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Type: Journal Article
Author(s): Debora Voltolina; Giacomo Cappellini; Tiziana Apuani; Simone Sterlacchini
Publication Date: 2022

Our ability to predict wildland surface fire behaviour is of great significance for planning and optimising risk-mitigation and fire-suppression strategies. This applies especially for Euro-Mediterranean countries, where an intensified fire-related risk is expected in the decades to come due to both climatic and anthropogenic factors. In the midst of a broad variety of existing fire spread models, Rothermel’s quasi-empirical mathematical model is one of the most extensively employed, even though the impact of the drivers of fire spread on the model evaluation and uncertainty is not fully understood.

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Citation: Voltolina, Debora; Cappellini, Giacomo; Apuani, Tiziana; Sterlacchini, Simone. 2022. A machine learning model for predicting wildland surface fire spread according to Rothemel's equations. Environmental Sciences Proceedings 17(1):26.

Cataloging Information

Topics:
Fire Behavior    Fuels    Models
Regions:
Keywords:
  • feature importance
  • fire spread
  • Italy
  • rate of spread
  • Rothermel's fire behavior model
Record Last Modified:
Record Maintained By: FRAMES Staff (https://www.frames.gov/contact)
FRAMES Record Number: 66829