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Non-Homogeneous Diffusion of Residential Crime in Urban China

Author

Listed:
  • Yicheng Tang

    (State Key Lab of Information Engineering in Surveying Mapping and Remote Sensing & Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China)

  • Xinyan Zhu

    (State Key Lab of Information Engineering in Surveying Mapping and Remote Sensing & Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China)

  • Wei Guo

    (State Key Lab of Information Engineering in Surveying Mapping and Remote Sensing & Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China)

  • Xinyue Ye

    (Department of Geography, Kent State University, Kent, OH 42240, USA)

  • Tao Hu

    (State Key Lab of Information Engineering in Surveying Mapping and Remote Sensing & Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China)

  • Yaxin Fan

    (State Key Lab of Information Engineering in Surveying Mapping and Remote Sensing & Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China)

  • Faming Zhang

    (State Key Lab of Information Engineering in Surveying Mapping and Remote Sensing & Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China)

Abstract

The relationship between crime and urban environment has always been the focus of crime geography. Like diseases which can transmit and diffuse, crimes may also spread during a certain period of time and to a certain area by the near-repeat effect. Traditional near-repeat analysis focuses on the spatial spread of crimes to adjacent areas, with little regard to the displacement effect. Crime displacement refers to the relocation of criminal events as a result of policing efforts. If this phenomenon is neglected, the near-repeat analysis will tend not to obtain the overall spatial distribution pattern of criminal cases, leading to limited effectiveness of crime control. This paper presents a non-homogeneous diffusion model where crime spreads not only to spatially and temporally adjacent areas, but also to areas with similar environmental characteristics. By virtue of spatial constraints and environmental characteristics, the most vulnerable areas are identified, and this will be helpful for developing policing strategy as well as for sustainable community development.

Suggested Citation

  • Yicheng Tang & Xinyan Zhu & Wei Guo & Xinyue Ye & Tao Hu & Yaxin Fan & Faming Zhang, 2017. "Non-Homogeneous Diffusion of Residential Crime in Urban China," Sustainability, MDPI, vol. 9(6), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:6:p:934-:d:100343
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    References listed on IDEAS

    as
    1. Ling Wu & Xinyue Ye & David Webb, 2012. "Space-Time Analysis of Auto Burglary Patterns in a Fast-Growing Small City," International Journal of Applied Geospatial Research (IJAGR), IGI Global, vol. 3(4), pages 69-86, October.
    2. Nils-Bastian Heidenreich & Anja Schindler & Stefan Sperlich, 2013. "Bandwidth selection for kernel density estimation: a review of fully automatic selectors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 403-433, October.
    3. Enrico di Bella & Matteo Corsi & Lucia Leporatti & Luca Persico, 2017. "The spatial configuration of urban crime environments and statistical modeling," Environment and Planning B, , vol. 44(4), pages 647-667, July.
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    Cited by:

    1. Dongping Long & Lin Liu & Jiaxin Feng & Suhong Zhou & Fengrui Jing, 2018. "Assessing the Influence of Prior on Subsequent Street Robbery Location Choices: A Case Study in ZG City, China," Sustainability, MDPI, vol. 10(6), pages 1-16, May.
    2. Fengrui Jing & Lin Liu & Suhong Zhou & Guangwen Song, 2020. "Examining the Relationship between Hukou Status, Perceived Neighborhood Conditions, and Fear of Crime in Guangzhou, China," Sustainability, MDPI, vol. 12(22), pages 1-19, November.

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