Microscale Prediction of Near‐Future Crime Concentrations with Street‐Level Geosurveillance. Issue 4 (17th September 2014)

• Record Type: Journal Article
• Authors: Shiode, Shino; Shiode, Narushige
• Is Part Of: Geographical analysis. Volume 46:Issue 4(2014)
• Page Start: 435
• Page End: 455
• Publication Date: 2014-09-17
• Subjects: Geography -- Methodology -- Periodicals; Electronic journals; 910.00182
• DOI: 10.1111/gean.12065
• Languages: English
• ISSNs: 0016-7363

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>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.</p> </abstract>