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

Author

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

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.

Suggested Citation

  • Jones, Sara Sharon & Matsala, Maksym & Delin, Emily Viola & Subramanian, Narayanan & Nilsson, Urban & Holmström, Emma & Drobyshev, Igor, 2025. "Forest structure, roads and soil moisture provide realistic predictions of fire spread in modern Swedish landscape," Ecological Modelling, Elsevier, vol. 499(C).
    • Handle: RePEc:eee:ecomod:v:499:y:2025:i:c:s0304380024003302
    DOI: 10.1016/j.ecolmodel.2024.110942
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