Spatial downscaling of SMAP radiometer soil moisture using radar data: Application of machine learning to the SMAPEx and SMAPVEX campaigns
This study developed a random forest approach for downscaling the coarse-resolution (36 km) soil moisture measured by The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) mission to 1 km spatial resolution, utilizing airborne remotely sensed data (radar backsc...
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| Главные авторы: | , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Elsevier
2024-06-01
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| Серии: | Science of Remote Sensing |
| Предметы: | |
| Online-ссылка: | http://www.sciencedirect.com/science/article/pii/S2666017224000063 |
| Метки: |
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