Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method

Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method

Abstract More frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. In this study, we proposed an interpretable and accurate hybrid...

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Bibliographic Details
Main Authors: Fa Li, Qing Zhu, Kunxiaojia Yuan, Fujiang Ji, Arindam Paul, Peng Lee, Volker C. Radeloff, Min Chen
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Earth's Future
Subjects:
Western US
wildfires
interpretable machine learning
explainable AI
climate change
compound effects
Online Access:https://doi.org/10.1029/2024EF004588
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https://doi.org/10.1029/2024EF004588

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