg. 660 Pg. 660 Pg. 661 Pg. 661 Pg. 662 Pg. 662 Pg. 663 Pg. 663
VAC Pg. 664 Pg. 664 Pg. 665 Pg. 665 Pg. 666 Pg. 666 Pg. 667 Pg. 667 Pg. 668 Pg. 668
613
Within 500 Feet of?
Figure 811: Proportion of AG Parcels Within 500 Feet of AG Parcels
Figure 812: Proportion of COM Parcels Within 500 Feet of AG Parcels
614
Figure 813: Proportion of IND Parcels Within 500 Feet of AG Parcels
Figure 814: Proportion of MMR Parcels Within 500 Feet of AG Parcels
615
Figure 815: Proportion of MU Parcels Within 500 Feet of AG Parcels
Figure 816: Proportion of MFR Parcels Within 500 Feet of AG Parcels
616
Figure 817: Proportion of PUB Parcels Within 500 Feet of AG Parcels
Figure 818: Proportion of SFDR Parcels Within 500 Feet of AG Parcels
617
Figure 819: Proportion of TCU Parcels Within 500 Feet of AG Parcels
Figure 820: Proportion of VAC Parcels Within 500 Feet of AG Parcels
618
Figure 821: Proportion of AG Parcels Within 500 Feet of COM Parcels
Figure 822: Proportion of COM Parcels Within 500 Feet of COM Parcels
619
Figure 823: Proportion of IND Parcels Within 500 Feet of COM Parcels
Figure 824: Proportion of MMR Parcels Within 500 Feet of COM Parcels
620
Figure 825: Proportion of MU Parcels Within 500 Feet of COM Parcels
Figure 826: Proportion of MFR Parcels Within 500 Feet of COM Parcels
621
Figure 827: Proportion of PUB Parcels Within 500 Feet of COM Parcels
Figure 828: Proportion of SFDR Parcels Within 500 Feet of COM Parcels
622
Figure 829: Proportion of TCU Parcels Within 500 Feet of COM Parcels
Figure 830: Proportion of VAC Parcels Within 500 Feet of COM Parcels
623
Figure 831: Proportion of AG Parcels Within 500 Feet of IND Parcels
Figure 832: Proportion of COM Parcels Within 500 Feet of IND Parcels
624
Figure 833: Proportion of IND Parcels Within 500 Feet of IND Parcels
Figure 834: Proportion of MMR Parcels Within 500 Feet of IND Parcels
625
Figure 835: Proportion of MU Parcels Within 500 Feet of IND Parcels
Figure 836: Proportion of MFR Parcels Within 500 Feet of IND Parcels
626
Figure 837: Proportion of PUB Parcels Within 500 Feet of IND Parcels
Figure 838: Proportion of SFDR Parcels Within 500 Feet of IND Parcels
627
Figure 839: Proportion of TCU Parcels Within 500 Feet of IND Parcels
Figure 840: Proportion of VAC Parcels Within 500 Feet of IND Parcels
628
Figure 841: Proportion of AG Parcels Within 500 Feet of MMR Parcels
Figure 842: Proportion of COM Parcels Within 500 Feet of MMR Parcels
629
Figure 843: Proportion of IND Parcels Within 500 Feet of MMR Parcels
Figure 844: Proportion of MMR Parcels Within 500 Feet of MMR Parcels
630
Figure 845: Proportion of MU Parcels Within 500 Feet of MMR Parcels
Figure 846: Proportion of MFR Parcels Within 500 Feet of MMR Parcels
631
Figure 847: Proportion of PUB Parcels Within 500 Feet of MMR Parcels
Figure 848: Proportion of SFDR Parcels Within 500 Feet of MMR Parcels
632
Figure 849: Proportion of TCU Parcels Within 500 Feet of MMR Parcels
Figure 850: Proportion of VAC Parcels Within 500 Feet of MMR Parcels
633
Figure 851: Proportion of AG Parcels Within 500 Feet of MU Parcels
Figure 852: Proportion of COM Parcels Within 500 Feet of MU Parcels
634
Figure 853: Proportion of IND Parcels Within 500 Feet of MU Parcels
Figure 854: Proportion of MMR Parcels Within 500 Feet of MU Parcels
635
Figure 855: Proportion of MU Parcels Within 500 Feet of MU Parcels
Figure 856: Proportion of MFR Parcels Within 500 Feet of MU Parcels
636
Figure 857: Proportion of PUB Parcels Within 500 Feet of MU Parcels
Figure 858: Proportion of SFDR Parcels Within 500 Feet of MU Parcels
637
Figure 859: Proportion of TCU Parcels Within 500 Feet of MU Parcels
Figure 860: Proportion of VAC Parcels Within 500 Feet of MU Parcels
638
Figure 861: Proportion of AG Parcels Within 500 Feet of MFR Parcels
Figure 862: Proportion of COM Parcels Within 500 Feet of MFR Parcels
639
Figure 863: Proportion of IND Parcels Within 500 Feet of MFR Parcels
Figure 864: Proportion of MMR Parcels Within 500 Feet of MFR Parcels
640
Figure 865: Proportion of MU Parcels Within 500 Feet of MFR Parcels
Figure 866: Proportion of MFR Parcels Within 500 Feet of MFR Parcels
641
Figure 867: Proportion of PUB Parcels Within 500 Feet of MFR Parcels
Figure 868: Proportion of SFDR Parcels Within 500 Feet of MFR Parcels
642
Figure 869: Proportion of TCU Parcels Within 500 Feet of MFR Parcels
Figure 870: Proportion of VAC Parcels Within 500 Feet of MFR Parcels
643
Figure 871: Proportion of AG Parcels Within 500 Feet of PUB Parcels
Figure 872: Proportion of COM Parcels Within 500 Feet of PUB Parcels
644
Figure 873: Proportion of IND Parcels Within 500 Feet of PUB Parcels
Figure 874: Proportion of MMR Parcels Within 500 Feet of PUB Parcels
645
Figure 875: Proportion of MU Parcels Within 500 Feet of PUB Parcels
Figure 876: Proportion of MFR Parcels Within 500 Feet of PUB Parcels
646
Figure 877: Proportion of PUB Parcels Within 500 Feet of PUB Parcels
Figure 878: Proportion of SFDR Parcels Within 500 Feet of PUB Parcels
647
Figure 879: Proportion of TCU Parcels Within 500 Feet of PUB Parcels
Figure 880: Proportion of VAC Parcels Within 500 Feet of PUB Parcels
648
Figure 881: Proportion of AG Parcels Within 500 Feet of SFDR Parcels
Figure 882: Proportion of COM Parcels Within 500 Feet of SFDR Parcels
649
Figure 883: Proportion of IND Parcels Within 500 Feet of SFDR Parcels
Figure 884: Proportion of MMR Parcels Within 500 Feet of SFDR Parcels
650
Figure 885: Proportion of MU Parcels Within 500 Feet of SFDR Parcels
Figure 886: Proportion of MFR Parcels Within 500 Feet of SFDR Parcels
651
Figure 887: Proportion of PUB Parcels Within 500 Feet of SFDR Parcels
Figure 888: Proportion of SFDR Parcels Within 500 Feet of SFDR Parcels
652
Figure 889: Proportion of TCU Parcels Within 500 Feet of SFDR Parcels
Figure 890: Proportion of VAC Parcels Within 500 Feet of SFDR Parcels
653
Figure 891: Proportion of AG Parcels Within 500 Feet of TCU Parcels
Figure 892: Proportion of COM Parcels Within 500 Feet of TCU Parcels
654
Figure 893: Proportion of IND Parcels Within 500 Feet of TCU Parcels
Figure 894: Proportion of MMR Parcels Within 500 Feet of TCU Parcels
655
Figure 895: Proportion of MU Parcels Within 500 Feet of TCU Parcels
Figure 896: Proportion of MFR Parcels Within 500 Feet of TCU Parcels
656
Figure 897: Proportion of PUB Parcels Within 500 Feet of TCU Parcels
Figure 898: Proportion of SFDR Parcels Within 500 Feet of TCU Parcels
657
Figure 899: Proportion of TCU Parcels Within 500 Feet of TCU Parcels
Figure 900: Proportion of VAC Parcels Within 500 Feet of TCU Parcels
658
Figure 901: Proportion of AG Parcels Within 500 Feet of UNKN Parcels
Figure 902: Proportion of COM Parcels Within 500 Feet of UNKN Parcels
659
Figure 903: Proportion of IND Parcels Within 500 Feet of UNKN Parcels
Figure 904: Proportion of MMR Parcels Within 500 Feet of UNKN Parcels
660
Figure 905: Proportion of MU Parcels Within 500 Feet of UNKN Parcels
Figure 906: Proportion of MFR Parcels Within 500 Feet of UNKN Parcels
661
Figure 907: Proportion of PUB Parcels Within 500 Feet of UNKN Parcels
Figure 908: Proportion of SFDR Parcels Within 500 Feet of UNKN Parcels
662
Figure 909: Proportion of TCU Parcels Within 500 Feet of UNKN Parcels
Figure 910: Proportion of VAC Parcels Within 500 Feet of UNKN Parcels
663
Figure 911: Proportion of AG Parcels Within 500 Feet of VAC Parcels
Figure 912: Proportion of COM Parcels Within 500 Feet of VAC Parcels
664
Figure 913: Proportion of IND Parcels Within 500 Feet of VAC Parcels
Figure 914: Proportion of MMR Parcels Within 500 Feet of VAC Parcels
665
Figure 915: Proportion of MU Parcels Within 500 Feet of VAC Parcels
Figure 916: Proportion of MFR Parcels Within 500 Feet of VAC Parcels
666
Figure 917: Proportion of PUB Parcels Within 500 Feet of VAC Parcels
Figure 918: Proportion of SFDR Parcels Within 500 Feet of VAC Parcels
667
Figure 919: Proportion of TCU Parcels Within 500 Feet of VAC Parcels
Figure 920: Proportion of VAC Parcels Within 500 Feet of VAC Parcels
668
Appendix J: Bar Charts Showing the Normalized Proportion of Parcels that Have Each Land
Use Within 500 Feet
This appendix provides bar charts showing the normalized proportion of parcels that have each land use within 500 feet.  For
ease of reference, an index with the page number of each land use combination?s chart is provided in Table 12.
Table 12: Bar Chart Index, Normalized Proportion of Parcels that Have Each Land Use Within 500 Feet
% of Parcels with Land Use?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 670 Pg. 670 Pg. 671 Pg. 671 Pg. 672 Pg. 672 Pg. 673 Pg. 673 Pg. 674 Pg. 674
COM Pg. 675 Pg. 675 Pg. 676 Pg. 676 Pg. 677 Pg. 677 Pg. 678 Pg. 678 Pg. 679 Pg. 679
IND Pg. 680 Pg. 680 Pg. 681 Pg. 681 Pg. 682 Pg. 682 Pg. 683 Pg. 683 Pg. 684 Pg. 684
MMR Pg. 685 Pg. 685 Pg. 686 Pg. 686 Pg. 687 Pg. 687 Pg. 688 Pg. 688 Pg. 689 Pg. 689
MU Pg. 690 Pg. 690 Pg. 691 Pg. 691 Pg. 692 Pg. 692 Pg. 693 Pg. 693 Pg. 694 Pg. 694
MFR Pg. 695 Pg. 695 Pg. 696 Pg. 696 Pg. 697 Pg. 697 Pg. 698 Pg. 698 Pg. 699 Pg. 699
PUB Pg. 700 Pg. 700 Pg. 701 Pg. 701 Pg. 702 Pg. 702 Pg. 703 Pg. 703 Pg. 704 Pg. 704
SFDR Pg. 705 Pg. 705 Pg. 706 Pg. 706 Pg. 707 Pg. 707 Pg. 708 Pg. 708 Pg. 709 Pg. 709
TCU Pg. 710 Pg. 710 Pg. 711 Pg. 711 Pg. 712 Pg. 712 Pg. 713 Pg. 713 Pg. 714 Pg. 714
UNKN Pg. 715 Pg. 715 Pg. 716 Pg. 716 Pg. 717 Pg. 717 Pg. 718 Pg. 718 Pg. 719 Pg. 719
VAC Pg. 720 Pg. 720 Pg. 721 Pg. 721 Pg. 722 Pg. 722 Pg. 723 Pg. 723 Pg. 724 Pg. 724
669
Within 500 Feet of?
Figure 921: Proportion of AG Parcels Within 500 Feet of AG Parcels (Normalized)
Figure 922: Proportion of COM Parcels Within 500 Feet of AG Parcels (Normalized)
670
Figure 923: Proportion of IND Parcels Within 500 Feet of AG Parcels (Normalized)
Figure 924: Proportion of MMR Parcels Within 500 Feet of AG Parcels (Normalized)
671
Figure 925: Proportion of MU Parcels Within 500 Feet of AG Parcels (Normalized)
Figure 926: Proportion of MFR Parcels Within 500 Feet of AG Parcels (Normalized)
672
Figure 927: Proportion of PUB Parcels Within 500 Feet of AG Parcels (Normalized)
Figure 928: Proportion of SFDR Parcels Within 500 Feet of AG Parcels (Normalized)
673
Figure 929: Proportion of TCU Parcels Within 500 Feet of AG Parcels (Normalized)
Figure 930: Proportion of VAC Parcels Within 500 Feet of AG Parcels (Normalized)
674
Figure 931: Proportion of AG Parcels Within 500 Feet of COM Parcels (Normalized)
Figure 932: Proportion of COM Parcels Within 500 Feet of COM Parcels (Normalized)
675
Figure 933: Proportion of IND Parcels Within 500 Feet of COM Parcels (Normalized)
Figure 934: Proportion of MMR Parcels Within 500 Feet of COM Parcels (Normalized)
676
Figure 935: Proportion of MU Parcels Within 500 Feet of COM Parcels (Normalized)
Figure 936: Proportion of MFR Parcels Within 500 Feet of COM Parcels (Normalized)
677
Figure 937: Proportion of PUB Parcels Within 500 Feet of COM Parcels (Normalized)
Figure 938: Proportion of SFDR Parcels Within 500 Feet of COM Parcels (Normalized)
678
Figure 939: Proportion of TCU Parcels Within 500 Feet of COM Parcels (Normalized)
Figure 940: Proportion of VAC Parcels Within 500 Feet of COM Parcels (Normalized)
679
Figure 941: Proportion of AG Parcels Within 500 Feet of IND Parcels (Normalized)
Figure 942: Proportion of COM Parcels Within 500 Feet of IND Parcels (Normalized)
680
Figure 943: Proportion of IND Parcels Within 500 Feet of IND Parcels (Normalized)
Figure 944: Proportion of MMR Parcels Within 500 Feet of IND Parcels (Normalized)
681
Figure 945: Proportion of MU Parcels Within 500 Feet of IND Parcels (Normalized)
Figure 946: Proportion of MFR Parcels Within 500 Feet of IND Parcels (Normalized)
682
Figure 947: Proportion of PUB Parcels Within 500 Feet of IND Parcels (Normalized)
Figure 948: Proportion of SFDR Parcels Within 500 Feet of IND Parcels (Normalized)
683
Figure 949: Proportion of TCU Parcels Within 500 Feet of IND Parcels (Normalized)
Figure 950: Proportion of VAC Parcels Within 500 Feet of IND Parcels (Normalized)
684
Figure 951: Proportion of AG Parcels Within 500 Feet of MMR Parcels (Normalized)
Figure 952: Proportion of COM Parcels Within 500 Feet of MMR Parcels (Normalized)
685
Figure 953: Proportion of IND Parcels Within 500 Feet of MMR Parcels (Normalized)
Figure 954: Proportion of MMR Parcels Within 500 Feet of MMR Parcels (Normalized)
686
Figure 955: Proportion of MU Parcels Within 500 Feet of MMR Parcels (Normalized)
Figure 956: Proportion of MFR Parcels Within 500 Feet of MMR Parcels (Normalized)
687
Figure 957: Proportion of PUB Parcels Within 500 Feet of MMR Parcels (Normalized)
Figure 958: Proportion of SFDR Parcels Within 500 Feet of MMR Parcels (Normalized)
688
Figure 959: Proportion of TCU Parcels Within 500 Feet of MMR Parcels (Normalized)
Figure 960: Proportion of VAC Parcels Within 500 Feet of MMR Parcels (Normalized)
689
Figure 961: Proportion of AG Parcels Within 500 Feet of MU Parcels (Normalized)
Figure 962: Proportion of COM Parcels Within 500 Feet of MU Parcels (Normalized)
690
Figure 963: Proportion of IND Parcels Within 500 Feet of MU Parcels (Normalized)
Figure 964: Proportion of MMR Parcels Within 500 Feet of MU Parcels (Normalized)
691
Figure 965: Proportion of MU Parcels Within 500 Feet of MU Parcels (Normalized)
Figure 966: Proportion of MFR Parcels Within 500 Feet of MU Parcels (Normalized)
692
Figure 967: Proportion of PUB Parcels Within 500 Feet of MU Parcels (Normalized)
Figure 968: Proportion of SFDR Parcels Within 500 Feet of MU Parcels (Normalized)
693
Figure 969: Proportion of TCU Parcels Within 500 Feet of MU Parcels (Normalized)
Figure 970: Proportion of VAC Parcels Within 500 Feet of MU Parcels (Normalized)
694
Figure 971: Proportion of AG Parcels Within 500 Feet of MFR Parcels (Normalized)
Figure 972: Proportion of COM Parcels Within 500 Feet of MFR Parcels (Normalized)
695
Figure 973: Proportion of IND Parcels Within 500 Feet of MFR Parcels (Normalized)
Figure 974: Proportion of MMR Parcels Within 500 Feet of MFR Parcels (Normalized)
696
Figure 975: Proportion of MU Parcels Within 500 Feet of MFR Parcels (Normalized)
Figure 976: Proportion of MFR Parcels Within 500 Feet of MFR Parcels (Normalized)
697
Figure 977: Proportion of PUB Parcels Within 500 Feet of MFR Parcels (Normalized)
Figure 978: Proportion of SFDR Parcels Within 500 Feet of MFR Parcels (Normalized)
698
Figure 979: Proportion of TCU Parcels Within 500 Feet of MFR Parcels (Normalized)
Figure 980: Proportion of VAC Parcels Within 500 Feet of MFR Parcels (Normalized)
699
Figure 981: Proportion of AG Parcels Within 500 Feet of PUB Parcels (Normalized)
Figure 982: Proportion of COM Parcels Within 500 Feet of PUB Parcels (Normalized)
700
Figure 983: Proportion of IND Parcels Within 500 Feet of PUB Parcels (Normalized)
Figure 984: Proportion of MMR Parcels Within 500 Feet of PUB Parcels (Normalized)
701
Figure 985: Proportion of MU Parcels Within 500 Feet of PUB Parcels (Normalized)
Figure 986: Proportion of MFR Parcels Within 500 Feet of PUB Parcels (Normalized)
702
Figure 987: Proportion of PUB Parcels Within 500 Feet of PUB Parcels (Normalized)
Figure 988: Proportion of SFDR Parcels Within 500 Feet of PUB Parcels (Normalized)
703
Figure 989: Proportion of TCU Parcels Within 500 Feet of PUB Parcels (Normalized)
Figure 990: Proportion of VAC Parcels Within 500 Feet of PUB Parcels (Normalized)
704
Figure 991: Proportion of AG Parcels Within 500 Feet of SFDR Parcels (Normalized)
Figure 992: Proportion of COM Parcels Within 500 Feet of SFDR Parcels (Normalized)
705
Figure 993: Proportion of IND Parcels Within 500 Feet of SFDR Parcels (Normalized)
Figure 994: Proportion of MMR Parcels Within 500 Feet of SFDR Parcels (Normalized)
706
Figure 995: Proportion of MU Parcels Within 500 Feet of SFDR Parcels (Normalized)
Figure 996: Proportion of MFR Parcels Within 500 Feet of SFDR Parcels (Normalized)
707
Figure 997: Proportion of PUB Parcels Within 500 Feet of SFDR Parcels (Normalized)
Figure 998: Proportion of SFDR Parcels Within 500 Feet of SFDR Parcels (Normalized)
708
Figure 999: Proportion of TCU Parcels Within 500 Feet of SFDR Parcels (Normalized)
Figure 1000: Proportion of VAC Parcels Within 500 Feet of SFDR Parcels (Normalized)
709
Figure 1001: Proportion of AG Parcels Within 500 Feet of TCU Parcels (Normalized)
Figure 1002: Proportion of COM Parcels Within 500 Feet of TCU Parcels (Normalized)
710
Figure 1003: Proportion of IND Parcels Within 500 Feet of TCU Parcels (Normalized)
Figure 1004: Proportion of MMR Parcels Within 500 Feet of TCU Parcels (Normalized)
711
Figure 1005: Proportion of MU Parcels Within 500 Feet of TCU Parcels (Normalized)
Figure 1006: Proportion of MFR Parcels Within 500 Feet of TCU Parcels (Normalized)
712
Figure 1007: Proportion of PUB Parcels Within 500 Feet of TCU Parcels (Normalized)
Figure 1008: Proportion of SFDR Parcels Within 500 Feet of TCU Parcels (Normalized)
713
Figure 1009: Proportion of TCU Parcels Within 500 Feet of TCU Parcels (Normalized)
Figure 1010: Proportion of VAC Parcels Within 500 Feet of TCU Parcels (Normalized)
714
Figure 1011: Proportion of AG Parcels Within 500 Feet of UNKN Parcels (Normalized)
Figure 1012: Proportion of COM Parcels Within 500 Feet of UNKN Parcels (Normalized)
715
Figure 1013: Proportion of IND Parcels Within 500 Feet of UNKN Parcels (Normalized)
Figure 1014: Proportion of MMR Parcels Within 500 Feet of UNKN Parcels (Normalized)
716
Figure 1015: Proportion of MU Parcels Within 500 Feet of UNKN Parcels (Normalized)
Figure 1016: Proportion of MFR Parcels Within 500 Feet of UNKN Parcels (Normalized)
717
Figure 1017: Proportion of PUB Parcels Within 500 Feet of UNKN Parcels (Normalized)
Figure 1018: Proportion of SFDR Parcels Within 500 Feet of UNKN Parcels (Normalized)
718
Figure 1019: Proportion of TCU Parcels Within 500 Feet of UNKN Parcels (Normalized)
Figure 1020: Proportion of VAC Parcels Within 500 Feet of UNKN Parcels (Normalized)
719
Figure 1021: Proportion of AG Parcels Within 500 Feet of VAC Parcels (Normalized)
Figure 1022: Proportion of COM Parcels Within 500 Feet of VAC Parcels (Normalized)
720
Figure 1023: Proportion of IND Parcels Within 500 Feet of VAC Parcels (Normalized)
Figure 1024: Proportion of MMR Parcels Within 500 Feet of VAC Parcels (Normalized)
721
Figure 1025: Proportion of MU Parcels Within 500 Feet of VAC Parcels (Normalized)
Figure 1026: Proportion of MFR Parcels Within 500 Feet of VAC Parcels (Normalized)
722
Figure 1027: Proportion of PUB Parcels Within 500 Feet of VAC Parcels (Normalized)
Figure 1028: Proportion of SFDR Parcels Within 500 Feet of VAC Parcels (Normalized)
723
Figure 1029: Proportion of TCU Parcels Within 500 Feet of VAC Parcels (Normalized)
Figure 1030: Proportion of VAC Parcels Within 500 Feet of VAC Parcels (Normalized)
724
Appendix K: Bar Charts Showing the Proportion of Parcels That Have Zero, One, Two, Three,
Four, Five, Six, Seven, Eight, or Nine Other Land Uses Within 500 Feet
This appendix provides bar charts showing the proportion of parcels that have zero, one, two, three, four, five, six, seven,
eight, or nine other land uses within 500 feet.  For ease of reference, an index with the page number of each land use combination?s
chart is provided in Table 13.  Note that charts showing nine other land uses nearby are only provided for the land use classes that
show at least one instance of this situation across the study cities.
Table 13: Bar Chart Index, Proportion of Parcels That Have Zero, One, Two, Three, Four, Five, Six, Seven, Eight, or Nine Other Land Uses Within 500
Feet
Number of Other Land Uses Within 500 Feet
0 1 2 3 4 5 6 7 8 9
AG Pg. 726 Pg. 726 Pg. 727 Pg. 727 Pg. 728 Pg. 728 Pg. 729 Pg. 729 Pg. 730 -
COM Pg. 730 Pg. 731 Pg. 731 Pg. 732 Pg. 732 Pg. 733 Pg. 733 Pg. 734 Pg. 734 -
IND Pg. 735 Pg. 735 Pg. 736 Pg. 736 Pg. 737 Pg. 737 Pg. 738 Pg. 738 Pg. 739 -
MMR Pg. 739 Pg. 740 Pg. 740 Pg. 741 Pg. 741 Pg. 742 Pg. 742 Pg. 743 Pg. 743 -
MU Pg. 744 Pg. 744 Pg. 745 Pg. 745 Pg. 746 Pg. 746 Pg. 747 Pg. 747 Pg. 748 -
MFR Pg. 748 Pg. 749 Pg. 749 Pg. 750 Pg. 750 Pg. 751 Pg. 751 Pg. 752 Pg. 752 -
PUB Pg. 753 Pg. 753 Pg. 754 Pg. 754 Pg. 755 Pg. 755 Pg. 756 Pg. 756 Pg. 757 Pg. 757
SFDR Pg. 758 Pg. 758 Pg. 759 Pg. 759 Pg. 760 Pg. 760 Pg. 761 Pg. 761 Pg. 762 -
TCU Pg. 762 Pg. 763 Pg. 763 Pg. 764 Pg. 764 Pg. 765 Pg. 765 Pg. 766 Pg. 766 Pg. 767
UNKN
VAC Pg. 767 Pg. 768 Pg. 768 Pg. 769 Pg. 769 Pg. 770 Pg. 770 Pg. 771 Pg. 771 -
725
Figure 1031: Proportion of AG Parcels with Zero Other Land Uses Within 500 Feet
Figure 1032: Proportion of AG Parcels with One Other Land Use Within 500 Feet
726
Figure 1033: Proportion of AG Parcels with Two Other Land Uses Within 500 Feet
Figure 1034: Proportion of AG Parcels with Three Other Land Uses Within 500 Feet
727
Figure 1035: Proportion of AG Parcels with Four Other Land Uses Within 500 Feet
Figure 1036: Proportion of AG Parcels with Five Other Land Uses Within 500 Feet
728
Figure 1037: Proportion of AG Parcels with Six Other Land Uses Within 500 Feet
Figure 1038: Proportion of AG Parcels with Seven Other Land Uses Within 500 Feet
729
Figure 1039: Proportion of AG Parcels with Eight Other Land Uses Within 500 Feet
Figure 1040: Proportion of COM Parcels with Zero Other Land Uses Within 500 Feet
730
Figure 1041: Proportion of COM Parcels with One Other Land Use Within 500 Feet
Figure 1042: Proportion of COM Parcels with Two Other Land Uses Within 500 Feet
731
Figure 1043: Proportion of COM Parcels with Three Other Land Uses Within 500 Feet
Figure 1044: Proportion of COM Parcels with Four Other Land Uses Within 500 Feet
732
Figure 1045: Proportion of COM Parcels with Five Other Land Uses Within 500 Feet
Figure 1046: Proportion of COM Parcels with Six Other Land Uses Within 500 Feet
733
Figure 1047: Proportion of COM Parcels with Seven Other Land Uses Within 500 Feet
Figure 1048: Proportion of COM Parcels with Eight Other Land Uses Within 500 Feet
734
Figure 1049: Proportion of IND Parcels with Zero Other Land Uses Within 500 Feet
Figure 1050: Proportion of IND Parcels with One Other Land Use Within 500 Feet
735
Figure 1051: Proportion of IND Parcels with Two Other Land Uses Within 500 Feet
Figure 1052: Proportion of IND Parcels with Three Other Land Uses Within 500 Feet
736
Figure 1053: Proportion of IND Parcels with Four Other Land Uses Within 500 Feet
Figure 1054: Proportion of IND Parcels with Five Other Land Uses Within 500 Feet
737
Figure 1055: Proportion of IND Parcels with Six Other Land Uses Within 500 Feet
Figure 1056: Proportion of IND Parcels with Seven Other Land Uses Within 500 Feet
738
Figure 1057: Proportion of IND Parcels with Eight Other Land Uses Within 500 Feet
Figure 1058: Proportion of MMR Parcels with Zero Other Land Uses Within 500 Feet
739
Figure 1059: Proportion of MMR Parcels with One Other Land Use Within 500 Feet
Figure 1060: Proportion of MMR Parcels with Two Other Land Uses Within 500 Feet
740
Figure 1061: Proportion of MMR Parcels with Three Other Land Uses Within 500 Feet
Figure 1062: Proportion of MMR Parcels with Four Other Land Uses Within 500 Feet
741
Figure 1063: Proportion of MMR Parcels with Five Other Land Uses Within 500 Feet
Figure 1064: Proportion of MMR Parcels with Six Other Land Uses Within 500 Feet
742
Figure 1065: Proportion of MMR Parcels with Seven Other Land Uses Within 500 Feet
Figure 1066: Proportion of MMR Parcels with Eight Other Land Uses Within 500 Feet
743
Figure 1067: Proportion of MU Parcels with Zero Other Land Uses Within 500 Feet
Figure 1068: Proportion of MU Parcels with One Other Land Use Within 500 Feet
744
Figure 1069: Proportion of MU Parcels with Two Other Land Uses Within 500 Feet
Figure 1070: Proportion of MU Parcels with Three Other Land Uses Within 500 Feet
745
Figure 1071: Proportion of MU Parcels with Four Other Land Uses Within 500 Feet
Figure 1072: Proportion of MU Parcels with Five Other Land Uses Within 500 Feet
746
Figure 1073: Proportion of MU Parcels with Six Other Land Uses Within 500 Feet
Figure 1074: Proportion of MU Parcels with Seven Other Land Uses Within 500 Feet
747
Figure 1075: Proportion of MU Parcels with Eight Other Land Uses Within 500 Feet
Figure 1076: Proportion of MFR Parcels with Zero Other Land Uses Within 500 Feet
748
Figure 1077: Proportion of MFR Parcels with One Other Land Use Within 500 Feet
Figure 1078: Proportion of MFR Parcels with Two Other Land Uses Within 500 Feet
749
Figure 1079: Proportion of MFR Parcels with Three Other Land Uses Within 500 Feet
Figure 1080: Proportion of MFR Parcels with Four Other Land Uses Within 500 Feet
750
Figure 1081: Proportion of MFR Parcels with Five Other Land Uses Within 500 Feet
Figure 1082: Proportion of MFR Parcels with Six Other Land Uses Within 500 Feet
751
Figure 1083: Proportion of MFR Parcels with Seven Other Land Uses Within 500 Feet
Figure 1084: Proportion of MFR Parcels with Eight Other Land Uses Within 500 Feet
752
Figure 1085: Proportion of PUB Parcels with Zero Other Land Uses Within 500 Feet
Figure 1086: Proportion of PUB Parcels with One Other Land Use Within 500 Feet
753
Figure 1087: Proportion of PUB Parcels with Two Other Land Uses Within 500 Feet
Figure 1088: Proportion of PUB Parcels with Three Other Land Uses Within 500 Feet
754
Figure 1089: Proportion of PUB Parcels with Four Other Land Uses Within 500 Feet
Figure 1090: Proportion of PUB Parcels with Five Other Land Uses Within 500 Feet
755
Figure 1091: Proportion of PUB Parcels with Six Other Land Uses Within 500 Feet
Figure 1092: Proportion of PUB Parcels with Seven Other Land Uses Within 500 Feet
756
Figure 1093: Proportion of PUB Parcels with Eight Other Land Uses Within 500 Feet
Figure 1094: Proportion of PUB Parcels with Nine Other Land Uses Within 500 Feet
757
Figure 1095: Proportion of SFDR Parcels with Zero Other Land Uses Within 500 Feet
Figure 1096: Proportion of SFDR Parcels with One Other Land Use Within 500 Feet
758
Figure 1097: Proportion of SFDR Parcels with Two Other Land Uses Within 500 Feet
Figure 1098: Proportion of SFDR Parcels with Three Other Land Uses Within 500 Feet
759
Figure 1099: Proportion of SFDR Parcels with Four Other Land Uses Within 500 Feet
Figure 1100: Proportion of SFDR Parcels with Five Other Land Uses Within 500 Feet
760
Figure 1101: Proportion of SFDR Parcels with Six Other Land Uses Within 500 Feet
Figure 1102: Proportion of SFDR Parcels with Seven Other Land Uses Within 500 Feet
761
Figure 1103: Proportion of SFDR Parcels with Eight Other Land Uses Within 500 Feet
Figure 1104: Proportion of TCU Parcels with Zero Other Land Uses Within 500 Feet
762
Figure 1105: Proportion of TCU Parcels with One Other Land Use Within 500 Feet
Figure 1106: Proportion of TCU Parcels with Two Other Land Uses Within 500 Feet
763
Figure 1107: Proportion of TCU Parcels with Three Other Land Uses Within 500 Feet
Figure 1108: Proportion of TCU Parcels with Four Other Land Uses Within 500 Feet
764
Figure 1109: Proportion of TCU Parcels with Five Other Land Uses Within 500 Feet
Figure 1110: Proportion of TCU Parcels with Six Other Land Uses Within 500 Feet
765
Figure 1111: Proportion of TCU Parcels with Seven Other Land Uses Within 500 Feet
Figure 1112: Proportion of TCU Parcels with Eight Other Land Uses Within 500 Feet
766
Figure 1113: Proportion of TCU Parcels with Nine Other Land Uses Within 500 Feet
Figure 1114: Proportion of VAC Parcels with Zero Other Land Uses Within 500 Feet
767
Figure 1115: Proportion of VAC Parcels with One Other Land Use Within 500 Feet
Figure 1116: Proportion of VAC Parcels with Two Other Land Uses Within 500 Feet
768
Figure 1117: Proportion of VAC Parcels with Three Other Land Uses Within 500 Feet
Figure 1118: Proportion of VAC Parcels with Four Other Land Uses Within 500 Feet
769
Figure 1119: Proportion of VAC Parcels with Five Other Land Uses Within 500 Feet
Figure 1120: Proportion of VAC Parcels with Six Other Land Uses Within 500 Feet
770
Figure 1121: Proportion of VAC Parcels with Seven Other Land Uses Within 500 Feet
Figure 1122: Proportion of VAC Parcels with Eight Other Land Uses Within 500 Feet
771
Appendix L: Bar Charts Showing the Normalized Proportion of Parcels That Have Zero, One,
Two, Three, Four, Five, Six, Seven, Eight, or Nine Other Land Uses Within 500 Feet
This appendix provides bar charts showing the normalized proportion of parcels that have zero, one, two, three, four, five, six,
seven, eight, or nine other land uses within 500 feet.  For ease of reference, an index with the page number of each land use
combination?s chart is provided in Table 14.  Note that charts showing nine other land uses nearby are only provided for the land use
classes that show at least one instance of this situation across the study cities.
Table 14: Bar Chart Index, Normalized Proportion of Parcels That Have Zero, One, Two, Three, Four, Five, Six, Seven, Eight, or Nine Other Land
Uses Within 500 Feet
Number of Other Land Uses Within 500 Feet
0 1 2 3 4 5 6 7 8 9
AG Pg. 773 Pg. 773 Pg. 774 Pg. 774 Pg. 775 Pg. 775 Pg. 776 Pg. 776 Pg. 777 -
COM Pg. 777 Pg. 778 Pg. 778 Pg. 779 Pg. 779 Pg. 780 Pg. 780 Pg. 781 Pg. 781 -
IND Pg. 782 Pg. 782 Pg. 783 Pg. 783 Pg. 784 Pg. 784 Pg. 785 Pg. 785 Pg. 786 -
MMR Pg. 786 Pg. 787 Pg. 787 Pg. 788 Pg. 788 Pg. 789 Pg. 789 Pg. 790 Pg. 790 -
MU Pg. 791 Pg. 791 Pg. 792 Pg. 792 Pg. 793 Pg. 793 Pg. 794 Pg. 794 Pg. 795 -
MFR Pg. 795 Pg. 796 Pg. 796 Pg. 797 Pg. 797 Pg. 798 Pg. 798 Pg. 799 Pg. 799 -
PUB Pg. 800 Pg. 800 Pg. 801 Pg. 801 Pg. 802 Pg. 802 Pg. 803 Pg. 803 Pg. 804 Pg. 804
SFDR Pg. 805 Pg. 805 Pg. 806 Pg. 806 Pg. 807 Pg. 807 Pg. 808 Pg. 808 Pg. 809 -
TCU Pg. 809 Pg. 810 Pg. 810 Pg. 811 Pg. 811 Pg. 812 Pg. 812 Pg. 813 Pg. 813 Pg. 814
UNKN
VAC Pg. 814 Pg. 815 Pg. 815 Pg. 816 Pg. 816 Pg. 817 Pg. 817 Pg. 818 Pg. 818 -
772
Figure 1123: Proportion of AG Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
Figure 1124: Proportion of AG Parcels with One Other Land Use Within 500 Feet (Normalized)
773
Figure 1125: Proportion of AG Parcels with Two Other Land Uses Within 500 Feet (Normalized)
Figure 1126: Proportion of AG Parcels with Three Other Land Uses Within 500 Feet (Normalized)
774
Figure 1127: Proportion of AG Parcels with Four Other Land Uses Within 500 Feet (Normalized)
Figure 1128: Proportion of AG Parcels with Five Other Land Uses Within 500 Feet (Normalized)
775
Figure 1129: Proportion of AG Parcels with Six Other Land Uses Within 500 Feet (Normalized)
Figure 1130: Proportion of AG Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
776
Figure 1131: Proportion of AG Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
Figure 1132: Proportion of COM Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
777
Figure 1133: Proportion of COM Parcels with One Other Land Use Within 500 Feet (Normalized)
Figure 1134: Proportion of COM Parcels with Two Other Land Uses Within 500 Feet (Normalized)
778
Figure 1135: Proportion of COM Parcels with Three Other Land Uses Within 500 Feet (Normalized)
Figure 1136: Proportion of COM Parcels with Four Other Land Uses Within 500 Feet (Normalized)
779
Figure 1137: Proportion of COM Parcels with Five Other Land Uses Within 500 Feet (Normalized)
Figure 1138: Proportion of COM Parcels with Six Other Land Uses Within 500 Feet (Normalized)
780
Figure 1139: Proportion of COM Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
Figure 1140: Proportion of COM Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
781
Figure 1141: Proportion of IND Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
Figure 1142: Proportion of IND Parcels with One Other Land Use Within 500 Feet (Normalized)
782
Figure 1143: Proportion of IND Parcels with Two Other Land Uses Within 500 Feet (Normalized)
Figure 1144: Proportion of IND Parcels with Three Other Land Uses Within 500 Feet (Normalized)
783
Figure 1145: Proportion of IND Parcels with Four Other Land Uses Within 500 Feet (Normalized)
Figure 1146: Proportion of IND Parcels with Five Other Land Uses Within 500 Feet (Normalized)
784
Figure 1147: Proportion of IND Parcels with Six Other Land Uses Within 500 Feet (Normalized)
Figure 1148: Proportion of IND Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
785
Figure 1149: Proportion of IND Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
Figure 1150: Proportion of MMR Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
786
Figure 1151: Proportion of MMR Parcels with One Other Land Use Within 500 Feet (Normalized)
Figure 1152: Proportion of MMR Parcels with Two Other Land Uses Within 500 Feet (Normalized)
787
Figure 1153: Proportion of MMR Parcels with Three Other Land Uses Within 500 Feet (Normalized)
Figure 1154: Proportion of MMR Parcels with Four Other Land Uses Within 500 Feet (Normalized)
788
Figure 1155: Proportion of MMR Parcels with Five Other Land Uses Within 500 Feet (Normalized)
Figure 1156: Proportion of MMR Parcels with Six Other Land Uses Within 500 Feet (Normalized)
789
Figure 1157: Proportion of MMR Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
Figure 1158: Proportion of MMR Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
790
Figure 1159: Proportion of MU Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
Figure 1160: Proportion of MU Parcels with One Other Land Use Within 500 Feet (Normalized)
791
Figure 1161: Proportion of MU Parcels with Two Other Land Uses Within 500 Feet (Normalized)
Figure 1162: Proportion of MU Parcels with Three Other Land Uses Within 500 Feet (Normalized)
792
Figure 1163: Proportion of MU Parcels with Four Other Land Uses Within 500 Feet (Normalized)
Figure 1164: Proportion of MU Parcels with Five Other Land Uses Within 500 Feet (Normalized)
793
Figure 1165: Proportion of MU Parcels with Six Other Land Uses Within 500 Feet (Normalized)
Figure 1166: Proportion of MU Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
794
Figure 1167: Proportion of MU Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
Figure 1168: Proportion of MFR Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
795
Figure 1169: Proportion of MFR Parcels with One Other Land Use Within 500 Feet (Normalized)
Figure 1170: Proportion of MFR Parcels with Two Other Land Uses Within 500 Feet (Normalized)
796
Figure 1171: Proportion of MFR Parcels with Three Other Land Uses Within 500 Feet (Normalized)
Figure 1172: Proportion of MFR Parcels with Four Other Land Uses Within 500 Feet (Normalized)
797
Figure 1173: Proportion of MFR Parcels with Five Other Land Uses Within 500 Feet (Normalized)
Figure 1174: Proportion of MFR Parcels with Six Other Land Uses Within 500 Feet (Normalized)
798
Figure 1175: Proportion of MFR Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
Figure 1176: Proportion of MFR Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
799
Figure 1177: Proportion of PUB Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
Figure 1178: Proportion of PUB Parcels with One Other Land Use Within 500 Feet (Normalized)
800
Figure 1179: Proportion of PUB Parcels with Two Other Land Uses Within 500 Feet (Normalized)
Figure 1180: Proportion of PUB Parcels with Three Other Land Uses Within 500 Feet (Normalized)
801
Figure 1181: Proportion of PUB Parcels with Four Other Land Uses Within 500 Feet (Normalized)
Figure 1182: Proportion of PUB Parcels with Five Other Land Uses Within 500 Feet (Normalized)
802
Figure 1183: Proportion of PUB Parcels with Six Other Land Uses Within 500 Feet (Normalized)
Figure 1184: Proportion of PUB Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
803
Figure 1185: Proportion of PUB Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
Figure 1186: Proportion of PUB Parcels with Nine Other Land Uses Within 500 Feet (Normalized)
804
Figure 1187: Proportion of SFDR Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
Figure 1188: Proportion of SFDR Parcels with One Other Land Use Within 500 Feet (Normalized)
805
Figure 1189: Proportion of SFDR Parcels with Two Other Land Uses Within 500 Feet (Normalized)
Figure 1190: Proportion of SFDR Parcels with Three Other Land Uses Within 500 Feet (Normalized)
806
Figure 1191: Proportion of SFDR Parcels with Four Other Land Uses Within 500 Feet (Normalized)
Figure 1192: Proportion of SFDR Parcels with Five Other Land Uses Within 500 Feet (Normalized)
807
Figure 1193: Proportion of SFDR Parcels with Six Other Land Uses Within 500 Feet (Normalized)
Figure 1194: Proportion of SFDR Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
808
Figure 1195: Proportion of SFDR Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
Figure 1196: Proportion of TCU Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
809
Figure 1197: Proportion of TCU Parcels with One Other Land Use Within 500 Feet (Normalized)
Figure 1198: Proportion of TCU Parcels with Two Other Land Uses Within 500 Feet (Normalized)
810
Figure 1199: Proportion of TCU Parcels with Three Other Land Uses Within 500 Feet (Normalized)
Figure 1200: Proportion of TCU Parcels with Four Other Land Uses Within 500 Feet (Normalized)
811
Figure 1201: Proportion of TCU Parcels with Five Other Land Uses Within 500 Feet (Normalized)
Figure 1202: Proportion of TCU Parcels with Six Other Land Uses Within 500 Feet (Normalized)
812
Figure 1203: Proportion of TCU Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
Figure 1204: Proportion of TCU Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
813
Figure 1205: Proportion of TCU Parcels with Nine Other Land Uses Within 500 Feet (Normalized)
Figure 1206: Proportion of VAC Parcels with Zero Other Land Uses Within 500 Feet (Normalized)
814
Figure 1207: Proportion of VAC Parcels with One Other Land Use Within 500 Feet (Normalized)
Figure 1208: Proportion of VAC Parcels with Two Other Land Uses Within 500 Feet (Normalized)
815
Figure 1209: Proportion of VAC Parcels with Three Other Land Uses Within 500 Feet (Normalized)
Figure 1210: Proportion of VAC Parcels with Four Other Land Uses Within 500 Feet (Normalized)
816
Figure 1211: Proportion of VAC Parcels with Five Other Land Uses Within 500 Feet (Normalized)
Figure 1212: Proportion of VAC Parcels with Six Other Land Uses Within 500 Feet (Normalized)
817
Figure 1213: Proportion of VAC Parcels with Seven Other Land Uses Within 500 Feet (Normalized)
Figure 1214: Proportion of VAC Parcels with Eight Other Land Uses Within 500 Feet (Normalized)
818
Appendix M: Bar Charts Showing the Average Distance Between the Nearest Parcels of Each
Land Use Class
This appendix provides bar charts showing, for each land use class, the average distance to the nearest parcel of each land use.
For ease of reference, an index with the page number of each land use combination?s chart is provided in Table 15.
Table 15: Bar Chart Index, Average Distance Between the Nearest Parcels of Each Land Use Class
Average Distance From Parcels With Land Use (LU) Class?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 820 Pg. 820 Pg. 821 Pg. 821 Pg. 822 Pg. 822 Pg. 823 Pg. 823 Pg. 824 Pg. 824
COM Pg. 825 Pg. 825 Pg. 826 Pg. 826 Pg. 827 Pg. 827 Pg. 828 Pg. 828 Pg. 829 Pg. 829
IND Pg. 830 Pg. 830 Pg. 831 Pg. 831 Pg. 832 Pg. 832 Pg. 833 Pg. 833 Pg. 834 Pg. 834
MMR Pg. 835 Pg. 835 Pg. 836 Pg. 836 Pg. 837 Pg. 837 Pg. 838 Pg. 838 Pg. 839 Pg. 839
MU Pg. 840 Pg. 840 Pg. 841 Pg. 841 Pg. 842 Pg. 842 Pg. 843 Pg. 843 Pg. 844 Pg. 844
MFR Pg. 845 Pg. 845 Pg. 846 Pg. 846 Pg. 847 Pg. 847 Pg. 848 Pg. 848 Pg. 849 Pg. 849
PUB Pg.850 Pg. 850 Pg. 851 Pg. 851 Pg. 852 Pg. 852 Pg. 853 Pg. 853 Pg. 854 Pg. 854
SFDR Pg. 855 Pg. 855 Pg. 856 Pg. 856 Pg. 857 Pg. 857 Pg. 858 Pg. 858 Pg. 859 Pg. 859
TCU Pg. 860 Pg. 860 Pg. 861 Pg. 861 Pg. 862 Pg. 862 Pg. 863 Pg. 863 Pg. 864 Pg. 864
UNKN Pg. 865 Pg. 865 Pg. 866 Pg. 866 Pg. 867 Pg. 867 Pg. 868 Pg. 868 Pg. 869 Pg. 869
VAC Pg. 870 Pg. 870 Pg. 871 Pg. 871 Pg. 872 Pg. 872 Pg. 873 Pg. 873 Pg. 874 Pg. 874
819
To Closest Parcel with LU?
Figure 1215: Average Distance from AG Parcels to the Nearest AG Parcel
Figure 1216: Average Distance from COM Parcels to the Nearest AG Parcel
820
Figure 1217: Average Distance from IND Parcels to the Nearest AG Parcel
Figure 1218: Average Distance from MMR Parcels to the Nearest AG Parcel
821
Figure 1219: Average Distance from MU Parcels to the Nearest AG Parcel
Figure 1220: Average Distance from MFR Parcels to the Nearest AG Parcel
822
Figure 1221: Average Distance from PUB Parcels to the Nearest AG Parcel
Figure 1222: Average Distance from SFDR Parcels to the Nearest AG Parcel
823
Figure 1223: Average Distance from TCU Parcels to the Nearest AG Parcel
Figure 1224: Average Distance from VAC Parcels to the Nearest AG Parcel
824
Figure 1225: Average Distance from AG Parcels to the Nearest COM Parcel
Figure 1226: Average Distance from COM Parcels to the Nearest COM Parcel
825
Figure 1227: Average Distance from IND Parcels to the Nearest COM Parcel
Figure 1228: Average Distance from MMR Parcels to the Nearest COM Parcel
826
Figure 1229: Average Distance from MU Parcels to the Nearest COM Parcel
Figure 1230: Average Distance from MFR Parcels to the Nearest COM Parcel
827
Figure 1231: Average Distance from PUB Parcels to the Nearest COM Parcel
Figure 1232: Average Distance from SFDR Parcels to the Nearest COM Parcel
828
Figure 1233: Average Distance from TCU Parcels to the Nearest COM Parcel
Figure 1234: Average Distance from VAC Parcels to the Nearest COM Parcel
829
Figure 1235: Average Distance from AG Parcels to the Nearest IND Parcel
Figure 1236: Average Distance from COM Parcels to the Nearest IND Parcel
830
Figure 1237: Average Distance from IND Parcels to the Nearest IND Parcel
Figure 1238: Average Distance from MMR Parcels to the Nearest IND Parcel
831
Figure 1239: Average Distance from MU Parcels to the Nearest IND Parcel
Figure 1240: Average Distance from MFR Parcels to the Nearest IND Parcel
832
Figure 1241: Average Distance from PUB Parcels to the Nearest IND Parcel
Figure 1242: Average Distance from SFDR Parcels to the Nearest IND Parcel
833
Figure 1243: Average Distance from TCU Parcels to the Nearest IND Parcel
Figure 1244: Average Distance from VAC Parcels to the Nearest IND Parcel
834
Figure 1245: Average Distance from AG Parcels to the Nearest MMR Parcel
Figure 1246: Average Distance from COM Parcels to the Nearest MMR Parcel
835
Figure 1247: Average Distance from IND Parcels to the Nearest MMR Parcel
Figure 1248: Average Distance from MMR Parcels to the Nearest MMR Parcel
836
Figure 1249: Average Distance from MU Parcels to the Nearest MMR Parcel
Figure 1250: Average Distance from MFR Parcels to the Nearest MMR Parcel
837
Figure 1251: Average Distance from PUB Parcels to the Nearest MMR Parcel
Figure 1252: Average Distance from SFDR Parcels to the Nearest MMR Parcel
838
Figure 1253: Average Distance from TCU Parcels to the Nearest MMR Parcel
Figure 1254: Average Distance from VAC Parcels to the Nearest MMR Parcel
839
Figure 1255: Average Distance from AG Parcels to the Nearest MU Parcel
Figure 1256: Average Distance from COM Parcels to the Nearest MU Parcel
840
Figure 1257: Average Distance from IND Parcels to the Nearest MU Parcel
Figure 1258: Average Distance from MMR Parcels to the Nearest MU Parcel
841
Figure 1259: Average Distance from MU Parcels to the Nearest MU Parcel
Figure 1260: Average Distance from MFR Parcels to the Nearest MU Parcel
842
Figure 1261: Average Distance from PUB Parcels to the Nearest MU Parcel
Figure 1262: Average Distance from SFDR Parcels to the Nearest MU Parcel
843
Figure 1263: Average Distance from TCU Parcels to the Nearest MU Parcel
Figure 1264: Average Distance from VAC Parcels to the Nearest MU Parcel
844
Figure 1265: Average Distance from AG Parcels to the Nearest MFR Parcel
Figure 1266: Average Distance from COM Parcels to the Nearest MFR Parcel
845
Figure 1267: Average Distance from IND Parcels to the Nearest MFR Parcel
Figure 1268: Average Distance from MMR Parcels to the Nearest MFR Parcel
846
Figure 1269: Average Distance from MU Parcels to the Nearest MFR Parcel
Figure 1270: Average Distance from MFR Parcels to the Nearest MFR Parcel
847
Figure 1271: Average Distance from PUB Parcels to the Nearest MFR Parcel
Figure 1272: Average Distance from SFDR Parcels to the Nearest MFR Parcel
848
Figure 1273: Average Distance from TCU Parcels to the Nearest MFR Parcel
Figure 1274: Average Distance from VAC Parcels to the Nearest MFR Parcel
849
Figure 1275: Average Distance from AG Parcels to the Nearest PUB Parcel
Figure 1276: Average Distance from COM Parcels to the Nearest PUB Parcel
850
Figure 1277: Average Distance from IND Parcels to the Nearest PUB Parcel
Figure 1278: Average Distance from MMR Parcels to the Nearest PUB Parcel
851
Figure 1279: Average Distance from MU Parcels to the Nearest PUB Parcel
Figure 1280: Average Distance from MFR Parcels to the Nearest PUB Parcel
852
Figure 1281: Average Distance from PUB Parcels to the Nearest PUB Parcel
Figure 1282: Average Distance from SFDR Parcels to the Nearest PUB Parcel
853
Figure 1283: Average Distance from TCU Parcels to the Nearest PUB Parcel
Figure 1284: Average Distance from VAC Parcels to the Nearest PUB Parcel
854
Figure 1285: Average Distance from AG Parcels to the Nearest SFDR Parcel
Figure 1286: Average Distance from COM Parcels to the Nearest SFDR Parcel
855
Figure 1287: Average Distance from IND Parcels to the Nearest SFDR Parcel
Figure 1288: Average Distance from MMR Parcels to the Nearest SFDR Parcel
856
Figure 1289: Average Distance from MU Parcels to the Nearest SFDR Parcel
Figure 1290: Average Distance from MFR Parcels to the Nearest SFDR Parcel
857
Figure 1291: Average Distance from PUB Parcels to the Nearest SFDR Parcel
Figure 1292: Average Distance from SFDR Parcels to the Nearest SFDR Parcel
858
Figure 1293: Average Distance from TCU Parcels to the Nearest SFDR Parcel
Figure 1294: Average Distance from VAC Parcels to the Nearest SFDR Parcel
859
Figure 1295: Average Distance from AG Parcels to the Nearest TCU Parcel
Figure 1296: Average Distance from COM Parcels to the Nearest TCU Parcel
860
Figure 1297: Average Distance from IND Parcels to the Nearest TCU Parcel
Figure 1298: Average Distance from MMR Parcels to the Nearest TCU Parcel
861
Figure 1299: Average Distance from MU Parcels to the Nearest TCU Parcel
Figure 1300: Average Distance from MFR Parcels to the Nearest TCU Parcel
862
Figure 1301: Average Distance from PUB Parcels to the Nearest TCU Parcel
Figure 1302: Average Distance from SFDR Parcels to the Nearest TCU Parcel
863
Figure 1303: Average Distance from TCU Parcels to the Nearest TCU Parcel
Figure 1304: Average Distance from VAC Parcels to the Nearest TCU Parcel
864
Figure 1305: Average Distance from AG Parcels to the Nearest UNKN Parcel
Figure 1306: Average Distance from COM Parcels to the Nearest UNKN Parcel
865
Figure 1307: Average Distance from IND Parcels to the Nearest UNKN Parcel
Figure 1308: Average Distance from MMR Parcels to the Nearest UNKN Parcel
866
Figure 1309: Average Distance from MU Parcels to the Nearest UNKN Parcel
Figure 1310: Average Distance from MFR Parcels to the Nearest UNKN Parcel
867
Figure 1311: Average Distance from PUB Parcels to the Nearest UNKN Parcel
Figure 1312: Average Distance from SFDR Parcels to the Nearest UNKN Parcel
868
Figure 1313: Average Distance from TCU Parcels to the Nearest UNKN Parcel
Figure 1314: Average Distance from VAC Parcels to the Nearest UNKN Parcel
869
Figure 1315: Average Distance from AG Parcels to the Nearest VAC Parcel
Figure 1316: Average Distance from COM Parcels to the Nearest VAC Parcel
870
Figure 1317: Average Distance from IND Parcels to the Nearest VAC Parcel
Figure 1318: Average Distance from MMR Parcels to the Nearest VAC Parcel
871
Figure 1319: Average Distance from MU Parcels to the Nearest VAC Parcel
Figure 1320: Average Distance from MFR Parcels to the Nearest VAC Parcel
872
Figure 1321: Average Distance from PUB Parcels to the Nearest VAC Parcel
Figure 1322: Average Distance from SFDR Parcels to the Nearest VAC Parcel
873
Figure 1323: Average Distance from TCU Parcels to the Nearest VAC Parcel
Figure 1324: Average Distance from VAC Parcels to the Nearest VAC Parcel
874
Appendix N: Bar Charts Showing the Normalized Average Distance Between the Nearest
Parcels of Each Land Use Class
This appendix provides bar charts showing, for each land use class, the normalized average distance to the nearest parcel of
each land use. For ease of reference, an index with the page number of each land use combination?s chart is provided in Table 16.
Table 16: Bar Chart Index, Normalized Average Distance Between the Nearest Parcels of Each Land Use Class
Average Distance From Parcels With Land Use (LU) Class?
AG COM IND MMR MU MFR PUB SFDR TCU UNKN VAC
AG Pg. 876 Pg. 876 Pg. 877 Pg. 877 Pg. 878 Pg. 878 Pg. 879 Pg. 879 Pg. 880 Pg. 880
COM Pg. 881 Pg. 881 Pg. 882 Pg. 882 Pg. 883 Pg. 883 Pg. 884 Pg. 884 Pg. 885 Pg. 885
IND Pg. 886 Pg. 886 Pg. 887 Pg. 887 Pg. 888 Pg. 888 Pg. 889 Pg. 889 Pg. 890 Pg. 890
MMR Pg. 891 Pg. 891 Pg. 892 Pg. 892 Pg. 893 Pg. 893 Pg. 894 Pg. 894 Pg. 895 Pg. 895
MU Pg. 896 Pg. 896 Pg. 897 Pg. 897 Pg. 898 Pg. 898 Pg. 899 Pg. 899 Pg. 900 Pg. 900
MFR Pg. 901 Pg. 901 Pg. 902 Pg. 902 Pg. 903 Pg. 903 Pg. 904 Pg. 904 Pg. 905 Pg. 905
PUB Pg. 906 Pg. 906 Pg. 907 Pg. 907 Pg. 908 Pg. 908 Pg. 909 Pg. 909 Pg. 910 Pg. 910
SFDR Pg. 911 Pg. 911 Pg. 912 Pg. 912 Pg. 913 Pg. 913 Pg. 914 Pg. 914 Pg. 915 Pg. 915
TCU Pg. 916 Pg. 916 Pg. 917 Pg. 917 Pg. 918 Pg. 918 Pg. 919 Pg. 919 Pg. 920 Pg. 920
UNKN Pg. 921 Pg. 921 Pg. 922 Pg. 922 Pg. 923 Pg. 923 Pg. 924 Pg. 924 Pg. 925 Pg. 925
VAC Pg. 926 Pg. 926 Pg. 927 Pg. 927 Pg. 928 Pg. 928 Pg. 929 Pg. 929 Pg. 930 Pg. 930
875
To Closest Parcel with LU?
Figure 1325: Average Distance from AG Parcels to the Nearest AG Parcel (Normalized)
Figure 1326: Average Distance from COM Parcels to the Nearest AG Parcel (Normalized)
876
Figure 1327: Average Distance from IND Parcels to the Nearest AG Parcel (Normalized)
Figure 1328: Average Distance from MMR Parcels to the Nearest AG Parcel (Normalized)
877
Figure 1329: Average Distance from MU Parcels to the Nearest AG Parcel (Normalized)
Figure 1330: Average Distance from MFR Parcels to the Nearest AG Parcel (Normalized)
878
Figure 1331: Average Distance from PUB Parcels to the Nearest AG Parcel (Normalized)
Figure 1332: Average Distance from SFDR Parcels to the Nearest AG Parcel (Normalized)
879
Figure 1333: Average Distance from TCU Parcels to the Nearest AG Parcel (Normalized)
Figure 1334: Average Distance from VAC Parcels to the Nearest AG Parcel (Normalized)
880
Figure 1335: Average Distance from AG Parcels to the Nearest COM Parcel (Normalized)
Figure 1336: Average Distance from COM Parcels to the Nearest COM Parcel (Normalized)
881
Figure 1337: Average Distance from IND Parcels to the Nearest COM Parcel (Normalized)
Figure 1338: Average Distance from MMR Parcels to the Nearest COM Parcel (Normalized)
882
Figure 1339: Average Distance from MU Parcels to the Nearest COM Parcel (Normalized)
Figure 1340: Average Distance from MFR Parcels to the Nearest COM Parcel (Normalized)
883
Figure 1341: Average Distance from PUB Parcels to the Nearest COM Parcel (Normalized)
Figure 1342: Average Distance from SFDR Parcels to the Nearest COM Parcel (Normalized)
884
Figure 1343: Average Distance from TCU Parcels to the Nearest COM Parcel (Normalized)
Figure 1344: Average Distance from VAC Parcels to the Nearest COM Parcel (Normalized)
885
Figure 1345: Average Distance from AG Parcels to the Nearest IND Parcel (Normalized)
Figure 1346: Average Distance from COM Parcels to the Nearest IND Parcel (Normalized)
886
Figure 1347: Average Distance from IND Parcels to the Nearest IND Parcel (Normalized)
Figure 1348: Average Distance from MMR Parcels to the Nearest IND Parcel (Normalized)
887
Figure 1349: Average Distance from MU Parcels to the Nearest IND Parcel (Normalized)
Figure 1350: Average Distance from MFR Parcels to the Nearest IND Parcel (Normalized)
888
Figure 1351: Average Distance from PUB Parcels to the Nearest IND Parcel (Normalized)
Figure 1352: Average Distance from SFDR Parcels to the Nearest IND Parcel (Normalized)
889
Figure 1353: Average Distance from TCU Parcels to the Nearest IND Parcel (Normalized)
Figure 1354: Average Distance from VAC Parcels to the Nearest IND Parcel (Normalized)
890
Figure 1355: Average Distance from AG Parcels to the Nearest MMR Parcel (Normalized)
Figure 1356: Average Distance from COM Parcels to the Nearest MMR Parcel (Normalized)
891
Figure 1357: Average Distance from IND Parcels to the Nearest MMR Parcel (Normalized)
Figure 1358: Average Distance from MMR Parcels to the Nearest MMR Parcel (Normalized)
892
Figure 1359: Average Distance from MU Parcels to the Nearest MMR Parcel (Normalized)
Figure 1360: Average Distance from MFR Parcels to the Nearest MMR Parcel (Normalized)
893
Figure 1361: Average Distance from PUB Parcels to the Nearest MMR Parcel (Normalized)
Figure 1362: Average Distance from SFDR Parcels to the Nearest MMR Parcel (Normalized)
894
Figure 1363: Average Distance from TCU Parcels to the Nearest MMR Parcel (Normalized)
Figure 1364: Average Distance from VAC Parcels to the Nearest MMR Parcel (Normalized)
895
Figure 1365: Average Distance from AG Parcels to the Nearest MU Parcel (Normalized)
Figure 1366: Average Distance from COM Parcels to the Nearest MU Parcel (Normalized)
896
Figure 1367: Average Distance from IND Parcels to the Nearest MU Parcel (Normalized)
Figure 1368: Average Distance from MMR Parcels to the Nearest MU Parcel (Normalized)
897
Figure 1369: Average Distance from MU Parcels to the Nearest MU Parcel (Normalized)
Figure 1370: Average Distance from MFR Parcels to the Nearest MU Parcel (Normalized)
898
Figure 1371: Average Distance from PUB Parcels to the Nearest MU Parcel (Normalized)
Figure 1372: Average Distance from SFDR Parcels to the Nearest MU Parcel (Normalized)
899
Figure 1373: Average Distance from TCU Parcels to the Nearest MU Parcel (Normalized)
Figure 1374: Average Distance from VAC Parcels to the Nearest MU Parcel (Normalized)
900
Figure 1375: Average Distance from AG Parcels to the Nearest MFR Parcel (Normalized)
Figure 1376: Average Distance from COM Parcels to the Nearest MFR Parcel (Normalized)
901
Figure 1377: Average Distance from IND Parcels to the Nearest MFR Parcel (Normalized)
Figure 1378: Average Distance from MMR Parcels to the Nearest MFR Parcel (Normalized)
902
Figure 1379: Average Distance from MU Parcels to the Nearest MFR Parcel (Normalized)
Figure 1380: Average Distance from MFR Parcels to the Nearest MFR Parcel (Normalized)
903
Figure 1381: Average Distance from PUB Parcels to the Nearest MFR Parcel (Normalized)
Figure 1382: Average Distance from SFDR Parcels to the Nearest MFR Parcel (Normalized)
904
Figure 1383: Average Distance from TCU Parcels to the Nearest MFR Parcel (Normalized)
Figure 1384: Average Distance from VAC Parcels to the Nearest MFR Parcel (Normalized)
905
Figure 1385: Average Distance from AG Parcels to the Nearest PUB Parcel (Normalized)
Figure 1386: Average Distance from COM Parcels to the Nearest PUB Parcel (Normalized)
906
Figure 1387: Average Distance from IND Parcels to the Nearest PUB Parcel (Normalized)
Figure 1388: Average Distance from MMR Parcels to the Nearest PUB Parcel (Normalized)
907
Figure 1389: Average Distance from MU Parcels to the Nearest PUB Parcel (Normalized)
Figure 1390: Average Distance from MFR Parcels to the Nearest PUB Parcel (Normalized)
908
Figure 1391: Average Distance from PUB Parcels to the Nearest PUB Parcel (Normalized)
Figure 1392: Average Distance from SFDR Parcels to the Nearest PUB Parcel (Normalized)
909
Figure 1393: Average Distance from TCU Parcels to the Nearest PUB Parcel (Normalized)
Figure 1394: Average Distance from VAC Parcels to the Nearest PUB Parcel (Normalized)
910
Figure 1395: Average Distance from AG Parcels to the Nearest SFDR Parcel (Normalized)
Figure 1396: Average Distance from COM Parcels to the Nearest SFDR Parcel (Normalized)
911
Figure 1397: Average Distance from IND Parcels to the Nearest SFDR Parcel (Normalized)
Figure 1398: Average Distance from MMR Parcels to the Nearest SFDR Parcel (Normalized)
912
Figure 1399: Average Distance from MU Parcels to the Nearest SFDR Parcel (Normalized)
Figure 1400: Average Distance from MFR Parcels to the Nearest SFDR Parcel (Normalized)
913
Figure 1401: Average Distance from PUB Parcels to the Nearest SFDR Parcel (Normalized)
Figure 1402: Average Distance from SFDR Parcels to the Nearest SFDR Parcel (Normalized)
914
Figure 1403: Average Distance from TCU Parcels to the Nearest SFDR Parcel (Normalized)
Figure 1404: Average Distance from VAC Parcels to the Nearest SFDR Parcel (Normalized)
915
Figure 1405: Average Distance from AG Parcels to the Nearest TCU Parcel (Normalized)
Figure 1406: Average Distance from COM Parcels to the Nearest TCU Parcel (Normalized)
916
Figure 1407: Average Distance from IND Parcels to the Nearest TCU Parcel (Normalized)
Figure 1408: Average Distance from MMR Parcels to the Nearest TCU Parcel (Normalized)
917
Figure 1409: Average Distance from MU Parcels to the Nearest TCU Parcel (Normalized)
Figure 1410: Average Distance from MFR Parcels to the Nearest TCU Parcel (Normalized)
918
Figure 1411: Average Distance from PUB Parcels to the Nearest TCU Parcel (Normalized)
Figure 1412: Average Distance from SFDR Parcels to the Nearest TCU Parcel (Normalized)
919
Figure 1413: Average Distance from TCU Parcels to the Nearest TCU Parcel (Normalized)
Figure 1414: Average Distance from VAC Parcels to the Nearest TCU Parcel (Normalized)
920
Figure 1415: Average Distance from AG Parcels to the Nearest UNKN Parcel (Normalized)
Figure 1416: Average Distance from COM Parcels to the Nearest UNKN Parcel (Normalized)
921
Figure 1417: Average Distance from IND Parcels to the Nearest UNKN Parcel (Normalized)
Figure 1418: Average Distance from MMR Parcels to the Nearest UNKN Parcel (Normalized)
922
Figure 1419: Average Distance from MU Parcels to the Nearest UNKN Parcel (Normalized)
Figure 1420: Average Distance from MFR Parcels to the Nearest UNKN Parcel (Normalized)
923
Figure 1421: Average Distance from PUB Parcels to the Nearest UNKN Parcel (Normalized)
Figure 1422: Average Distance from SFDR Parcels to the Nearest UNKN Parcel (Normalized)
924
Figure 1423: Average Distance from UNKN Parcels to the Nearest UNKN Parcel (Normalized)
Figure 1424: Average Distance from VAC Parcels to the Nearest UNKN Parcel (Normalized)
925
Figure 1425: Average Distance from AG Parcels to the Nearest VAC Parcel (Normalized)
Figure 1426: Average Distance from COM Parcels to the Nearest VAC Parcel (Normalized)
926
Figure 1427: Average Distance from IND Parcels to the Nearest VAC Parcel (Normalized)
Figure 1428: Average Distance from MMR Parcels to the Nearest VAC Parcel (Normalized)
927
Figure 1429: Average Distance from MU Parcels to the Nearest VAC Parcel (Normalized)
Figure 1430: Average Distance from MFR Parcels to the Nearest VAC Parcel (Normalized)
928
Figure 1431: Average Distance from PUB Parcels to the Nearest VAC Parcel (Normalized)
Figure 1432: Average Distance from SFDR Parcels to the Nearest VAC Parcel (Normalized)
929
Figure 1433: Average Distance from TCU Parcels to the Nearest VAC Parcel (Normalized)
Figure 1434: Average Distance from VAC Parcels to the Nearest VAC Parcel (Normalized)
930
Appendix O: Bar Charts Showing the Proportional Area of Each Land Use Class Within 200
Feet of Non-Access Controlled Arterial Roadway Centerlines
This appendix provides bar charts showing the (non-normalized) proportional area of each land use class within 200 feet of
non-access controlled arterial roadway centerlines.
Figure 1435: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to AG Uses
931
Figure 1436: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to COM Uses
Figure 1437: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to IND Uses
932
Figure 1438: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MMR Uses
Figure 1439: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MU Uses
933
Figure 1440: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to MFR Uses
Figure 1441: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to PUB Uses
934
Figure 1442: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to SFDR Uses
Figure 1443: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to TCU Uses
935
Figure 1444: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to UNKN Uses
Figure 1445: Proportion of Parcel Area Within 200 Feet of Arterials Devoted to VAC Uses
936
Appendix P: Bar Charts Showing the Proportional Area of Each Land Use Class Within 200
Feet of Rail Lines
This appendix provides bar charts showing the (non-normalized) proportional area of each land use class within 200 feet of rail
lines.
Figure 1446: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to AG Uses
937
Figure 1447: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to COM Uses
Figure 1448: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to IND Uses
938
Figure 1449: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MMR Uses
Figure 1450: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MU Uses
939
Figure 1451: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to MFR Uses
Figure 1452: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to PUB Uses
940
Figure 1453: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to SFDR Uses
Figure 1454: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to TCU Uses
941
Figure 1455: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to UNKN Uses
Figure 1456: Proportion of Parcel Area Within 200 Feet of Rail Lines Devoted to VAC Uses
942
Appendix Q: Bar Charts Showing the Proportional Area of Each Land Use Class Within a
Half Mile of a Limited Access Highway Exit
This appendix provides bar charts showing the (non-normalized) proportional area of each land use class within a half mile of
a limited access highway exit.
Figure 1457: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to AG Uses
943
Figure 1458: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to COM Uses
Figure 1459: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to IND Uses
944
Figure 1460: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to MMR Uses
Figure 1461: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to MU Uses
945
Figure 1462: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to MFR Uses
Figure 1463: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to PUB Uses
946
Figure 1464: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to SFDR Uses
Figure 1465: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to TCU Uses
947
Figure 1466: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to UNKN Uses
Figure 1467: Proportion of Parcel Area Within a Half Mile of a Limited Highway Exit Devoted to VAC Uses
948
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