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Identifying the Spatio-Temporal Characteristics of Crime in Liangshan Prefecture, China

Author

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  • Wuxue Cheng

    (The Faculty Geography Resources Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu 610066, China)

  • Yajun Rao

    (The Faculty Geography Resources Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu 610066, China)

  • Yixin Tang

    (The Faculty Geography Resources Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu 610066, China)

  • Jiajia Yang

    (The Faculty Geography Resources Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu 610066, China)

  • Yuxin Chen

    (The Faculty Geography Resources Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu 610066, China)

  • Li Peng

    (The Faculty Geography Resources Sciences, Sichuan Normal University, Chengdu 610101, China
    Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu 610066, China)

  • Jiangcheng Hao

    (Xi’an Yirun Cultural Landscape Planning and Design Co., Ltd., Xi’an 710075, China)

Abstract

Crime prevention and governance play critical roles in public security management. Liangshan Yi Autonomous Prefecture in Sichuan Province has a high crime rate, and spatio-temporal analysis of crime in this region could assist with public security management. Therefore, Liangshan Prefecture was selected as the research object in this study. The spatial crime data were obtained from China Judgments Online, and property crime, violent crime, and special crime (i.e., pornography, gambling, drugs, and guns) were analyzed. The findings were as follows. In terms of time characteristics (month, day, and hour), property crime tended to occur in autumn and winter, in the early month, on Wednesdays and Fridays, and at early morning. Violent crime tended to occur in winter and spring, on Mondays and Thursdays, and at night. Special crime occurred in spring and autumn, on Tuesdays, and in the daytime. In terms of spatial features, the central region of Liangshan Prefecture was the focal area for crime. There were obvious low-aggregation areas in the western region for special crime. The eastern region exhibited a high incidence of various crimes. Regarding the spatio-temporal evolution characteristics from 2013 to 2019, there were some obvious hotspots of violent and property crime in downtown and surrounding townships of Xichang City, which is the capital of Liangshan Prefecture. During the study period, the incidence of special crime has an obvious downward trend which shows that there are more new cold spots.

Suggested Citation

  • Wuxue Cheng & Yajun Rao & Yixin Tang & Jiajia Yang & Yuxin Chen & Li Peng & Jiangcheng Hao, 2022. "Identifying the Spatio-Temporal Characteristics of Crime in Liangshan Prefecture, China," IJERPH, MDPI, vol. 19(17), pages 1-14, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:17:p:10862-:d:902807
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    References listed on IDEAS

    as
    1. Wang, Chuhong & Liu, Xingfei & Yan, Zizhong & Zhao, Yi, 2022. "Higher education expansion and crime: New evidence from China," China Economic Review, Elsevier, vol. 74(C).
    2. Wei Song & Daqian Liu, 2013. "Exploring Spatial Patterns of Property Crime Risks in Changchun, China," International Journal of Applied Geospatial Research (IJAGR), IGI Global, vol. 4(3), pages 80-100, July.
    3. Liu, Xingfei & Wang, Chuhong & Yan, Zizhong & Zhao, Yi, 2022. "Higher Education Expansion and Crime: New Evidence from China," Working Papers 2022-2, University of Alberta, Department of Economics.
    4. Álvaro Briz‐Redón & Jorge Mateu & Francisco Montes, 2022. "Identifying crime generators and spatially overlapping high‐risk areas through a nonlinear model: A comparison between three cities of the Valencian region (Spain)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(1), pages 97-120, February.
    Full references (including those not matched with items on IDEAS)

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