A General Paradigm for Retrieving Soil Moisture and Surface Temperature from Passive Microwave Remote Sensing Data Based on Artificial Intelligence

A General Paradigm for Retrieving Soil Moisture and Surface Temperature from Passive Microwave Remote Sensing Data Based on Artificial Intelligence

Soil moisture (SM) and land surface temperature (LST) are entangled, and the retrieval of one of them requires a priori specification of the other one. Due to insufficient observational information, retrieval of LST and SM from passive microwave remote sensing data is often ill-posed, and the retrie...

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Bibliographic Details
Main Authors: Kebiao Mao, Han Wang, Jiancheng Shi, Essam Heggy, Shengli Wu, Sayed M. Bateni, Guoming Du
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Remote Sensing
Subjects:
deep learning
geophysical logical reasoning
interleaved iterative optimization
soil moisture
land surface temperature
collaborative retrieval
Online Access:https://www.mdpi.com/2072-4292/15/7/1793

Internet

https://www.mdpi.com/2072-4292/15/7/1793

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