Identifying factors of influence in the spatial distribution of domestic fires

Abstract

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.

Keywords:

• domestic fires
• point pattern analysis
• G-function
• non-stationary Strauss process

Acknowledgements

This paper originated from a visit of the first author to the ITC International Institute for Geoinformatic Science and Earth Observation. We are grateful to Prof. Kirsi Virrantaus and the ITC for facilitating this. We would also like to thank the Finnish Fire Rescue Services for Cooperation and supporting the research.