| 涉毒人员日常活动对盗窃警情空间格局影响的时间差异 |
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| 引用本文： | 柳林,孙秋远,肖露子,宋广文,陈建国.涉毒人员日常活动对盗窃警情空间格局影响的时间差异[J].地球信息科学,2021,23(12):2187-2200. |
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| 作者姓名： | 柳林 孙秋远 肖露子 宋广文 陈建国 |
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| 作者单位： | 广州大学地理科学与遥感学院公共安全地理信息分析中心,广州510006;辛辛那提大学地理系,辛辛那提OH45221-1031,美国;广州大学地理科学与遥感学院公共安全地理信息分析中心,广州510006 |
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| 基金项目： | 国家自然科学基金项目(41901177);国家自然科学基金项目(42001171);国家自然科学基金项目(42071184);广东省自然科学基金项目(2019A1515011065);广州市科技计划项目(201804020016) |
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| 摘 要： | 根据日常活动理论,犯罪时空格局与受害者、犯罪者日常活动规律均存在较强关系。但受限于数据获取难度,较缺乏有关犯罪者日常活动与实际警情时空格局的研究。已有文献表明涉毒人员与盗窃等财产犯罪存在较大相关性。基于此,本研究通过分析涉毒人员日常活动对盗窃警情时空格局的影响,验证犯罪者日常活动在塑造盗窃警情时空格局中的作用。本文以中国南部大城市ZG市XT派出所为例,以150 m×150 m的格网为分析单元,采用盗窃警情数据、涉毒人员日常活动数据、POI数据以及巡逻盘查数据,划分不同时间段分别建立泊松回归模型。研究发现：① 相对于传统静态的抓获或警情数据,动态的潜在犯罪者、受害者日常活动数据可更有效地提高盗窃模型的拟合优度;② 相对于全天汇总的总人数,动态近实时的涉毒人员活动与居民活动能更好地解释盗窃的空间分布;③ 静态的土地利用混合度在不同时段对盗窃具有不同的影响作用。以上结果验证了涉毒人员日常活动与盗窃警情的时空格局的关系,研究结论验证和丰富了日常活动理论,可为实际犯罪预测与警力布置提供一定的参考。
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| 关 键 词： | 盗窃警情 潜在犯罪者 涉毒人员 日常活动理论 时空格局 泊松回归 |
| 收稿时间： | 2021-02-05 |
The Temporal Influence Difference of Drug-related Personnels' Routine Activity on the Spatial Pattern of Theft |
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| LIU Lin,SUN Qiuyuan,XIAO Luzi,SONG Guangwen,CHEN Jianguo.The Temporal Influence Difference of Drug-related Personnels' Routine Activity on the Spatial Pattern of Theft[J].Geo-information Science,2021,23(12):2187-2200. |
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| Authors: | LIU Lin SUN Qiuyuan XIAO Luzi SONG Guangwen CHEN Jianguo |
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| Institution: | 1. Center of GeoInformatics for Public Security, School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China2. Department of Geography, University of Cincinnati, Cincinnati, OH 45221-0131, USA |
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| Abstract: | According to the routine activity theory, the spatiotemporal pattern of crime is strongly related to routine activity of victims and offenders. However, due to the difficulty of data acquisition, there is a lack of research on offenders' routine activity and the spatiotemporal pattern of crime events. The existing literature shows that there is a great correlation between drug-related persons and property crimes such as theft. Based on this, this study verifies the role of the routine activity of offenders in shaping the spatial-temporal pattern of theft through analyzing the impact of the routine activity of drug-related persons on theft. In this paper, taking XT police district with 150 m×150 m grids in ZG city in southern China as an example, the theft data, routine activity data of drug-related persons, POI data, and patrol and interrogation data were used. Poisson regression models were established respectively in different periods. The results show that, firstly, compared with traditional static arrest or policing events data, active routine activity data of potential offenders and victims could promote goodness of fit in models effectively. Secondly, compared with total amount of people in whole day, active real-time activity data of drug-related personnel and residents could explain the spatial pattern of theft better. Thirdly, static land use density has a different influence on theft events in different periods. The above results verify the relationship between the routine activity of drug-related persons and the spatiotemporal pattern of theft. The research conclusions verify and enrich the routine activity theory, which can provide a certain reference for the actual crime prediction and police deployment. |
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| Keywords: | theft events potential offenders drug-related persons routine activity theory spatiotemporal pattern Poisson regression |
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