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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...

Deskribapen osoa

Gorde:
Egile Nagusiak: 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
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: MDPI AG 2022-05-01
Saila:Remote Sensing
Gaiak:
fire
burned area
machine learning
Brazil
Landsat
fire regime
Sarrera elektronikoa:https://www.mdpi.com/2072-4292/14/11/2510
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