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

Publication dates
Authors	Brimicombe, A.
Type	Conference 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’.
Keywords	residential burglary data; point event patterns; crime detection; clustering point event data
Year	2008
Conference	Proceedings of Advances in Computing and Technology
Publisher's version	Brimicombe, AJ (2008) AC&T 6.pdf License CC BY-ND
Print	2008
Publication process dates
Deposited	22 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 publication	University of East London
Page range	6-13

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