Machine Learning Model Reveals Land Use and Climate’s Role in Caatinga Wildfires: Present and Future Scenarios

Machine Learning Model Reveals Land Use and Climate’s Role in Caatinga Wildfires: Present and Future Scenarios

Wildfires significantly impact ecosystems, economies, and biodiversity, particularly in fire-prone regions like the Caatinga biome in Northeastern Brazil. This study integrates machine learning with climate and land use data to model current and future fire dynamics in the Caatinga. Using MaxEnt, fi...

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Bibliographic Details
Main Authors: Rodrigo N. Vasconcelos, Mariana M. M. de Santana, Diego P. Costa, Soltan G. Duverger, Jefferson Ferreira-Ferreira, Mariana Oliveira, Leonardo da Silva Barbosa, Carlos Leandro Cordeiro, Washington J. S. Franca Rocha
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Fire
Subjects:
semiarid
drylands
fire susceptibility
fire dynamics
Maxent
climate change
Online Access:https://www.mdpi.com/2571-6255/8/1/8
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