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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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-08-01
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| Series: | Biogeosciences |
| Online Access: | https://bg.copernicus.org/articles/22/3965/2025/bg-22-3965-2025.pdf |
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