地理科学进展 ›› 2011, Vol. 30 ›› Issue (10): 1240-1246.doi: 10.11820/dlkxjz.2011.10.006

• 城市地理 • 上一篇    下一篇

基于GIS的城市犯罪行为空间分布特征及预警分析

耿莎莎, 张旺锋, 刘勇, 李甜甜, 马彦强   

  1. 兰州大学资源环境学院,兰州 730000
  • 收稿日期:2011-02-01 修回日期:2011-06-01 出版日期:2011-10-25 发布日期:2011-10-25
  • 通讯作者: 张旺锋(1968-),男,甘肃庆阳人,副教授,硕士生导师,主要研究方向为城市地产评估、城市土地规划、区域经济发展 和城市规划等。E-mail: zhangwf@lzu.edu.cn E-mail:zhangwf@lzu.edu.cn
  • 作者简介:耿莎莎(1988-),女,河南睢县人,硕士研究生,主要从事区域与城市规划和GIS应用研究。E-mail: gengss10@lzu.cn
  • 基金资助:

    兰州大学君政基金。

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

GENG Shasha, ZHANG Wangfeng, LIU Yong, LI Tiantian, MA Yanqiang   

  1. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
  • Received:2011-02-01 Revised:2011-06-01 Online:2011-10-25 Published:2011-10-25

摘要: 本文利用中原某县城区土地利用现状图、道路图、社区人口统计资料,以及10 年的城区犯罪案例数据等,对该县城区不同犯罪类型和不同年份的犯罪数据进行了空间分析。对该县城区犯罪及其影响因素的空间格局研究表明:①该县城区的核心区案件数量最多,其次为东关和西关较多,而边缘区案件数量相对较少;②就所有犯罪案件在城区的空间分布看,犯罪密度空间分布具明显的分区特征,其中水口路、十字街和袁山市场是犯罪密度最高的区域;东关、西关以及城北新区是犯罪密度较高的区域;城市边缘区的犯罪密度最低。研究表明城市犯罪与城市建成区的发展有关系;城市犯罪案件数与城市出行人数存在较强的线性关系。通过建立城市犯罪空间分布模型,可以模拟与预测城市犯罪未来空间分布,从而使公安部门及时准确地作出防范措施。

关键词: GIS, 地理数据库, 犯罪, 空间分析, 影响因素

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.

Key words: crime, geographic databases, GIS, influencing factors, spatial analysis