Using automated machine learning for the upscaling of gross primary productivity
<p>Estimating gross primary productivity (GPP) over space and time is fundamental for understanding the response of the terrestrial biosphere to climate change. Eddy covariance flux towers provide in situ estimates of GPP at the ecosystem scale, but their sparse geographical distribution limit...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2024-05-01
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| Series: | Biogeosciences |
| Online Access: | https://bg.copernicus.org/articles/21/2447/2024/bg-21-2447-2024.pdf |