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Crime Geosurveillance in Microscale Urban Environments: NetSurveillance

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  • Shino Shiode
  • Narushige Shiode

Abstract

Events and phenomena such as crime incidents and outbreak of an epidemic tend to form concentrations of high risk known as hotspots. Geosurveillance is an increasingly popular notion for detecting and monitoring the emergence of and changes in hotspots. Yet the existing range of methods is not designed to accurately detect emerging risks at the microscale of street address level. This study proposes NetSurveillance, a method for monitoring the emergence of significant concentrations of events along the intricate network of urban streets. Through a simulation test, the study demonstrates the high accuracy of NetSurveillance in detecting such clusters, outperforming its conventional counterpart conclusively when applied at the individual street address level. Empirical analysis of drug incidents from Chicago also illustrates its capacity to identify rapid outbursts of crimes as well as a more gradual buildup of such a concentration, and their disappearance, either as a one-off or as part of a recurrent hotbed.

Suggested Citation

  • Shino Shiode & Narushige Shiode, 2020. "Crime Geosurveillance in Microscale Urban Environments: NetSurveillance," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 110(5), pages 1386-1406, September.
    • Handle: RePEc:taf:raagxx:v:110:y:2020:i:5:p:1386-1406
    DOI: 10.1080/24694452.2019.1696663
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    Cited by:

    1. Danlin Yu & Chuanglin Fang, 2022. "How Neighborhood Characteristics Influence Neighborhood Crimes: A Bayesian Hierarchical Spatial Analysis," IJERPH, MDPI, vol. 19(18), pages 1-16, September.

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