A New Fusion Algorithm for Simultaneously Improving Spatio-Temporal Continuity and Quality of Remotely Sensed Soil Moisture Over the Tibetan Plateau

A New Fusion Algorithm for Simultaneously Improving Spatio-Temporal Continuity and Quality of Remotely Sensed Soil Moisture Over the Tibetan Plateau

Spatio-temporally continuous and high-quality soil moisture (SM) is very important for assessing changes in the water cycle and climate, especially over the Tibetan plateau (TP). Data fusion is an important method to improve the quality of SM product. However, limited observation overlaps between di...

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Bibliographic Details
Main Authors: Yaokui Cui, Chao Zeng, Xi Chen, Wenjie Fan, Haijiang Liu, Yuan Liu, Wentao Xiong, Cong Sun, Zengliang Luo
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Essential climate variables (ECV)
Fengyun (FY)
general regression neural network (GRNN)
quality
soil moisture (SM)
spatio-temporal continuity
Online Access:https://ieeexplore.ieee.org/document/9286493/

Internet

https://ieeexplore.ieee.org/document/9286493/

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