Evaluations of Machine Learning-Based CYGNSS Soil Moisture Estimates against SMAP Observations
This paper presents a machine learning (ML) framework to derive a quasi-global soil moisture (SM) product by direct use of the Cyclone Global Navigation Satellite System (CYGNSS)’s high spatio-temporal resolution observations over the tropics (within <inline-formula><math display="inline"><semantics...
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| Autors principals: | , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI AG
2020-10-01
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| Col·lecció: | Remote Sensing |
| Matèries: | |
| Accés en línia: | https://www.mdpi.com/2072-4292/12/21/3503 |
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