Introducing State-of-the-Art Deep Learning Technique for Gap-Filling of Eddy Covariance Crop Evapotranspiration Data
Gaps often occur in eddy covariance flux measurements, leading to data loss and necessitating accurate gap-filling. Furthermore, gaps in evapotranspiration (ET) measurements of annual field crops are particularly challenging to fill because crops undergo rapid change over a short season. In this stu...
Main Authors: | Lior Fine, Antoine Richard, Josef Tanny, Cedric Pradalier, Rafael Rosa, Offer Rozenstein |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-02-01
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Series: | Water |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4441/14/5/763 |
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