On the added value of sequential deep learning for the upscaling of evapotranspiration

<p>Estimating ecosystem–atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary methodology that is independent fro...

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Bibliographic Details
Main Authors: B. Kraft, J. A. Nelson, S. Walther, F. Gans, U. Weber, G. Duveiller, M. Reichstein, W. Zhang, M. Rußwurm, D. Tuia, M. Körner, Z. Hamdi, M. Jung
Format: Article
Language:English
Published: Copernicus Publications 2025-08-01
Series:Biogeosciences
Online Access:https://bg.copernicus.org/articles/22/3965/2025/bg-22-3965-2025.pdf
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