Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Data

Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Data

Abstract Facing the escalating threat of global wildfires, numerous computer vision techniques using remote sensing data have been applied in this area. However, the selection of deep learning methods for wildfire prediction remains uncertain due to the lack of comparative analysis in a quantitative...

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Bibliographic Details
Main Authors: Yihang Zhou, Ruige Kong, Zhengsen Xu, Linlin Xu, Sibo Cheng
Format: Article
Language:English
Published: Wiley 2025-06-01
Series:Journal of Geophysical Research: Machine Learning and Computation
Subjects:
deep learning
wildfire
natural hazards
Online Access:https://doi.org/10.1029/2024JH000409
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https://doi.org/10.1029/2024JH000409

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