Domestic fires at the city level, being causes for casualties and causing significant material damages, are stored as a point pattern in a GIS. In this paper we apply a statistical point pattern analysis to derive major causes from related layers of information. We fit a G-function
to analyse neighbourhood relations and a Strauss process for inferring causal relations. Using open-source software we find significant differences in patterns and explaining factors between the different parts of the day, in particular for different building types and income groups. We conclude
that a quantitative spatial model can be fitted and that this provides a useful opportunity for fire brigades to improve planning their efforts.
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non-stationary Strauss process;
point pattern analysis
Document Type: Research Article
Department of Surveying, Faculty of Engineering and Architecture, Helsinki University of Technology, Espoo, Finland
ITC International Institute for GeoInformation Science and Earth Observation, Enschede, The Netherlands
Publication date: 2010-06-01
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