Modeling and Theoretical Analysis of GNSS-R Soil Moisture Retrieval Based on the Random Forest and Support Vector Machine Learning Approach

Modeling and Theoretical Analysis of GNSS-R Soil Moisture Retrieval Based on the Random Forest and Support Vector Machine Learning Approach

Global Navigation Satellite System-Reflectometry (GNSS-R) as a microwave remote sensing technique can retrieve the Earth’s surface parameters using the GNSS reflected signal from the surface. These reflected signals convey the surface features and therefore can be utilized to detect certain physical...

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Bibliographic Details
Main Authors: Yan Jia, Shuanggen Jin, Patrizia Savi, Qingyun Yan, Wenmei Li
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Remote Sensing
Subjects:
Global Navigation Satellite System-Reflectometry (GNSS-R)
soil moisture retrieval
signal-to-noise ratio (SNR)
random forest (RF)
support vector machine (SVM)
Online Access:https://www.mdpi.com/2072-4292/12/22/3679

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https://www.mdpi.com/2072-4292/12/22/3679

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