Crime analysis mapping in the UK: a GIS analysis of burglaries in Leicestershire

Burnham, Jahnavi (2014) Crime analysis mapping in the UK: a GIS analysis of burglaries in Leicestershire. In: 42nd Australian and New Zealand Map Society Conference (GeoCart 2014): Cartographic Journaeys through Space and Time, 3-5 Sep 2014, Auckland, New Zealand.

Abstract

Crime mapping studies have a history of more than 150 years. However, in the past, studies on Crime Analysis mapping have advanced due to the advent of GIS. GIS gives an array of suitable capabilities for crime analysis mapping. The present study utilises GIS to examine the relationships between burglaries and the socio-demographic characteristics in the context of Leicestershire County, UK, with a hypothesis that the socio-economic status can influence the crime patterns and crime rate of particular area. The factors such as population density, unemployment, and single households are considered for this study. The other factors such as types of houses, occupancy and tenure/ownership are also investigated. Using the regression analysis models - Geographically Weighted Regression (GWR) and Ordinary Least-Squares (OLS), the variations in the relationships are examined. The local and global significant variables are successfully identified and mapped. These variables are both locally and globally significant. The practical implication of the regression analysis techniques is that, by exploring the local processes that drive crime levels it is possible to implement crime prevention policies in different locations.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © New Zealand Cartographic Society Inc 2014. Permanent restricted access to published version due to publisher copyright policy.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 24 Apr 2015 04:36
Last Modified: 17 Jul 2017 23:55
Uncontrolled Keywords: crime mapping; GIS; geographically weighted regression; ordinary least squares regression; socio-economic characteristics
Fields of Research : 01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics
16 Studies in Human Society > 1602 Criminology > 160205 Police Administration, Procedures and Practice
09 Engineering > 0909 Geomatic Engineering > 090903 Geospatial Information Systems
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
URI: http://eprints.usq.edu.au/id/eprint/27060

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