Original Articles

GIS-based Spatial Pattern of the Crimes in Cities and the Early Warning Mechanism

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  • College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China

Received date: 2011-02-01

  Revised date: 2011-06-01

  Online published: 2011-10-25

Abstract

This paper attempts to use the land use map, road map, community demographic data, and the 10 years data about urban crimes in a county-level city, to conduct a spatial analysis of the county town’s crimes of different types in different years. The research on the urban crime and the spatial pattern of its influencing factors shows that (1) the number of cases in the core area of the county town is the largest, followed by the east and west areas, while fringe areas have a relatively small number of cases; (2) the spatial distribution of crime density have clear regional characteristics, of which the Shuikou Road, Cross Street and Yuanshan market have the highest density of crime; the east and west areas as well as the new city in the north area are the high density areas of crime; while, the fringe of the city is the lowest density area of crime. The study has shown that urban crime has relations with the development of urban built-up area, and there is a strong linear relationship between urban crime and urban travel. Based on the establishment of the spatial distribution model of urban crime, we can simulate and predict the future spatial distribution of urban crimes, so that police departments can take accurate and timely preventive measures.

Cite this article

GENG Shasha, ZHANG Wangfeng, LIU Yong, LI Tiantian, MA Yanqiang . GIS-based Spatial Pattern of the Crimes in Cities and the Early Warning Mechanism[J]. PROGRESS IN GEOGRAPHY, 2011 , 30(10) : 1240 -1246 . DOI: 10.11820/dlkxjz.2011.10.006

References

[1] 杨毅. 地理信息系统在犯罪分析及辅助决策中的应用研究[D]. 四川大学, 2005: 1-3.

[2] Brunsdon C, Corcoran J, Higgs G. Visualising space and time in crime pattern: A comparison of methods. Computers, Environment and Urban Systems, 2007, 31(1): 52-75.

[3] Stauffer E, Bonfanti M. Forensic Investigation of Stolen- Recovered and Other Crime-Related Vehicles. Massachusetts: Academic Press, 2006: 521-542.

[4] 邬伦, 任伏虎, 谢昆青, 等. 地理信息系统教程. 北京: 北京大学出版社, 1994.

[5] 李志伟. 地理信息系统及其应用. 计算机工程与应用, 1995(6): 43.

[6] 马虹. 地理信息系统空间分析方法及其若干应用. 干旱区地理, 1997, 20(3): 30-31.

[7] 王劲峰, 柏延臣, 朱彩英, 等. 地理信息系统空间分析能力探讨. 中国图象图形学报, 2001, 6(9): 849-852.

[8] 贺日兴. 国外警用地理信息技术发展历史、现状与趋势 (一). 警察技术, 2005(1): 11-13.

[9] 贺日兴. 国外警用地理信息技术发展历史、现状与趋势 (二). 警察技术, 2005(2): 20-23.

[10] 方正数码有限公司. GIS 推动公安信息化进程: 上海市公安局计算机辅助决策系统. 警察技术, 2002(4): 18.

[11] 周治新. 公安系统GIS 应用中需要着力解决的问题. 中国公共安全, 2005(Z1): 94-95.

[12] 贺日兴, 候震宇, 李家龙, 等. 我国警用地理信息系统建设若干问题的探讨. 警察技术, 2006(2): 4-9.

[13] 曹晓晗. 辽宁省人口密度分布模拟研究. 测绘与空间地理信息, 2010, 33(2): 144.

[14] 田永中, 陈述彭, 岳天祥, 等. 基于土地利用的中国人口密度模拟. 地理学报, 2004, 59(2): 287-290.

[15] 刘纪远, 岳天祥, 王英安. 中国人口密度数字模拟. 地理学报, 2003, 58(1): 17-24.

[16] 易汉文. 出行预测方法从出行模型到行为模型的变革. 城市交通, 2007, 5(1): 72-73.

[17] 杜德斌. 国外有关城市犯罪出行问题的研究. 城市问题, 1998(1): 57-60.
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