摘要
基于道路交通网络的热点分析可以获取犯罪热点道路,从而为公安巡控、警务资源优化提供指导性意见。以等距路段为最小研究单元,采用等距路段热点研究方法识别分析北京市西城区2016年盗窃犯罪在道路交通网络上的分布情况。对于空间兴趣点(points of interest, POI)的10类源数据,采用主成分分析方法实现降维,通过多元线性回归对提取出的两类主成分因子进行犯罪影响因素解释。研究发现:北京市西城区盗窃犯罪在空间分布上呈高度聚集态势,少量路段聚集了大量犯罪;热点路段大都集中在人员流动性大、交通便利等地区;较不等距路段犯罪热点分析方法而言,等距路段犯罪热点分析方法可以更精准地实现热点路段的识别;提取两个主成分分别是与居民日常生活类和与居民精神文化类,与居民日常生活较多的区域对犯罪的发生呈正相关作用,与居民精神文化相关的区域对犯罪的发生呈反相关作用。研究结果可以为一线执法机关的警务资源分布优化、维护社会稳定提供安全防范依据。
Based on the hot spot analysis of road traffic network,hot spots of crime can be obtained,so as to provide guidance for police patrol and control and police resources optimization.The isometric road section was taken as the minimum research unit,and the isometric road section hot spot research method was adopted to identify and analyze the distribution of theft crimes on the road traffic network in Xicheng District,Beijing in 2016.For the 10 types of source data of points of interest(POI),dimension reduction was achieved by principal component analysis,and the two types of principal component factors were given explanation of influencing factors of crime by multiple linear regression.The research results show that the spatial distribution of theft crimes is highly concentrated in Xicheng District of Beijing,and a large number of crimes are concentrated in a few sections,where the hot sections are mostly concentrated in areas with high mobility and convenient transportation.Compared with the hot spot analysis method of unequal distance sections,the hot spot analysis method of equal distance sections can realize the identification of hot spots more accurately.The two principal components are respectively related to residents daily life and residents spiritual culture.The areas with more residents daily life have a positive correlation with the occurrence of crimes,while the areas with residents spiritual culture have a negative correlation with the occurrence of crimes.After all,the research results can provide safety precaution bases about optimizing the distribution of police resources and maintaining social stability for front-line law enforcement agencies.
作者
张勃
张馨泽
林艳
ZHANG Bo;ZHANG Xin-ze;LIN Yan(School of Information Technology and Cyber security,People s Public Security University of China,Beijing 100038,China;Key Laboratory of Security Technology&Risk Assessment,Ministry of Public Security,Beijing 102623,China)
出处
《科学技术与工程》
北大核心
2022年第21期9437-9446,共10页
Science Technology and Engineering
基金
国家自然科学基金(41971367)。
