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PROGRESS IN GEOGRAPHY    2018, Vol. 37 Issue (8) : 1131-1139     DOI: 10.18306/dlkxjz.2018.08.012
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Drug-related crime risk assessment and predictive policing based on risk terrain modeling
ZHANG Ning(),WANG Dawei()
School of Criminology, People's Public Security University of China, Beijing 100038, China
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Abstract  

Crime is the product of a certain time and space. Research on crime cannot be separated from temporal and spatial analyses, as well as social, geographical, ecological, environmental, and other factors that generate crime. Risk terrain modeling technology was developed by American scholars for spatial risk assessment and predictive policing. It has been independently proven and tested in over 45 countries across six continents around the world and 35 states in the United States. It has been widely used in many fields such as predictive policing, homeland security, traffic accidents, public health, child abuse, environmental pollution, and urban development. It has achieved remarkable results in the crime research area of drug, arson, explosion, rape, robbery, and theft. This study adopted crime hotspot analysis and risk terrain modeling to analyze the risk factors, spatial blind spots, and risk terrain of narcotics crimes in 2015 in N City of the Yangtze River Delta region, explored the mechanism and evolution of drug crimes, and made a prediction on N City 2016 drug crime trend. The results show that N City drug crime presents obvious crime hotspots and crime cold spots. Rental housing, hotels, railway stations, banks, parking lots, entertainment venues, urban expressways, and Internet cafes are drug risk factors in the city. Risk terrain modeling is effective in predicting drug crimes. The narcotics departments of public security organs should put more police and energy to gradually limit and eliminate the hotspots that generate, attract, and promote crime.

Keywords drug-related crime      hotspot analysis      risk terrain modeling      risk assessment      predictive policing     
Fund:Changjiang River Administration of Navigational Affairs in Ministry of Transport of the People's Republic of China's Technology Project, No.201710012
Corresponding Authors: WANG Dawei     E-mail: 709626991@qq.com;wdw_ppsuc@163.com
Issue Date: 04 September 2018
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ZHANG Ning
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ZHANG Ning,WANG Dawei. Drug-related crime risk assessment and predictive policing based on risk terrain modeling[J]. PROGRESS IN GEOGRAPHY, 2018, 37(8): 1131-1139.
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http://www.progressingeography.com/EN/10.18306/dlkxjz.2018.08.012     OR     http://www.progressingeography.com/EN/Y2018/V37/I8/1131
Fig.1  Average nearest neighbor analysis of drug crimes in N City, 2015
Fig.2  K function and L function of drug crimes in N City, 2015
Fig.3  Drug crime Gi* hotspot analysis chart for N City, 2015
Fig.4  Kernel density analysis of drug crimes in N City, 2015
Tab.1  Optimized risk terrain modeling (RTM) model specifications
Fig.5  Risk terrain modeling (RTM) risk estimation overlaid with 2016 actual cases
Fig.6  Risk terrain model prediction and crime hotspot model prediction success rate comparison chart
[1] 陈鹏, 疏学明, 袁宏永, 等. 2011. 时空犯罪热点预测模型研究[J]. 系统仿真学报, 23(9): 1782-1786.http://d.wanfangdata.com.cn/Periodical/xtfzxb201109006
[1] [Chen P, Shu X M, Yuan H Y, et al.2011. Research about spatial-temporal forecasting of crime hotspot[J]. Journal of System Simulation, 23(9): 1782-1786.]
[2] 邓敏, 樊子德, 刘启亮. 2015. 空间分析实验教程[M]. 北京: 测绘出版社.
[2] [Deng M, Fan Z D, Liu Q L.2015. Experimental tutorial of spatial analysis[M]. Beijing, China: Surveying and Mapping Press.]
[3] 国家禁毒委员会办公室. 2017. 2016年中国毒品形势报告[EB/OL]. .http://www.nncc626.com/2017-04/06/c_129526120.htm,2017.4.6
[3] [Office of China National Narcotics Control Commission. 2017. China drug situation report 2016[EB/OL]. .]http://www.nncc626.com/2017-04/06/c_129526120.htm,2017.4.6
[4] 何志雄, 罗伟导, 丘志文, 等. 2004. 对吸毒原因的调查与分析[J]. 中国药物滥用防治杂志, 10(1): 20-23.http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_zgywlyfzzz200401007
doi: 10.3969/j.issn.1006-902X.2004.01.007
[4] [He Z X, Luo W D, Qiu Z W, et al.2004. The survey and analysis of the causes of drug abusing[J]. Chinese Journal of Drug Prevention and Treatment, 10(1): 20-23.]
[5] 姜超, 唐焕丽, 柳林. 2014. 中国犯罪地理研究述评[J]. 地理科学进展, 33(4): 561-573.http://d.wanfangdata.com.cn/Periodical/dlkxjz201404013
doi: 10.11820/dlkxjz.2014.04.013
[5] [Jiang C, Tang H L, Liu L.2014. Review of crime geography in China[J]. Progress in Geography, 33(4): 561-573.]
[6] 林大为. 2014. 毒品犯罪时空热点分析: 以台北市中山区为例[J]. 警学丛刊, 45(3): 115-150.
[6] [Lin D W.2014. Temporal and spatial hot spot analysis of drug crime: A case study of Zhongshan district of Taipei city[J]. Police Science Bimonthly, 45(3): 115-150.]
[7] 刘建宏. 2012. 国际犯罪学大师论犯罪控制科学(2)[M]. 北京: 人民出版社.
[7] [Liu J H.2012. Master criminologist on the science of crime control: Vol.2[M]. Beijing, China: People's Publishing House.]
[8] 陆娟, 汤国安, 张宏, 等. 2012. 犯罪热点时空分布研究方法综述[J]. 地理科学进展, 31(4): 419-425.http://d.wanfangdata.com.cn/Periodical_dlkxjz201204004.aspx
doi: 10.11820/dlkxjz.2012.04.004
[8] [Lu J, Tang G A, Zhang H, et al.2012. A review of research methods for spatiotemporal distribution of the crime hot spots[J]. Progress in Geography, 31(4): 419-425.]
[9] 单勇. 2016. 基于热点稳定性的犯罪空间分布规律再认识[J]. 法制与社会发展, 22(5): 118-130.http://www.cnki.com.cn/Article/CJFDTotal-SFAS201605011.htm
[9] [Shan Y.2016. A re-understanding of the distribution law of crime space based on hot spot stability[J]. Law and Social Development, 22(5): 118-130.]
[10] 王利荣, 揭萍. 2016. 毒品消费与供给关系实证分析: 以江西省毒情为样本[J]. 时代法学, 14(1): 8-21.http://d.wanfangdata.com.cn/Periodical/sdfx201601002
doi: 10.3969/j.issn.1672-769X.2016.01.002
[10] [Wang L R, Jie P.2016. Evidence study of the relationship between drug consumption and supply: Based on the drug analysis of Jiangxi[J]. Presentday Law Science, 14(1): 8-21.]
[11] 肖汉, 杜永慧, 徐金泽, 等. 2013. 融合GIS的犯罪概率模型及应用[J]. 北京大学学报:自然科学版, 49(6): 1025-1030.http://d.wanfangdata.com.cn/Periodical/bjdxxb201306012
[11] [Xiao H, Du Y H, Xu J Z, et al.2013. Integration of the GIS with criminal probability model and its application[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 49(6): 1025-1030.]
[12] 叶碧翠. 2016. 少年及成人施用第三、四级毒品犯罪空间初探: 以台北市为例[J]. 警学丛刊, 17(3): 57-88.
[12] [Ye B C.2016. A preliminary study on the application of the third and level 4 drug related crime in juvenile and adult: A case study of Taipei city[J]. Police Science Bimonthly, 17(3): 57-88.]
[13] Barnum J D, Campbell W L, Troccio S, et al.2016. Examining the environmental characteristics of drug dealing locations[J]. Crime & Delinquency,6: 1-26.http://www.researchgate.net/publication/303478594_Examining_the_Environmental_Characteristics_of_Drug_Dealing_Locations
doi: 10.1177/0011128716649735
[14] Braga A A, Papachristos A V, Hureau D W.2014. The effects of hot spots policing on crime: An updated systematic review and meta-analysis[J]. Justice Quarterly, 31(4): 633-663.http://www.tandfonline.com/doi/full/10.1080/07418825.2012.673632
doi: 10.1080/07418825.2012.673632
[15] Caeti T J.1999. Houston's targeted beat program: A quasi-experimental test of police patrol strategies[D]. Huntsville, TX: Sam Houston State University.
[16] Caplan J M, Kennedy L W.2011. Risk terrain modeling compendium[M]. Newark, NJ: Rutgers Center on Public Security.
[17] Caplan J M, Kennedy L W.2016. Risk terrain modeling: Crime prediction and risk reduction[M]. Berkeley, CA: University of California Press.
[18] Chainey S, Ratcliffe J.2005. GIS and crime mapping[M]. Hoboken, NJ: John Wiley & Sons.
[19] Gaziarifoglu Y, Kennedy L W. 2014. Applying risk terrain modeling to street robberies in Newark, NJ[J/OL]//ASC Annual Meeting. 2014-11-25 [2018-08-21]. .http://citation.allacademic.com/meta/p515712_index.html
[20] Gorman D M.2004. Alcohol outlet density and violence: a geospatial analysis[J]. Alcohol & Alcoholism, 4(39): 369-375.http://onlinelibrary.wiley.com/resolve/reference/PMED?id=15208173
doi: 10.1093/alcalc/agh062 pmid: 15208173
[21] Hollernan D, Gale R.2013. An application of risk terrain modeling to residential burglary[J]. TCNJ Journal of Student Scholarship, 15: 1-9.http://citation.allacademic.com/meta/p_mla_apa_research_citation/5/8/5/2/6/p585265_index.html
[22] Santos R B.2012. Crime analysis with crime mapping[M]. Thousand Oaks, CA: Sage Publications.
[23] United Nations Office on Drugs and Crime. 2016. UNODC annual report 2015[EB/OL].http://www.unodc.org/unodc/en/about-unodc/annual-report
[24] Weisburd D, Mazerolle L G.2000. Crime and disorder in drug hot spots: Implications for theory and practice in policing[J]. Police Quarterly, 3(3): 331-349.
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