Predicting the fundamental fluxes of an eddy-covariance station using machine learning methods
Monitoring tools are needed to maximise living systems' ability to mitigate emissions and adapt to changing environmental conditions. Therefore, it is important to be able to predict the fundamental fluxes in crops, in this case vineyards, such as sensible heat flux (H), latent heat flux (LE) and ca...
| Main Authors: | , , , , , |
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| Format: | article |
| Language: | Inglés |
| Published: |
Elsevier
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/20.500.11939/8965 https://www.sciencedirect.com/science/article/pii/S1574954124001808 |
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