多尺度探查偷车案件的犯罪时空热点

doi:10.3969/j.issn.1000-5641.2018.03.015

华东师范大学学报(自然科学版) ›› 2018, Vol. 2018 ›› Issue (3): 136-145.doi: 10.3969/j.issn.1000-5641.2018.03.015

多尺度探查偷车案件的犯罪时空热点

任浙豪^1,2, 张昊天^1,2, 刘苇航^1,2, 过仲阳^1,2

1. 华东师范大学地理信息科学教育部重点实验室, 上海 200241;
2. 华东师范大学地理科学学院, 上海 200241

收稿日期:2017-05-17 出版日期:2018-05-25 发布日期:2018-05-29
通讯作者: 过仲阳,男,教授,博士生导师,研究方向为数据挖掘、数据可视化.E-mail:zyguo@geo.ecnu.edu.cn E-mail:过仲阳,男,教授,博士生导师,研究方向为数据挖掘、数据可视化.E-mail:zyguo@geo.ecnu.edu.cn
作者简介:任浙豪,男,本科生,研究领域为数据挖掘、遥感图像分析.E-mail:13681956189@126.com.
基金资助:
国家理科基地科研训练及科研能力提高项目（J1310028）

Detecting spatiotemporal hotspots for vehicle thefts by multi-scale analysis

REN Zhe-hao^1,2, ZHANG Hao-tian^1,2, LIU Wei-hang^1,2, GUO Zhong-yang^1,2

1. Key Laboratory of Geographic Information Science(Ministry of Education), East China Normal University, Shanghai 200241, China;
2. School of Geographic Sciences, East China Normal University, Shanghai 200241, China

Received:2017-05-17 Online:2018-05-25 Published:2018-05-29

摘要/Abstract

摘要： 犯罪热点探查逐渐成为被动式转向主动式警务工作的关键.现有许多研究提出多种犯罪分析方法，得到较好成果.本文关注时空分析中的尺度问题，以某区偷盗"三车"案件为例，提出分析时空热点的两种多尺度方法，并据此分析，为警务实务提供参考.这两种方法与结论是：①结合尺度法与传统的严格法整合时间数据，在单尺度数据不足时也能探查到时间热点.分析得到研究区偷车案件存在较显著的30 d周期和极显著的20 h周期，警务工作可借此调整轮班时间.②以30 d周期作分析，在DBSCAN算法中设置评估函数（凸包案件密度中值），自适应选择最优尺度探查空间最优热点分布，分布的最优性由主流的PAI指数验证.分析得到研究区的某些地铁站与居民区需要重点防护.

关键词: 多尺度, 犯罪分析, 小波分析, DBSCAN, 凸包

Abstract: The detection of crime hot spots has become increasingly prominent in the conversion from reactive to active policing. There exist many crime analysis methods with good results. This paper focuses on scale effects in analysis. We proposed two multi-scale methods to detect temporal and spatial hotspots for vehicle thefts in a district, whose results were used for policing references. These two methods and their results are stated as follows:① a scaling method is proposed and combined with a rigid process to aggregate temporal data. Through this combination, temporal hotspots can be detected when data are not sufficient under mono-scale. Results showed that daily hot spots (30 days) and hourly hot spots (20 hours) of vehicle thefts are significant at the study site, on which the rearrangement of shift intervals can be based;② on the basis of daily hot spots, we set a median case density of a convex hull as the evaluation function when applying DBSCAN. The optimal scale, verified by the popular Prediction Accuracy Index, was adaptively chosen. We found that several metro line stations and residence zones need key protection.

Key words: multi-scale, crime analysis, wavelet analysis, DBSCAN, convex hull

中图分类号:

TP391.4

任浙豪, 张昊天, 刘苇航, 过仲阳. 多尺度探查偷车案件的犯罪时空热点[J]. 华东师范大学学报(自然科学版), 2018, 2018(3): 136-145.

REN Zhe-hao, ZHANG Hao-tian, LIU Wei-hang, GUO Zhong-yang. Detecting spatiotemporal hotspots for vehicle thefts by multi-scale analysis[J]. Journal of East China Normal University(Natural Sc, 2018, 2018(3): 136-145.

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多尺度探查偷车案件的犯罪时空热点

Detecting spatiotemporal hotspots for vehicle thefts by multi-scale analysis

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