Crime Analysis Geographic Information System Services: Advanced Tools Report

• NCJ Number: 194340
• Author(s): Ezra B. Zubrow Ph.D.; Philip C. Mitchell M.S.; Monika Bolino M.A.
• Date Published: August 1999
• Length: 86 pages
• Grant Number(s): 97-IJ-CX-K020
• Agencies: NIJ-Sponsored
• Publication Type: Report (Study/Research)

Annotation

This final report presented a summary of findings, recommendations, and project reports on a Department of Justice funded project to develop a crime mapping tool kit for police departments.

Abstract

In a joint effort by the U.S. Department of Justice, National Institute of Justice, the Environmental Systems Research Institute (ESRI), and the University of Buffalo, a project was undertaken to develop an advanced crime mapping tool kit for police departments with standard and advanced crime mapping tools. The design of this tool kit was to use ArcView as a base platform and have both standard and advanced tools. The University of Buffalo was tasked with two project goals: determine the state of the art advanced tools for crime mapping and create a set of advanced tools in crime mapping. Findings presented were based on a double random survey of 1,000 police departments and an extensive literature survey of crime mapping. Highlighted findings included: (1) a majority of police departments were PC-based and used Windows 95/98; (2) a majority of police departments preferred “off the shelf” solutions to “customized software” solutions; (3) considerable crime mapping literature existed; and (4) the majority of literature was “gray literature” consisting of unpublished documents, web sites, list-servers, and internal documents. Recommendations presented included major recommendations, specific tool-by-tool recommendations, and implementation recommendations. The major recommendations included: (1) the need for advanced crime mapping tools; (2) the tools should consist of advanced statistics coupled to advanced spatial analysis; and (3) advanced crime mapping tools should consist of linked attribute analysis and spatial analysis algorithms. In addition to findings and recommendations, summaries of the content and results of seven project research reports submitted to ESRI were presented. These summaries covered cluster analysis, detecting hotspots, chloropleth mapping, Artificial Neural Networks (ANN), pattern analyses and pattern recognition, Patrol Car Allocation Tool (PAT), and Precinct Design Optimization Tool (PDOT). Appendices included full-text research reports and flow charts and GUIs.