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    Microscale prediction of near-future crime concentrations with street-level geosurveillance

    Shiode, Shino and Shiode, N. (2014) Microscale prediction of near-future crime concentrations with street-level geosurveillance. Geographical Analysis 46 (4), pp. 435-455. ISSN 0016-7363.

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    This article proposes a new type of geosurveillance method for monitoring elevated crime activities recorded at the disaggregate street address level. It is a prospective method that combines on a recently developed retrospective method for network-based space–time hot spot detection with a concept used in syndromic surveillance in epidemiology. This method detects emerging concentrations of crime activities at the street level by repeatedly sweeping across a street network using a flexible search window as new incidents are reported. Empirical analysis of drug incident data using a set of search windows with the same spatial extent but different temporal durations suggests that, while all window sizes raise an alarm against a sudden outburst of crime activities, the window with a longer temporal duration is more effective in the early detection of hot spots that are recurrent in nature as well as those that are slow in forming a concentration. A distribution of simulated hot spots is also used for examining the performance of the method in the form of days to detect. It shows that searches with a shorter temporal window can furnish a better performance in detecting hot spots that exhibit a sudden outburst with no recurrent pattern.


    Item Type: Article
    School: School of Social Sciences, History and Philosophy > Department of Geography
    Depositing User: Administrator
    Date Deposited: 24 Nov 2014 11:03
    Last Modified: 24 Nov 2014 11:03


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