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dc.contributor.authorTompson, Lisaen_US
dc.contributor.authorTownsley, Michaelen_US
dc.date.accessioned2017-05-03T12:54:15Z
dc.date.available2017-05-03T12:54:15Z
dc.date.issued2010en_US
dc.date.modified2011-04-18T06:56:26Z
dc.identifier.issn14613557en_US
dc.identifier.doi10.1350/ijps.2010.12.1.148en_AU
dc.identifier.urihttp://hdl.handle.net/10072/36910
dc.description.abstractCrime analysts attempt to identify regularities in police recorded crime data with a central view of disrupting the patterns found. One common method for doing so is hotspot mapping, focusing attention on spatial clustering as a route to crime reduction (Chainey & Ratcliffe, 2005; Clarke & Eck, 2003). Despite the widespread use of this analytical technique, evaluation tools to assess its ability to accurately predict spatial patterns have only recently become available to practitioners (Chainey, Tompson, & Uhlig, 2008). Crucially, none has examined this issue from a spatio-temporal standpoint. Given that the organisational nature of policing agencies is shift based, it is common-sensical to understand crime problems at this temporal sensitivity, so there is an opportunity for resources to be deployed swiftly in a manner that optimises prevention and detection. This paper tests whether hotspot forecasts can be enhanced when time-of-day information is incorporated into the analysis. Using street crime data, and employing an evaluative tool called the Predictive Accuracy Index (PAI), we found that the predictive accuracy can be enhanced for particular temporal shifts, and this is primarily influenced by the degree of spatial clustering present. Interestingly, when hotspots shrank (in comparison with the all-day hotspots), they became more concentrated, and subsequently more predictable. This is meaningful in practice; for if crime is more predictable during specific timeframes, then response resources can be used intelligently to reduce victimisation.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent278204 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherVathek Publishingen_US
dc.publisher.placeUnited Kingdomen_US
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofpagefrom23en_US
dc.relation.ispartofpageto40en_US
dc.relation.ispartofissue1en_US
dc.relation.ispartofjournalInternational Journal of Police Science and Managementen_US
dc.relation.ispartofvolume12en_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchLaw and Legal Studies not elsewhere classifieden_US
dc.subject.fieldofresearchcode189999en_US
dc.title(Looking) Back to the Future: using space-time patterns to better predict the location of street crimeen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.rights.copyrightCopyright 2010 Vathek Publishing Ltd. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.en_AU
gro.date.issued2010
gro.hasfulltextFull Text


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