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人文地理  2016, Vol. 31 Issue (5): 93-98,147    DOI: 10.13959/j.issn.1003-2398.2016.05.014
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基于道路网络的犯罪空间聚集特征研究
郑滋椀1,2,3, 张丰1,2, 杜震洪1,2, 刘仁义1,2, 周国民3
1. 浙江大学 浙江省资源与环境信息系统重点实验室, 杭州 310028;
2. 浙江大学 地理信息科学研究所, 杭州 310027;
3. 浙江警察学院 基于大数据架构的公安信息化应用公安部重点实验室, 杭州 310000
STUDY ON CHARACTERISTICS OF CRIME SPATIAL DISTRIBUTION BASED ON STREET NETWORK
ZHENG Zi-wan1,2,3, ZHANG Feng1,2, DU Zhen-hong1,2, LIU Ren-yi1,2, ZHOU Guo-min3
1. Zhejiang Provincial Key Laboratory of GIS, Zhejiang University, Hangzhou 310028, China;
2. Department of Geographic Information Science, Zhejiang University, Hangzhou 310027, China;
3. Ministry of Public Security's Key Laboratory of Public Security Information Application Based on Big-data Architecture, Zhejiang Police College, Hangzhou 310000, China

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摘要 由于目前犯罪空间聚集特征研究的单元主要是地点、街区、巡逻区等,但是许多警务工作是沿道路网络开展的,因此有必要研究犯罪在道路网络上的空间聚集特征。本文以路段为分析单元对浙江省某地2011-2014年发生的16787起盗窃类犯罪进行了研究。通过分析,发现:1在道路网络中存在犯罪热点路段;2犯罪在路段上具有聚集性,少部分犯罪热点路段聚集了大部分犯罪,如19.86%的犯罪热点路段聚集了53.42%的犯罪;3犯罪热点路段在道路网络中也具有空间聚集性,主要聚集在类型为住宅区、大学、商业区等7个区域。根据犯罪在道路网络上的聚集特征,警察部门能优化相关警务工作,科学分配警力资源,从而提高治安防控、犯罪预防、侦查破案等能力和效率。
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关键词 犯罪空间聚集犯罪热点热点警务道路网络    
Abstract:Over the last decades, the units of study on characteristics of crime spatial distribution are mainly address, block, beat, county, district, city, and so on. The paper analyzes 16787 property crime incidents occurring at one district, Zhejiang province during 2011-2014 with the analysis unit of street segment. Firstly, the analysis of the distribution of crime number of street segments suggests that there are street segments with a large number of crime, which are called the hot street segment, and these hot street segments account for a small proportion of all street segments. Secondly, the analysis of the Lorenz curve between street segment and crime reveals that a small proportion of hottest street segments are totally responsible for a very large proportion of crime. Thirdly, using classification of natural break with five categories to classify street segments, identify crime hotspots, and create crime hotspot map of street segment, shows that hottest street segments cluster on the street network and form seven clustering areas of hottest street segments, which are primarily residential areas, universities and business areas with high density of population, high diversity of population, and high degree of people mobility. Finally, the similarity of the shape of Lorenz curve of street segment and Lorenz curve of block suggests the characteristics of crime spatial concentration based on block are similar to the characteristics of crime spatial concentration based on street network as described above.
Key wordscrime spatial concentration    crime hotspot    hotspot policing    street network   
收稿日期: 2015-07-20     
基金资助:

公安部公安理论及软科学项目(2012LLYJZJST095)

通讯作者: 张丰(1977-),女,浙江金华人,副教授,博士生导师,博士,主要研究方向为时空GIS建模、高性能GIS技术等。E-mail:zfcarnation@zju.edu.cn。     E-mail: zfcarnation@zju.edu.cn
作者简介: 郑滋椀(1989-),男,浙江温州人,硕士研究生,主要研究方向为犯罪地理、刑事侦查等。E-mail:zhengziwan@zjjcxy.cn。
引用本文:   
郑滋椀, 张丰, 杜震洪, 刘仁义, 周国民. 基于道路网络的犯罪空间聚集特征研究[J]. 人文地理, 2016, 31(5): 93-98,147. ZHENG Zi-wan, ZHANG Feng, DU Zhen-hong, LIU Ren-yi, ZHOU Guo-min. STUDY ON CHARACTERISTICS OF CRIME SPATIAL DISTRIBUTION BASED ON STREET NETWORK. HUMAN GEOGRAPHY, 2016, 31(5): 93-98,147.
链接本文:  
http://rwdl.xisu.edu.cn/CN/10.13959/j.issn.1003-2398.2016.05.014      或     http://rwdl.xisu.edu.cn/CN/Y2016/V31/I5/93
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