EN中文

地理科学进展 >

2012 , Vol. 31 >Issue 4: 419 - 425

DOI: https://doi.org/10.11820/dlkxjz.2012.04.004

理论与方法研究

犯罪热点时空分布研究方法综述

展开
  • 1. 南京师范大学虚拟地理环境教育部重点实验室, 南京 210046;
    2. 南京市公安局,南京 210005

收稿日期: 2011-08-01

  修回日期: 2011-10-01

  网络出版日期: 2012-04-25

基金资助

“十一五”国家科技支撑计划项目(2008BAH23B01).

收起

A Review of Research Methods for Spatiotemporal Distribution of the Crime Hot Spots

Expand
  • 1.Key laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing 210046, China;
    2. Nanjing Public Security Bureau, Nanjing 210005, China

Received date: 2011-08-01

  Revised date: 2011-10-01

  Online published: 2012-04-25

Fold

摘要

犯罪在地理时空内并不是均匀分布的,而是表现出明显的时空聚集特性,这种聚集性常用“犯罪热点”表述.基于对犯罪热点的理解,从犯罪热点时空分布模式、犯罪热点成因分析以及犯罪热点时空转移及预测等3 个方面总结了当前国内外犯罪热点时空分布相关研究方法的进展.最后,对该领域研究进行了总结与展望.总体上,国内相关研究较少,尚需进一步结合中国国情,提出适用方法.另外,也需要通过相关犯罪理论的深入研究以及其他领域研究方法的借鉴,实现犯罪热点时空分布研究方法的突破与创新.

关键词： 犯罪; 犯罪热点; 时空分布; 研究方法

本文引用格式

陆娟, 汤国安, 张宏, 蒋平, 吴伟 . 犯罪热点时空分布研究方法综述[J]. 地理科学进展, 2012 , 31(4) : 419 -425 . DOI: 10.11820/dlkxjz.2012.04.004

Abstract

Crime is not distributed uniformly within the geographic time and space, and it shows significant spatial and temporal aggregation, which is called the "crime hot spots". Based on the understanding of crime hot spots, this paper reviews the current international development of research methods for the spatiotemporal distribution of crime hot spots in three aspects, including spatiotemporal patterns, cause analysis methods and spatiotemporal transfer and forecast. Finally, this paper summarizes the research about spatiotemporal distribution analysis of crime hot spots and made prospects of its future trends. On the whole, there have been relatively fewer related domestic research, so we should enhance some methods for crime analysis in combination of China's national conditions. In addition, some breakthroughs and innovations need to be made in the research methods for the spatiotemporal distribution of crime hot spots through in-depth research of the crime theory and the research in other fields as a reference.

Key words： crime; crime hot spots; research methods; spatiotemporal distribution

参考文献

[1] 孙峰华, 李世泰, 黄丽萍. 中外犯罪地理规律实证研究.人文地理, 2006, 21(5): 14-18.
[2] 孙峰华, 魏晓. 犯罪地理学研究的新进展. 人文地理,2004, 19(5): 60-63.
[3] Johnson S D. Repeat burglary victimization: A tale of twotheories. Journal of Experimental Criminology, 2008, 4(3): 215-240.
[4] 赵勇, 刘民, 柏书华, 等. 系列入室盗窃案件的犯罪距离研究. 中国人民公安大学学报: 社会科学版, 2010(2):143-149.
[5] Grubesic T H, Mack E A. Spatial-temporal interaction ofurban crime. Journal of Quantitative Criminology, 2008,24(3): 285-306.
[6] Bowers K J, Johnson S D. Domestic burglary repeats andspace-time clusters. European Journal of Criminology,2005, 2(1): 67-92.
[7] Chainey S, Ratcliffe J H. GIS and Crime Mapping. Chichester:Wiley, 2005.
[8] 刘战国, 郜昂. 城中村犯罪热点研究: 以深圳L 村为例.中国公共安全: 学术版, 2010(3): 9-12.
[9] Harries K. Mapping Crime: Principles and Practice.WashingtonDC: National Institute of Justice, 1999: 38-62.
[10] Anselin L, Cohen J, Cook D, et al. Spatial analyses ofcrime. Washington DC: National Institute of Justice,2000: 87-96.
[11] 李小文, 曹春香, 常超一. 地理学第一定律与时空邻近度的提出. 自然杂志, 2007, 29(4): 69-71.
[12] 陈彦光. 基于Moran统计量的空间自相关理论发展和方法改进. 地理研究, 2009, 28(6): 1449-1463.
[13] Levine N. CrimeStat III. Washington DC: the National Instituteof Justice, 2009.
[14] Mitchell A. The ESRI Guide to GIS Analysis : Volume 2:Spatial Measurements and Statistics. Redlands: EsriPress, 2005.
[15] 张志杰, 彭文祥, 周艺彪, 等. 空间点模式分析中离散趋势的描述研究及应用. 中国卫生统计, 2008, 25(5):470-473.
[16] 王超, 赵文吉, 周大良. 基于GIS的犯罪分析系统研究与设计. 首都师范大学学报: 自然科学版, 2010, 31(3):47-52.
[17] 王劲峰, 廖一兰, 刘鑫. 空间数据分析教程. 北京: 科学出版社, 2010: 74-81.
[18] Cohen J, Garman S, Gorr W L. Empirical calibration oftime series monitoring methods using receiver operatingcharacteristic curves. International Journal of Forecasting,2009, 25(3): 484-497.
[19] Gorr W L. Forecast accuracy measures for exception reportingusing receiver operating characteristic curves. InternationalJournal of Forecasting, 2009, 25(1): 48-61.
[20] 孙吉贵, 刘杰, 赵连宇. 聚类算法研究. 软件学报, 2008,19(1): 48-61.
[21] 邓敏, 刘启亮, 李光强, 等. 基于场论的空间聚类算法.遥感学报, 2010, 14(4): 702-709.
[22] 颜峻. 基于时空数据挖掘的社会安全(刑事)事件成因研究[D]. 清华大学, 2009.
[23] 颜峻, 袁宏永, 疏学明. 用于犯罪空间聚集态研究的优化聚类算法. 清华大学学报, 2009, 49(2): 176-178.
[24] Gorr W L, Olligschlaeger A, Thompson Y. Short-termforecasting of crime. International Journal of Forecasting,2003, 19(4): 579-594.
[25] Eck J E, Chainey S P, Cameron J, et al. Mapping Crime:Understanding hotspots. Washington DC: National Instituteof Justice, 2005.
[26] Poulsen E, Kennedy L W. Using dasymetric mapping forspatially aggregated crime data. Journal of QuantitativeCriminology, 2004, 20(3): 243-263.
[27] Harries K. Extreme spatial variations in crime density inBaltimore County. Geoforum, 2006, 37(3): 404-416.
[28] Cusimano M, Marshall S, Rinner C, et al. Patterns of urbanviolent injury: A spatio-temporal analysis. PLoSONE 5(1): e8669.
[29] 陈鹏, 疏学明, 颜峻, 等. 犯罪活动在一天内的发生时间规律. 清华大学学报: 自然科学版, 2009, 49(12):2032-2035.
[30] 梅建明. 论环境犯罪学的起源、发展与贡献. 中国人民公安大学学报: 社会科学版, 2006(5): 66-72.
[31] Ronald E. Wilson. The impact of software on crime mapping:An introduction to a special journal issue of socialscience computing review on crime mapping. Social ScienceComputer Review, 2007, 25(2): 135-142.
[32] Brantingham P L, Brantingham P J. The Rules of CrimePattern Theory. Devon,UK:Willan Publishing, 2008.
[33] 杨英姿. 国外城市社区空间环境与犯罪关系理论研究综述. 现代城市研究, 2011(2): 78-85.
[34] Andresen M A. Crime measures and the spatial analysisof criminal activity. British Journal of Criminology,2006, 46(2): 258-285.
[35] Phillips P, Lee I. Criminal Cross Correlation Mining andVisualization. Lecture Notes in Computer Science, 2009,Vol 5477: 2-13.
[36] Wang F H. Job access and homicide patterns in Chicago:An analysis at multiple geographic levels based onscale-space theory. Journal of Quantitative Criminology,2005, 21(2): 98-105.
[37] 于嘉. 长春市犯罪空间分析[D]. 东北师范大学, 2010.
[38] 王法辉. 基于GIS 的数量方法与应用. 北京: 商务印书馆, 2009: 184-232.
[39] 陈凯. 基于灰色关联分析法的毒品犯罪群实证研究[D].湘潭大学, 2010.
[40] Cracolici M F, Uberti T E. Geographical distribution ofcrime in Italian provinces: A spatial econometric analysis.Jahrbuch fur Regional wissenschaft, 2009, 29(1):1-28.
[41] 颜峻, 疏学明, 袁宏永. 盗窃犯罪空间分布与地理因素的关联. 清华大学学报: 自然科学版, 2010, 50(2):174-186.
[42] Ceccato V, Haining R. Short and medium term dynamicsand their influence on acquisitive crime rates in the transitionstates of Estonia, Latvia and Lithuania. Spatial Analysis,2008, 1(3): 215-244.
[43] Wing M G, Tynon J F. Crime mapping and spatial analysisin national forests. Journal of Forestry, 2006, 104(6):293-296.
[44] Breetzke G. Exploratory spatial data analysis(ESDA) ofviolent, economic and sexual offenders in the city of Tshwane,South Affica. Acta Criminologica, 2008, CRIMSAConference Special Edition (1): 131-149.
[45] Neumayer E. Inequality and violent crime: Evidencefrom data on robbery and violent theft. Journal of PeaceResearch, 2005, 42(1): 101-112.
[46] 王法辉. 社会科学和公共政策的空间化和GIS 的应用.地理学报, 2011, 66(8): 1089-1100.
[47] Lockwood D. Mapping crime in Savannah social disadvantage,land use, and violent crimes reported to the police.Social Science Computer Review, 2007, 25(2):194-209.
[48] 毛媛媛, 戴慎志, 沈志联. 国内城市空间环境与犯罪关系研究评析. 人文地理, 2010, 25(3): 41-46.
[49] 于静. 城市空间环境与城市犯罪. 兰州大学学报, 2008,36(3): 116-122.
[50] 毛媛媛, 戴慎志. 犯罪空间分布与环境特征: 以上海市为例. 城市规划学刊, 2006(3): 85-93.
[51] 王益澄, 林玲. 东部沿海城市犯罪问题的城市地理学研究: 以浙江省宁波市为例. 宁波大学学报: 人文科学版,2009, 22(1): 109-113.
[52] 余建辉, 张文忠, 王岱, 等. 基于居民视角的居住环境安全性研究进展. 地理科学进展, 2011, 30(6): 699-705.
[53] 颜峻, 袁宏永, 疏学明. 社会安全事件空间分布研究. 中国安全科学学报, 2008, 18(7): 39-42.
[54] 王发曾. 城市犯罪空间盲区的综合治理研究. 地理研究, 2010, 29(1): 57-67.
[55] 王发曾. 城市犯罪中特殊空间盲区的综合治理. 华东政法大学学报, 2007(5): 56-62.
[56] 王发曾. 我国城市犯罪空间防控研究二十年. 人文地理, 2010, 25(4): 25-30.
[57] Ratcliffe J H. Crime mapping and the training needs oflaw enforcement. European Journal on Criminal Policyand Research, 2004, 10(1): 65-83.
[58] Ratcliffe J H. Detecting spatial movement of intra-regioncrime patterns over time. Journal of Quantitative Criminology,2005, 21(1): 103-123.
[59] Harries K. Property crimes and violence in United States:An analysis of the influence of population density. InternationalJournal of Criminal Justice Sciences, 2006, 1(2):24-34.
[60] Clarke R V, Eck J. Become a problem-solving crime analystin 55 small steps. London:Willan Publishing, 2003.
[61] Gorr W L, Harries R. Introduction to crime forecasting.International Journal of Forecasting, 2003, 19(4):551-555.
[62] Talib M S, Sallehuddin R, Hassan S Z A. Forecastingmodel for residential burglary. Proceedings of the 2ndIMT-GT Regional Conference on Mathematics,Statisticsand Applications, 2006.
[63] 王欣. 治安预测方法与技术比较研究. 中国人民公安大学学报: 自然科学版, 2011(3): 29-35.
[64] Gorr W L, Olligschlaeger A M, Thompson Y. Short-termtime series forecasting of crime. The International Journalof Forecasting, Special Section on Crime Forecasting,2003, 19(4): 579-594.
[65] Moffatt J A F. Crime Potential Modelling: A GIS-basedMethod Using Weights-of-evidence[D]. Carleton University,2005.
[66] Deadman D. Forecasting residential burglary. Internation-al Journal of Forecasting, 2003, 19(4): 567-578.
[67] Laukkanen M, Santtila P, Jern P, et al. Predicting offenderhome location in urban burglary series. Forensic ScienceInternational, 2008, 178(2): 224-235.
[68] Liu H, Brown D E. Criminal incident prediction using apoint-pattern-based density model. International Journalof Forecasting, 2003, 19(4): 603-622.
[69] Xue Yifei, Brown D E. Spatial analysis with preferencespecification of latent decision makers for criminal eventprediction. Decision Support Systems, 2006, 41(3): 560-573.
[70] 陈鹏, 疏学明, 袁宏永, 等. 时空犯罪热点预测模型研究. 系统仿真学报, 2011, 23(9): 1782-1786.
[71] 薛钟, 乔良, 王峰, 等. 连续犯罪预测的区域覆盖加权模型(AOWM). 数学实践与认识, 2010, 40(15): 212-217.
[72] Goldstein D G, Gigerenzer G. Fast and frugal forecasting.International Journal of Forecasting, 2009, 25(4):760-772.
[73] Tompson L, Townsley M. Back to the future: Usingspace-time patterns to better predict the location of streetcrime. International Journal of Police Science and Management,2010, 12(1): 23-40.
Options
文章导航

/

〈 〉