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居民日常活动对扒窃警情时空格局的影响
引用本文:宋广文,肖露子,周素红,龙冬平,周淑丽,刘凯. 居民日常活动对扒窃警情时空格局的影响[J]. 地理学报, 2017, 72(2): 356-367. DOI: 10.11821/dlxb201702014
作者姓名:宋广文  肖露子  周素红  龙冬平  周淑丽  刘凯
作者单位:1. 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 5102752. 广东省城市化与地理环境空间模拟重点实验室,广州 510275
基金项目: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);国家自然科学基金优秀青年科学基金项目(41522104);国家自然科学基金项目(41171140);广东省科技计划项目(2015A020217003)
摘    要:扒窃现象与居民的日常活动有较强的关系,已有文献研究了不同活动场所对扒窃的影响,但鲜有考虑不同类型居民活动出行量及其场所对扒窃影响的时间差异。本文基于日常活动理论,以南方某大城市为例,以派出所为分析单元,利用居民入户调查问卷、兴趣点(Point of Interest, POI)、扒窃报警数据,检验不同类型活动出行量与扒窃的时间相关性,并划分时间段,建立多个空间滞后负二项回归模型分析不同时段居民日常活动对应场所与扒窃的关系。研究发现,扒窃警情存在明显的时空集聚性,其中,凌晨和早上的集聚性最强,白天和晚上相对较弱;不同类型的日常活动对扒窃时空格局的作用存在差异。买菜活动出行量与扒窃的时间变化存在正相关关系,买菜场所在凌晨和早上容易吸引扒窃者;购物活动与扒窃亦存在较强的时间正相关,白天和晚上在购物场所附近被盗的风险较高;外出吃饭的出行量与扒窃行为无直接关系,但在凌晨和早上餐馆周边容易吸引扒窃者;娱乐活动与扒窃同样存在较强的时间正相关,不同类型的娱乐场所对扒窃的影响存在差异,电影院、酒吧在大部分时间段均会吸引犯罪者,凌晨时段KTV附近区域的被盗风险较高。场所对扒窃的影响主要与犯罪机会吸引(犯罪目标的丰富性、暴露性)及场所自身属性有关(是否为犯罪者的集聚地)。文中最后对时间地理学和犯罪地理学结合的可能性、研究的应用意义等方面进行了探讨。

关 键 词:扒窃  日常活动理论  时间地理  活动类型  场所  时间差异  
收稿时间:2016-06-25
修稿时间:2017-01-02

Impact of residents' routine activities on the spatial-temporal pattern of theft from person
Guangwen SONG,Luzi XIAO,Suhong ZHOU,Dongping LONG,Shuli ZHOU,Kai LIU. Impact of residents' routine activities on the spatial-temporal pattern of theft from person[J]. Acta Geographica Sinica, 2017, 72(2): 356-367. DOI: 10.11821/dlxb201702014
Authors:Guangwen SONG  Luzi XIAO  Suhong ZHOU  Dongping LONG  Shuli ZHOU  Kai LIU
Affiliation:1. School of Geography and Planning, Center of Integrated Geographic Information Analysis,Sun Yat-sen University, Guangzhou 510275, China2. Guangdong Key Laboratory forUrbanization and Geo-simulation, Guangzhou 510275, China
Abstract:Theft from person (TFP) is one of the most common crimes in China. It is assumed that TFP is the result of interaction among motivated offenders, suitable targets and guardians. Specific routine activities and places can be important indicators for the TFPs. However, few studies can focus on the time differentiation of relationship between citizens' daily activities and TFPs. This study aims to narrow this gap by uncovering the time relationship between citizens' activities and TFPs, as well as the impacts of specific facilities on TFPs. Using the data of TFPs from the police, the sixth national census, facilities addresses and citizens activities log in a big city in south China, the whole day is divided into four stages (before dawn: 23:00-6:59, morning: 7:00-9:59, daytime: 10:00-17:59, night: 18:00-22:59). Spatial lag negative binomial regression models are built for the four stages accordingly. We find that the spatial and temporal aggregation of TFP is obvious for all the stages. Activities for buying food, shopping and entertainment are positively related to TFP while activity of dining out has no significant relationship with it. Besides, key factors that impact TFP vary from stage to stage. Before dawn, entertainment facilities, restaurants and food markets have positive influence on TFP. In the morning, the existence of food market, bus stations, restaurants and some entertainment facilities (cinema and net-bar) will improve the risks of TFP. In the daytime, subways, shops for daily supplement, some entertainment facilities (cinema, bar and net bar) have positive effect on TFP. At night, subway stations, shops, bars and net bars will increase the risk of TFP. In addition, possibility of combination of time geography and crime geography and its application are discussed in this study.
Keywords:theft from person  routine activity theory  time geography  different activities  facilities  time differentiation  
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