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Crimino-forensic applications to arson prevention: spatiotemporal factors
Journal article   Open access   Peer reviewed

Crimino-forensic applications to arson prevention: spatiotemporal factors

Tess Meyer, David Keatley, John Coumbaros and Brendan Chapman
Science & justice, Vol.66(2), 101400
2026
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Published2.66 MBDownloadView
Open Access CC BY V4.0

Abstract

Arson Crimino-forensic Fire-setting Hotspot Predictive policing Spatio-temporal analysis
Crime is known to distribute unevenly across space and time, leading to the formation of crime clusters. Similarly, incidences of arson have shown clustering, which allows for the investigation of hotspotting techniques for analysis. Geographical hotspot mapping typically only views arson through a single lens, but predictions may be improved by including criminological factors in analysis and through the integration of temporal analysis with spatial analysis. This study aimed to incorporate additional variables alongside traditional geographical hotspotting to investigate arson using Western Australian bushfire data from 2017 to 2023. The data were analysed temporally and spatially for discernible trends in fire-setting in the suspicious and deliberately lit subset. The geographical hotspots were measured against criminological factors that were hypothesised to facilitate (e.g. proximity to petrol service stations and main roads) or deter (e.g. proximity to police/fire stations and water bodies) arson. When analysing the temporal characteristics of the data increased number of bushfires occurred during warmer seasons and times of leisure such as weekends. Spatial clustering of fires was also demonstrated through 21 hotspots, all concentrated around urban and populated areas. When measuring these geographical hotspots against the criminological characteristics, a statistically significant difference was observed between arson facilitators and deterrents. This is the first study to combine criminological theory, spatio-temporal analysis, and geographic hotspotting techniques to establish fire patterns and clusters. This research paves the way for the development of a proximity prediction method which may identify areas targeted by fire-setters and allow for preventative policing in these locations.

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Citation topics
3 Agriculture, Environment & Ecology
3.40 Forestry
3.40.1598 Wildfire Dynamics
Web Of Science research areas
Medicine, Legal
Pathology
ESI research areas
Clinical Medicine
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