Use of Computerized Mapping in Crime Control and Prevention Programs

• NCJ Number: 155182
• Author(s): T F Rich
• Date Published: July 1995
• Length: 11 pages
• Publication Series: NIJ Research in Action
• Grant Number(s): OJP-94-C-007
• Agencies: NIJ
• Publication Type: Report (Study/Research)

Annotation

On the basis of a literature review and telephone interviews, this paper focuses on some organizations that use mapping technologies in crime control and prevention programs, assesses the overall utility of these technologies, and identifies some obstacles to increased use of mapping.

Abstract

For crime control and prevention, mapping software has two primary goals: to further an understanding of the nature and extent of criminal and social problems in a community, particularly the relationship between criminal activity and possible contributing factors, and to improve the allocation of resources to combat these problems. Mapping efforts for crime prevention and control rely on police data, particularly call- for-service and incident data. Community groups and multiagency task forces also use geographic and demographic data from the Census Bureau, other State and local government agencies, or commercial vendors. Mapping software is most widely used for crime analysis in medium and large police departments where computerized, "geocoded" data are a byproduct of routine, daily work. Examples of mapping software application in police departments include Chicago patrol officers' ability to produce their own maps, based on incident type or date range, and dispatchers' ability to locate calls for service and the nearest patrol cars and other response units. Examples of applications of mapping by community organizations include mapping data on street-specific problems (Hartford) and abandoned houses and bars (Chicago). The primary obstacles to mapping-software use in crime control and prevention relate to hardware and software costs, user expertise, data acquisition costs, and data quality. Lower costs, increased data availability, improved data quality, and growing user sophistication are expected to lower these obstacles. 27 notes