Reconstruction of Global Long-Term Gap-Free Daily Surface Soil Moisture from 2002 to 2020 Based on a Pixel-Wise Machine Learning Method

Reconstruction of Global Long-Term Gap-Free Daily Surface Soil Moisture from 2002 to 2020 Based on a Pixel-Wise Machine Learning Method

Global, long-term, gap-free, high quality soil moisture products are extremely important for hydrological monitoring and climate change research. However, soil moisture products produced from satellite observations have data gaps due to the limited capabilities of satellite orbit/swath and retrieval...

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Bibliographic Details
Main Authors: Pei Mi, Chaolei Zheng, Li Jia, Yu Bai
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Remote Sensing
Subjects:
surface soil moisture
machine learning
data reconstruction
pixel-by-pixel model
long-term products
Online Access:https://www.mdpi.com/2072-4292/15/8/2116

Internet

https://www.mdpi.com/2072-4292/15/8/2116

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