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Examining the influence of cell size and bandwidth size on kernel density estimation crime hotspot maps for predicting spatial patterns of crime

Chainey, SP; (2013) Examining the influence of cell size and bandwidth size on kernel density estimation crime hotspot maps for predicting spatial patterns of crime. Bulletin of the Geographical Society of Liege , 60 pp. 7-19. Green open access

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Abstract

Hotspot mapping is a popular technique used for helping target police patrols and other crime reduction initiatives. There are a number of spatial analysis techniques that can be used for identifying hotspots, but the most popular in recent years is kernel density estimation (KDE). KDE is popular because of the visually appealing way it represents the spatial distribution of crime, and because it is considered to be the most accurate of the commonly used hotspot mapping techniques. To produce KDE outputs, the researcher is required to enter values for two main parameters: the cell size and bandwidth size. To date little research has been conducted on the influence these parameters have on KDE hotspot mapping output, and none has been conducted on the influence these parameter settings have on a hotspot map’s central purpose – to identify where crime may occur in the future. We fill this gap with this research by conducting a number of experiments using different cell size and bandwidth values with crime data on residential burglary and violent assaults. We show that cell size has little influence on KDE crime hotspot maps for predicting spatial patterns of crime, but bandwidth size does have an influence. We conclude by discussing how the findings from this research can help inform police practitioners and researchers make better use of KDE for targeting policing and crime prevention initiatives.

Type: Article
Title: Examining the influence of cell size and bandwidth size on kernel density estimation crime hotspot maps for predicting spatial patterns of crime
Location: Belgium
Open access status: An open access version is available from UCL Discovery
Language: English
Keywords: Hotspot analysis, Kernel density estimation, Crime prediction, Cell size, Bandwidth, Burglary
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery.ucl.ac.uk/id/eprint/1388639
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