Space-Time Analysis of Auto Burglary Patterns in a Fast-Growing Small City

Ling Wu, Xinyue Ye and David Webb
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Ling Wu: Zhongnan University of Economics & Law, China
Xinyue Ye: Center for Regional Development & School of Earth, Environment and Society, Bowling Green State University, Bowling Green, OH, USA
David Webb: Law Enforcement Management Institute of Texas, Huntsville, TX, USA

International Journal of Applied Geospatial Research (IJAGR), 2012, vol. 3, issue 4, 69-86

Abstract: Auto burglary is a rising concern for small cities that rely so highly on revenues from malls and shopping. The fear of auto burglary dispels possible business partners, shoppers, and workers. This piece of research was conducted in Shenandoah, a small city near Houston, Texas. Shenandoah has been experiencing a fast-growing economy and annexation process. The research highlights the potency of space-time analysis for the local police department. The paper describes the temporal trends of auto burglary offenses. Hot spots of auto burglary offenses in different time periods are identified, which provide a clue for police to prioritize limited resources. In addition, this project analyzes the repeatability of auto burglary incidents in the same locations. The space-time analysis reveals that, once an auto burglary incident occurred, one week is the optimal time period for police to actively patrol, or adopt other preventive strategies on the same location to deter the potential follow-up auto burglaries.

Date: 2012
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