Forest structure, roads and soil moisture provide realistic predictions of fire spread in modern Swedish landscape

Sara Sharon Jones, Maksym Matsala, Emily Viola Delin, Narayanan Subramanian, Urban Nilsson, Emma Holmström and Igor Drobyshev

Ecological Modelling, 2025, vol. 499, issue C

Abstract: Recent increases in fire activity in Sweden call for the quantification of forest fire susceptibility, in order to develop management strategies to mitigate fire risk. Using the data from 100 large Swedish forest fires (>10 ha), mapped from sentinel-2 images from 2016 to 2022, we explored the predictive power of vegetation properties in estimating relative likelihood of fires within a landscape using logistic regression. To model spatially explicit fire susceptibility within a given landscape, we used the outcome of logistic regression as an input into a cellular automata model (CA model), which simulates fire spread in a 2D grid.

Keywords: Environmental hazards; Fire regime; Natural disturbances; Fire behaviour; Fuel management; Fire modelling; Cellular automata model (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:499:y:2025:i:c:s0304380024003302

DOI: 10.1016/j.ecolmodel.2024.110942

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