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

被引:6
|
作者
Wu, Ling [1 ]
Ye, Xinyue [2 ,3 ]
Webb, David [4 ]
机构
[1] Zhongnan Univ Econ & Law, Criminal Justice, Wuhan, Hubei, Peoples R China
[2] Bowling Green State Univ, Ctr Reg Dev, Bowling Green, OH 43403 USA
[3] Bowling Green State Univ, Sch Earth Environm & Soc, Bowling Green, OH 43403 USA
[4] Law Enforcement Management Inst Texas, Huntsville, TX USA
关键词
Auto Burglary; Burglary Patterns; Cluster; Hot Spots; Space-Time Analysis;
D O I
10.4018/jagr.2012100104
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
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.
引用
收藏
页码:69 / 86
页数:18
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