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Copyright, iv
Preface, xvi
Chapter 1: Introduction to Spatial Aspects of Crime: Theory and Practice, 1
Chapter 1. Introduction to Spatial Aspects of Crime: Theory and Practice, 1
Introduction to Criminological Theory, 1
Shifting the Focus to the Criminal Event, 2
How Theories Are Created and Evaluated, 4
The Usefulness of Criminological Theory, 5
An Introduction to the Book, 7
Part I. Theory, 9
Chapter 2. Crime and Place, 11
Introduction to Crime and Place, 11
International Differences in Crime Distribution, 12
Empirical Realities, 12
Explanations, 14
Regional Differences in Crime Distribution within the United States, 18
Empirical Realities, 18
Explanations, 23
Differences in Urban and Rural Distributions of Crime within the United States, 24
Empirical Realities, 25
Explanations, 28
Intra-City Differences in Distributions of Crime within the United States, 31
Empirical Realities, 31
Explanations, 32
Focus On: Criminal Revictimization, 33
Spatial Aspects of Fear of Crime and Public Perception of Crime, 36
Summary, 39
List of Major Research Findings, 39
Implications of Findings for Crime Mapping and Spatial Analysis, 42
Case Study: Hate Crimes and Space, 43
Chapter 3. Social Disorganization, 46
Introduction to Social Disorganization, 46
Prehistory of Social Disorganization Theory: Cartographic School of Criminology, 47
Early Social Disorganization Theories, 49
Park and Burgess: The City (1925), 49
The Chicago School of Criminology, 51
Shaw and Mckay: Juvenile Delinquency in Urban Areas (1942), 51
Focus On: Clifford Shaw, 52
Social Disorganization, 52
Focus On: Testing Social Disorganization, 53
Modern Social Disorganization Research, 55
Incivilities and Crime, 59
Focus On: Levels of Social Control, 60
Problems and Criticisms of Theory, 61
Summary, 63
List of Major Research Findings, 63
Implications of Findings for Crime Mapping and Spatial Analysis, 64
Case Study: Chicago Area Project, 65
Chapter 4. Ecological Theories of Crime, 68
Introduction to the Major Schools of Thought in Ecological Theory, 68
Defensible Space, 69
Major Hypotheses, 69
Major Findings, 72
Problems and Criticisms of Theory, 73
Crime Prevention through Environmental Design, 74
Major Hypotheses, 74
Focus On: C. Ray Jeffery, 76
Focus On: Three D’s of CPTED, 78
Major Findings, 79
Problems and Criticisms of Theory, 82
Situational Crime Prevention, 83
Major Hypotheses, 83
Major Findings, 85
Problems and Criticisms of Theory, 86
Routine Activity Theory, 88
Major Hypotheses, 88
Major Findings, 89
Focus On: Opportunity and Rational Choice Theories, 90
Problems and Criticisms of Theory, 91
Crime Pattern Theory, 92
Major Hypotheses, 92
Major Findings, 95
Focus On: Paul and Patricia Brantingham, 95
Problems and Criticisms of Theory, 97
Summary of Major Findings and Implications, 98
List of Major Research Findings Relating to Ecological Theories of Crime, 98
Implications of Findings for Crime Mapping and Spatial Analysis, 101
Case Study: Environmental Design in the Nation’s Cities and Architecture, 102
Chapter 5. Behavioral Geography and Criminal Behavior, 104
Introduction to Behavioral Geography, 105
Mental Maps, 106
Research Findings, 107
Awareness Space, 109
Research Findings, 112
Journey to Crime, 113
Research Findings, 113
Criticism of Research, 117
Geographic Profiling, 118
Development of Geographic Profiling, 119
Profiling Models, 121
Criticism of Geographic Profiling, 123
Focus On: Next event Forecasting, 123
Summary, 125
List of Major Research Findings, 125
Implications of Research for Crime Mapping and Spatial Analysis, 126
Chapter 6. Epidemics, Diffusion, and Displacement of Crimes, 128
Introduction to Epidemics, Diffusion, and Displacement, 128
Epidemics, 129
Types of Epidemics, 130
Crime and Epidemics, 132
Focus On: Media Coverage of the “Crack Cocaine Epidemic”, 135
Displacement, 136
Types of Displacement, 137
Crime and Displacement, 137
Diffusion, 139
Types of Criminal Diffusion, 139
Crime and Diffusion, 139
Summary, 143
List of Major Research Findings Relating to Epidemics, Diffusion, and Displacement, 143
Implications of Findings for Crime Mapping and Spatial Analysis, 144
Case Study: The Place of School Violence, 145
Part II. Practice, 149
Chapter 7. Mapping in the Criminal Justice System, 151
Introduction, 151
History of Mapping in Criminal Justice, 152
The Development of Mapping in American Policing, 153
Uses of Crime Mapping within Policing, 154
Mapping by Crime Analysts, 155
Mapping for Patrol Officers, 156
Mapping for Investigations, 159
Mapping for Police Executives, 161
Mapping for Police/Community Relations, 164
Mapping in Courts and Corrections, 165
Future Uses of GIS and Crime Mapping, 169
GIS and GPS, 171
High Definition Mapping, 172
Correctional Facility Mapping, 173
3-D Mapping, 173
Regional Mapping Initiatives, 173
Simulation, 174
Summary, 175
List of Major Findings, 175
Implications for Crime Mapping and Spatial Analysis, 175
Chapter 8. Major Issues in the Practice of Crime Mapping, 177
Introduction, 177
Barriers to the Use of Computerized Mapping, 178
Data Issues, 181
Sources of Data for Crime Maps, 189
Critical Issues Concerning the Use of Computerized Mapping, 193
Ethical and Legal Issues in Crime Mapping, 194
Privacy v. Public Information, 194
Issues and Guidelines, 196
Sharing Data with Researchers, 198
Liability Issues, 199
Summary, 200
List of Major Findings, 200
Implications for Crime Mapping and Spatial Analysis, 201
Case Study: The Geography of Social Control, 202
Part III. Crime Mapping Workbook, 205
Workbook Section I. ArcGIS Crime Mapping Workbook, 207
Workbook Chapter 1. Getting Started with ArcGIS, 209
Getting Started, 209
Accessing the Textbook Webpage, 209
Online Resources, 210
Obtaining a Copy of Crimestat 3.0 or GeoDa, 210
Opening ArcMap, 210
Adding Data to the View, 210
Exploring Selected ArcMap Tools and Features, 211
Editing the Legend, 211
Zoom In and Zoom Out, 212
Identify Features, 213
Measure Tool, 213
Saving Your Work, 213
Review Questions, 214
Workbook Chapter 2. Understanding Data Sources, 215
Introduction, 215
Different Types of Data, 215
Point Data, 216
Polygon Data, 216
Other Data Types, 217
Sources of Data, 217
Working with Different Data Types, 218
Suggestions for Classifying Data, 220
Creating Graduated Symbols, 220
Project: Contextual Data Analysis, 221
Point Data, 221
Line Data, 221
Polygon Data, 222
Review Questions, 222
Workbook Chapter 3. Entering Data, 223
Introduction, 223
Geocoding Data, 223
Practical Geocoding, 224
Matching Options and Setting Geocoding Preferences, 225
Selecting File for Geocoding, 226
Interactive Address Rematching, 226
TIPS for Interactive Rematching, 227
Adding GPS Coordinates, 228
Adding Event Themes, 228
Project: Geocoding Accuracy, 228
Review Questions, 229
Further Readings, 229
Workbook Chapter 4. Querying and Joining Data, 230
Introduction, 230
Why Query and Join Data?, 230
Querying Layers, 231
Creating a Query, 231
Converting, Clearing, or Querying the Query, 232
Joining Layers, 233
Exporting the Layer as a .shp file, 233
Project: Merge and Query of Data, 234
Review Questions, 234
Workbook Chapter 5. Understanding Layouts and Map Design, 235
Introduction, 235
Scale and Map Design, 235
Map Elements, 236
Map Layout, 236
Editing Map Elements, 237
Adding a Legend, 237
Legend Items, 237
Legend Title, 237
Legend Frame, 238
Item Size and Spacing, 238
Altering the Size and Location of a Map Element, 238
Editing the Scale, 239
Adding a Compass and Scale Bar, 239
Adding a Map Title, 239
Adding Other Elements to the Layout, 239
Printing and Exporting a Layout, 240
Exporting a Map, 240
Map Design, 240
Audience and Medium, 240
Map Colors, 242
Symbolization, 243
Labeling, 243
Other Issues in Map Design, 244
Project: Designing Effective Maps, 244
Review Questions, 245
Further Readings, 245
Workbook Section II. Basic Spatial Analysis, 247
Workbook Chapter 6. Proximity Analysis, 249
Introduction, 249
What Is Proximity Analysis and Why Use It?, 249
Buffer Zone Analysis, 250
Geographic Selection, 251
Options for Theme Select Results, 252
Exercises, 253
Review Questions, 253
Workbook Chapter 7. Spatial Distribution Analysis, 254
Introduction, 254
Mean Center Analysis, 254
Performing Mean Center Analysis in Crimestat, 255
Standard Deviation Analysis, 257
Performing Standard Deviation Analyses, 258
Spatial Autocorrelation Analysis, 259
Performing Moran’s I and Geary’s C, 260
Exercises, 260
Review Questions, 262
Further Readings, 262
Workbook Chapter 8. Distance Analysis, 263
Introduction, 263
Nearest Neighbor Index, 263
Performing Nearest Neighbor Analysis, 264
K-Order Nearest Neighbor Analysis, 265
Exercises, 266
Review Questions, 266
Further Readings, 266
Workbook Section III. Advanced Spatial Analysis, 267
Workbook Chapter 9. Hot Spot Analysis, 269
Introduction, 269
Hot Spot Methods, 271
Fuzzy Mode, 272
Performing a Fuzzy Mode Analysis, 272
Nearest Neighbor Hierarchical Clustering, 273
Performing NNH Analysis, 274
Risk Adjusted NNH Analysis, 275
Performing RNNH Analysis, 276
Exercises, 276
Review Questions, 277
Further Readings, 277
Workbook Chapter 10. Density Mapping, 279
Introduction, 279
Performing a Single Kernel Density Interpolation, 280
Dual Kernel Density Interpolation, 282
Performing a Dual Kernel Density Interpolation, 283
Exercises, 284
Review Questions, 284
Further Readings, 285
Workbook Chapter 11. Spatial Dispersion Mapping, 286
Introduction, 286
Performing Spatial Dispersion Mapping Using Dual Kernel Density Interpolation, 287
Exercises, 288
Review Questions, 288
Further Readings, 288
Workbook Section IV. Aggregate Data Analysis, 289
Workbook Chapter 12. Working with Aggregate Data, 291
Introduction, 291
Aggregating Point Data, 294
Downloading Aggregate Data and Joining It with Existing Map Data, 295
Joining Aggregate Data, 296
Aggregate Data Sources, 297
Exercises, 297
Workbook Chapter 13. Exploratory Spatial Data Analysis, 298
Introduction, 298
ESDA: Exploratory Spatial Data Analysis, 298
ESDA Techniques, 299
Boxplots, 299
Histogram, 300
Scatter Plot, 300
ESDA in GeoDa, 301
Overview of GeoDa, 301
Data Visualization Methods, 302
Quantile Map, 302
Percentile Map, 302
Standard Deviation Map, 303
Conducting ESDA with GeoDa, 303
Histogram, 304
Scatter Plot, 304
Exercises, 305
Further Readings, 305
Workbook Chapter 14. Spatial Autocorrelation, 306
Introduction, 306
Spatial Autocorrelation Analysis, 306
Moran’s I, 307
Lisa Analysis, 307
Conducting Moran’s I Analysis in GeoDa, 308
Interpretation, 309
Conducting a Moran’s I, 309
Interpretation of Moran’s I Results, 309
Conducting a Univariate Lisa Analysis, 310
Exercises, 310
Further Readings, 311
Bibliography, 312
Index, 327

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