Cluster detection inspatially repetitive events

Conference paper


Brimicombe, A. 2008. Cluster detection inspatially repetitive events. Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 3rd Annual Conference University of East London pp. 6-13
AuthorsBrimicombe, A.
TypeConference paper
Abstract

Analyses of point event patterns in geography, ecology and epidemiology have a
long tradition. Of particular interest are patterns of clustering or ‘hot spots’. Some point event
patterns exhibit a tendency towards spatial repetitiveness although with temporal separation.
Examples are burglary and traffic accidents. Spatial superimposition of point events
challenges many existing approaches to spatial cluster detection. In this paper a variable
resolution approach, Geo-ProZones, is applied to residential burglary data exhibiting a high
level of repeat victimisation. This is coupled with robust normalisation as a means of
consistently defining and visualising the ‘hot spots’.

Keywordsresidential burglary data; point event patterns; crime detection; clustering point event data
Year2008
ConferenceProceedings of Advances in Computing and Technology
Publisher's version
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CC BY-ND
Publication dates
Print2008
Publication process dates
Deposited22 Jul 2010
Web address (URL)http://www.uel.ac.uk/act/proceedings/documents/ACT08.pdf
http://hdl.handle.net/10552/890
Additional information

Citation:
Brimicombe, A.J. (2008) ‘Cluster detection inspatially repetitive events’ Proceedings of Advances in Computing and Technology, (AC&T) The School of Computing and Technology 3rd Annual Conference, University of East London, pp.6-13.

Place of publicationUniversity of East London
Page range6-13
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https://repository.uel.ac.uk/item/86585

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