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GIS Tutorial for Crime Analysis Second Edition [Pehme köide]

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  • Formaat: Paperback / softback, 364 pages, kõrgus x laius: 203x254 mm
  • Sari: GIS Tutorial
  • Ilmumisaeg: 05-Jul-2018
  • Kirjastus: Environmental Systems Research Institute Inc.,U.S.
  • ISBN-10: 1589485165
  • ISBN-13: 9781589485167
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GIS Tutorial for Crime Analysis Second EditionSuurem pilt
  • Formaat: Paperback / softback, 364 pages, kõrgus x laius: 203x254 mm
  • Sari: GIS Tutorial
  • Ilmumisaeg: 05-Jul-2018
  • Kirjastus: Environmental Systems Research Institute Inc.,U.S.
  • ISBN-10: 1589485165
  • ISBN-13: 9781589485167
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781589485167.html
Märksõnad:
GIS Tutorial for Crime Analysis, second edition, is a workbook for crime analysts and students of criminology. The book presents state-of-the-art methods that can be incorporated into any police department’s standard practices. This second edition builds upon the first edition by updating tutorials, adding a new chapter on building and evaluating predictive models using ModelBuilder and ArcGIS’s hot spot analysis tools, and adding a capstone project on hot spot modeling.
In contrast to GIS workbooks that teach skills for one-time projects, this book has users build and use a crime mapping and analysis system to meet all spatial information needs of a police department. The book combines introductions to GIS and crime analysis methods and step-by-step tutorial exercises with independent assignments to teach key GIS skills, including data preparation and updating, map template building, map queries and analysis, automation of map production, and predictive modeling skills. The book also includes a 180-day trial version of ArcGIS Desktop software and tutorial data. Instructor resources are available upon request.

GIS Tutorial for Crime Analysis, second edition presents state-of-the-art crime mapping and analysis methods that can be incorporated into any police department’s current practices.
Preface ix
Acknowledgments xiii
Chapter 1 Introducing GIS for police work
1(12)
Introduction
1(1)
GIS for police work
1(1)
Spatial coordinates
2(2)
Spatial data
4(2)
Police operations management systems and GIS
6(3)
Overview of the book
9(2)
Environmental criminology literature
11(1)
References
12(1)
Chapter 2 Exploring ArcGIS® Desktop
13(28)
Map documents and ArcMap™ interface
13(1)
Download and install ArcGIS Desktop software and tutorial data
14(1)
Tutorial 2-1 Exploring the ArcMap user interface
15(11)
Tutorial 2-2 Exploring the ArcCatalog™ user interface
26(5)
Tutorial 2-3 Examining map layer properties
31(3)
Tutorial 2-4 Examining Layout View
34(2)
Instructions on how to save and submit assignment files for grading
36(1)
Assignment 2-1 Critique an online crime mapping system
37(1)
Assignment 2-2 Compare crime maps for serious violent crimes in Pittsburgh
38(3)
Chapter 3 Using crime maps
41(40)
Crime maps for field officers
41(2)
Early warning system maps for investigators and command staff
43(1)
Crime maps for the public
44(2)
Tutorial 3-1 Using maps designed for the public
46(7)
Tutorial 3-2 Using an early warning system map
53(14)
Tutorial 3-3 Using a pin map for field officers
67(9)
Assignment 3-1 Analyze hot spots for larceny crimes
76(3)
Assignment 3-2 Create a map for the media
79(1)
References
80(1)
Chapter 4 Building crime maps
81(46)
Periodic versus ad hoc crime maps
81(1)
Graphic design
82(2)
Tutorial 4-1 Building a pin map for field officers
84(15)
Tutorial 4-2 Building an early warning system for investigators
99(15)
Tutorial 4-3 Building a map for public use
114(7)
Assignment 4-1 Build an auto theft pin map
121(4)
Assignment 4-2 Build auto squad choropleth maps
125(1)
References
126(1)
Chapter 5 Querying crime maps
127(28)
Attribute queries
127(2)
Spatial queries
129(1)
Building and using crime queries
129(1)
Tutorial 5-1 Creating attribute queries
130(11)
Tutorial 5-2 Creating spatial queries
141(7)
Assignment 5-1 Analyze leading-indicator crimes by day versus by night
148(3)
Assignment 5-2 Analyze robberies near check-cashing businesses
151(2)
References
153(2)
Chapter 6 Assembling jurisdiction feature classes
155(54)
Geospatial data sources and jurisdiction maps
155(1)
Geospatial data for crime mapping
156(1)
Extraction of jurisdiction maps
157(1)
Joining aggregate tabular data to polygon map layers
157(1)
Assembling police jurisdiction feature classes
158(1)
Tutorial 6-1 Downloading and preprocessing geospatial data
159(7)
Tutorial 6-2 Extracting jurisdiction maps
166(8)
Tutorial 6-3 Joining census data to census polygon maps
174(3)
Tutorial 6-4 Creating new feature classes from geospatial data
177(11)
Tutorial 6-5 Digitizing features
188(12)
Assignment 6-1 Download and use a census block group basemap and data
200(4)
Assignment 6-2 Create maps for foot patrols and DUI target areas
204(5)
Chapter 7 Geocoding crime incident data
209(52)
Master feature classes and update files
209(1)
Police reports and location data
210(1)
TIGER/Line® street centerline data
210(1)
Geocoding address data
211(1)
Address-matching errors and reporting
212(1)
Crime data aggregation
212(1)
Geocoding crime incident data
212(1)
Tutorial 7-1 Address-matching (or geocoding) data
213(8)
Tutorial 7-2 Improving address-matching results
221(15)
Tutorial 7-3 Processing update and master data files
236(8)
Tutorial 7-4 Aggregating data
244(5)
Tutorial 7-5 Protecting privacy in location data
249(7)
Assignment 7-1 Geocode Pittsburgh 911 calls for service data
256(2)
Assignment 7-2 Build space and time series data for 911 calls
258(3)
Chapter 8 Automating crime mapping
261(40)
ModelBuilder models
261(1)
Model user interface
261(1)
Documentation
262(1)
Debugging
262(1)
Using ModelBuilder for automation
263(1)
Tutorial 8-1 Exploring a completed model
264(9)
Tutorial 8-2 Processing police reports into master files
273(10)
Tutorial 8-3 Producing a pin map for field officers
283(11)
Assignment 8-1 Build a model to produce choropleth maps
294(3)
Assignment 8-2 Build a model to produce size-graduated point marker maps
297(4)
Chapter 9 Predictive policing for crime hot spots
301(46)
Spatial clustering of crime in urban areas
302(1)
Chronic and temporary hot spots
302(1)
Prediction models for temporary hot spots
303(1)
Predictive performance of hot spot models
303(1)
Prediction Accuracy Index effectiveness curves
304(1)
Crime prevention by police in hot spots
305(1)
Experimental field trials for crime hot spots
306(1)
Tutorial 9-1 Modeling and predicting chronic hot spots using grid cells
307(10)
Tutorial 9-2 Modeling and predicting chronic hot spots using Kernel Density Smoothing
317(8)
Tutorial 9-3 Emerging hot spot analysis
325(5)
Tutorial 9-4 Repeat and Near Repeat hot spots
330(12)
Project: Build and evaluate a crime hot spot program
342(4)
References
346(1)
Data and image credits 347
Wilpen L. Gorr is emeritus professor of public policy and management information systems at the School of Public Policy and Management, H. John Heinz III College, Carnegie Mellon University, where he taught and researched GIS applications. He was also chairman of the schools Master of Science in Public Policy and Management program and editor of the International Journal of Forecasting. 

Kristen S. Kurland is a Teaching Professor of Architecture, Information Systems, and Public Policy at the H. John Heinz III College and School of Architecture, Carnegie Mellon University, where she teaches GIS, building information modeling, computer-aided design, 3D visualization, infrastructure management, and enterprise data analytics. 

Zan M. Dodson is a postdoctoral associate in the Public Health Dynamics Laboratory at the University of Pittsburgh and adjunct faculty at the H. John Heinz III College, Carnegie Mellon University, where he teaches GIS, spatiotemporal modeling, spatial optimization, and remote sensing.