地理研究 ›› 2017, Vol. 36 ›› Issue (12): 2492-2504.doi: 10.11821/dlyj201712018

• 犯罪地理专栏 • 上一篇    下一篇

微观空间因素对街头抢劫影响的空间异质性——以DP半岛为例

徐冲1(), 柳林1,2(), 周素红3,4, 姜超3,4   

  1. 1. 广州大学地理科学学院公共安全地理信息分析中心,广州 510006
    2. 辛辛那提大学地理系,辛辛那提 OH45221-1031,美国
    3. 中山大学地理科学与规划学院综合地理信息研究中心,广州 510275
    4. 广东省城市化与地理环境空间模拟重点实验室,广州510275
  • 收稿日期:2017-06-13 修回日期:2017-09-16 出版日期:2017-12-15 发布日期:2018-01-18
  • 作者简介:

    作者简介:徐冲(1985- ),男,河南开封人,博士,讲师,主要从事城市犯罪和城市地理研究。E-mail:xcaiwd0123@163.com

  • 基金资助:
    国家自然科学基金项目(41601138,41522104,41171140);国家自然科学基金重点项目(41531178);广东省自然科学基金研究团队项目(2014A030312010);广东省科技计划项目(2015A020217003);广东省教育厅特色创新项目自然科学类(2015KQNCX120);广州市教育局科技项目(1201630250);广东省高等学校国际暨港澳台科技合作创新平台项目(2014KGJHZ009)

Spatial heterogeneity of micro-spatial factors' effects on street robberies: A case study of DP peninsula

Chong XU1(), Lin LIU1,2(), Suhong ZHOU3,4, Chao JIANG3,4   

  1. 1. School of Geographical Sciences, Center of Geo-Informatics for Public Security, Guangzhou University, Guangzhou 510006, China
    2. Department of Geography, University of Cincinnati, OH 45221-0131, Ohio, USA
    3. School of Geography Science and Planning, Center of Integrated Geographic Information Anlaysis, Sun Yat-sen University, Guangzhou 510275, China
    4. Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Guangzhou 510275, China
  • Received:2017-06-13 Revised:2017-09-16 Online:2017-12-15 Published:2018-01-18

摘要:

在快速城镇化的背景下,日益严重的城市犯罪问题已经严重影响了城市的安定与繁荣,深入研究城市犯罪的空间影响因素对于未来城市安全发展具有重要意义。以H市DP半岛上2006-2011年发生的373起街头抢劫案件为研究对象,通过将研究区域网格划分为233个样本单元,以核密度处理方式将原始案件点转化为每个格网单元的犯罪强度(密度)作为因变量,结合“日常活动理论”与“理性选择理论”选取微观空间因素作为自变量,最终采用地理加权回归模型分析微观空间因素对街头抢劫案件发生强度的空间异质性现象。研究表明:公交站点个数变量、交叉口个数变量、土地利用混合程度变量与最近出岛口距离变量,对街头抢劫发生的影响程度存在空间异质性现象,尤其是公交站点个数变量在GWR模型中表现出随空间位置的不同呈现显著的正负两种影响效果。警务部门可以参照该结果针对不同局部区域的高影响微观空间因素进行重点防控,提高警务效率,从而更有效地防范和抑制街头抢劫犯罪的发生。

关键词: 城市犯罪, 街头抢劫, 空间异质性, 地理加权回归

Abstract:

Urban crime has increasingly become a major issue in the context of rapid urbanization in China. Investigating the patterns and effects of spatial factors on urban crime is of great importantce for urban public safety and security. The relationship between robbery and spatial factors has long been a popular topic in crime research. Focusing on the DP peninsula of H City as the study area and using a total number of 373 street robbery incidences obtained from the Public Security Bureau Call for Service Data in the period of 2006-2011, this study examines the spatial heterogeneity in the effects of micro-spatial factors on street robberies by Moran's I, ordinary least squared regression (OLS) model and geographically weighted regression (GWR) model. Firstly, a theoretical framework is developed for analyzing the impacts of micro scale spatial factors on street robbery. Those micro scale spatial variables are identified based on two criminal justice theories - routine activities theory and rational choice theory. Those variables include the number of bus stops, the number of intersections, the length of road net, the distance to the nearest police station, the degree of mixed land use, and the distance to the nearest exit of the peninsula. Secondly, based on the kernel density estimation approach, the variation of crime density is estimated for each grid and is modeled as a function of those contextual micro-spatial variables. The number of micro-spatial variables was cut down with the OLS model test. The analytical results show that spatial heterogeneity exists in the effects of micro-spatial factors on street robberies in the DP peninsula by GWR model test. Especially, the number of bus stops has both positive and negative effects on the crime density, and the effects vary significantly and spatially. The results shed new light on the effects of the spatial factors on crime rate at local scale and suggest the pitfalls of the global averaging model. Overall, the proposed method in this study has the potential to help local police department to identify micro-spatial factors areas with high crime density more explicitly and thus could improve the effectiveness of crime control and prevention efforts centered on street robberies.

Key words: urban crime, street robberies, spatial heterogeneity, Geographically Weighted Regression (GWR)