近10年来犯罪时空预测国内外研究与实践进展  

Progress in Research and Practice of Spatial-temporal Crime Prediction over the Past Decade

作　　者：贺日兴 陆宇梅 姜超 邓悦 李欣然 时东 HE Rixing;LU Yumei;JIANG Chao;DENG Yue;LI Xinran;SHI Dong(College of Resources Environment and Tourism,Capital Normal University,Beijing 100048,China;Key Laboratory of 3D Information Acquisition and Application,MOE,Capital Normal University,Beijing 100048,China;College of Urban Economics and Public Administration,Capital University of Economics and Business,Beijing 100070,China;Beijing Key Laboratory of Megaregions Sustainable Development Modeling,Beijing 100070,China)

机构地区：[1]首都师范大学资源环境与旅游学院,北京100048 [2]首都师范大学三维数据获取与应用教育部重点实验室,北京100048 [3]首都经济贸易大学城市经济与公共管理学院,北京100070 [4]城市群系统演化与可持续发展的决策模拟研究北京市重点实验室,北京100070

出　　处：《地球信息科学学报》2023年第4期866-882,共17页Journal of Geo-information Science

基　　金：国家重点研发计划项目(2022YFB3903600);公安部科技强警基础工作专项(2021JC35);国家自然科学基金青年项目(42001159);首都师范大学校内专项(2255109);首都经济贸易大学北京市属高校基本科研业务费专项资金(XRZ2022008)。

摘　　要：基于地点的犯罪时空预测由于不直接涉及个人数据,且可与警务巡逻和精准化治安防控策略有机结合,现已成为预测性警务领域的研究热点和主要实践方向。本文对2013年以来国内外犯罪时空预测的最新进展进行综述,主要工作包括:①总结了该领域研究在文献数量快速增加、研究主题日益多元、主要研究群体分布相对集中等方面的总体特征;②梳理了犯罪时空预测的目标主体、时间尺度、空间尺度、模型方法、精度评价、实践效果评估六大基本要素的新变化、新指标或新进展;③介绍了常用犯罪时空预测软件及各国预测性警务实践;④探讨了在实践应用的各个阶段所面临的伦理问题及挑战,以及各界为规避此问题做出的尝试;⑤展望了犯罪时空预测后续研究重点。本研究为犯罪时空预测领域勾勒出一个较为全面和清晰的轮廓,可为国内犯罪地理、智慧警务、警用地理信息系统(PGIS)等相关领域的研究者和从业人员提供有益参考。As a forward-looking and proactive policing mode,predictive policing has been a major innovation of modern policing reforms across the USA and European countries since it was proposed in 2008.As it does not involve the use of personal privacy data and can be integrated with police patrolling and precise crime prevention strategies,place-based spatial-temporal crime prediction has been a hot research topic and main component of policing practices.This research presents a systematic review of the progress of spatial-temporal crime prediction across the world since 2013 when the RAND Corporation released its special report on predictive policing.It contributes to the literature with the following five aspects:(1)summarizing the new trends in the field of spatiotemporal crime prediction studies in terms of the number of papers,research topics,leading scholars,and academic journals.The studies on spatial-temporal crime prediction have received extensive attention from various countries in recent years,and the research themes have shown a diversified trend.The most productive scholars are mainly from China and the USA,with the main focus on spatialtemporal crime prediction model development;(2)describing the new dynamics and progress of six basic components involved in the spatial-temporal crime prediction research,which are the prediction target,temporal scale,spatial scale,prediction method,performance evaluation measure,and practical evaluation.The four most widely studied types of crimes are theft,robbery,burglary,and motor vehicle theft.For burglary crime,the typical temporal unit for spatial-temporal prediction is 1-month;For the other three types of crime,the typical temporal unit is 1-day.For these four types of crime,the typical spatial unit is 200-meter grid.The top three models with the best prediction performance are random forest model,spatial-temporal neural network model,and Hawkes process model;(3)introducing several main commercial softwares for spatial-temporal crime prediction and global predictive p

关 键 词：犯罪预测 时空尺度 预测性警务 主动型警务 智慧警务 伦理问题 犯罪分析 犯罪地理 

分 类 号：D917.3[政治法律—法学]