Long-Term Landsat-Based Monthly Burned Area Dataset for the Brazilian Biomes Using Deep Learning

Long-Term Landsat-Based Monthly Burned Area Dataset for the Brazilian Biomes Using Deep Learning

Fire is a significant agent of landscape transformation on Earth, and a dynamic and ephemeral process that is challenging to map. Difficulties include the seasonality of native vegetation in areas affected by fire, the high levels of spectral heterogeneity due to the spatial and temporal variability...

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Bibliographic Details
Main Authors: Ane A. C. Alencar, Vera L. S. Arruda, Wallace Vieira da Silva, Dhemerson E. Conciani, Diego Pereira Costa, Natalia Crusco, Soltan Galano Duverger, Nilson Clementino Ferreira, Washington Franca-Rocha, Heinrich Hasenack, Luiz Felipe Morais Martenexen, Valderli J. Piontekowski, Noely Vicente Ribeiro, Eduardo Reis Rosa, Marcos Reis Rosa, Sarah Moura B. dos Santos, Julia Z. Shimbo, Eduardo Vélez-Martin
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Remote Sensing
Subjects:
fire
burned area
machine learning
Brazil
Landsat
fire regime
Online Access:https://www.mdpi.com/2072-4292/14/11/2510

Internet

https://www.mdpi.com/2072-4292/14/11/2510

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