Artificial Neural Network Model of Soil Heat Flux over Multiple Land Covers in South America

Artificial Neural Network Model of Soil Heat Flux over Multiple Land Covers in South America

Soil heat flux (G) is an important component for the closure of the surface energy balance (SEB) and the estimation of evapotranspiration (ET) by remote sensing algorithms. Over the last decades, efforts have been focused on parameterizing empirical models for G prediction, based on biophysical para...

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Bibliographic Details
Main Authors: Bruno César Comini de Andrade, Olavo Correa Pedrollo, Anderson Ruhoff, Adriana Aparecida Moreira, Leonardo Laipelt, Rafael Bloedow Kayser, Marcelo Sacardi Biudes, Carlos Antonio Costa dos Santos, Debora Regina Roberti, Nadja Gomes Machado, Higo Jose Dalmagro, Antonio Celso Dantas Antonino, José Romualdo de Sousa Lima, Eduardo Soares de Souza, Rodolfo Souza
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Remote Sensing
Subjects:
remote sensing
surface energy balance
deep learning
MODIS
GLDAS 2.1
flux towers
Online Access:https://www.mdpi.com/2072-4292/13/12/2337

Internet

https://www.mdpi.com/2072-4292/13/12/2337

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