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Modeling Spatial Interactions between Areas to Assess the Burglary Risk

GIScience Research Group, Institute of Geography, Heidelberg University, Berliner Street 48, Heidelberg D-69120, Germany
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(4), 47;
Received: 10 February 2016 / Revised: 27 March 2016 / Accepted: 29 March 2016 / Published: 1 April 2016
(This article belongs to the Special Issue Frontiers in Spatial and Spatiotemporal Crime Analytics)
It is generally acknowledged that the urban environment presents different types of risk factors, but how the structural effects of areas influence the risk levels in neighboring areas has been less widely investigated. This research assesses the local effects of burglary contributory factors on burglary over small areas in a large metropolitan region. A comparative framework is developed for analyzing the effects of geographic dependence on burglary rates, and for assessing how such dependence conditions the community context and the urban land use. A local indicators spatial autocorrelation analysis assesses burglaries over five years (2011–2015) to identify risk clusters. Thereafter, effects of different variables (e.g., unemployment, building density) on burglary frequency are estimated in a series of regression models while controlling for changes in the risk levels of nearby surrounding areas. Results uncover strong evidence that the configuration of the surroundings influences risk. After controlling for area-based interaction, patterns are identified that contrast with the previous literature, such as lower burglary frequency in areas with higher tenancy in social housing units. Together the findings demonstrate that the spatial arrangement of areas is as crucial as contextual crime factors, particularly when assessing the risk for small areas. View Full-Text
Keywords: burglary; spatial dependence; risk assessment burglary; spatial dependence; risk assessment
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MDPI and ACS Style

Mburu, L.W.; Bakillah, M. Modeling Spatial Interactions between Areas to Assess the Burglary Risk. ISPRS Int. J. Geo-Inf. 2016, 5, 47.

AMA Style

Mburu LW, Bakillah M. Modeling Spatial Interactions between Areas to Assess the Burglary Risk. ISPRS International Journal of Geo-Information. 2016; 5(4):47.

Chicago/Turabian Style

Mburu, Lucy W., and Mohamed Bakillah. 2016. "Modeling Spatial Interactions between Areas to Assess the Burglary Risk" ISPRS International Journal of Geo-Information 5, no. 4: 47.

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