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Wildfire Risk Prediction: A Review
May 6, 2024, 4:41 a.m. | Zhengsen Xu, Jonathan Li, Linlin Xu
cs.LG updates on arXiv.org arxiv.org
Abstract: Wildfires have significant impacts on global vegetation, wildlife, and humans. They destroy plant communities and wildlife habitats and contribute to increased emissions of carbon dioxide, nitrogen oxides, methane, and other pollutants. The prediction of wildfires relies on various independent variables combined with regression or machine learning methods. In this technical review, we describe the options for independent variables, data processing techniques, models, independent variables collinearity and importance estimation methods, and model performance evaluation metrics. First, …
abstract arxiv carbon carbon dioxide communities cs.cv cs.lg emissions global humans impacts independent machine machine learning methane prediction regression review risk technical type variables wildfire wildfires wildlife
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