Soil Moisture Retrievals by Combining Passive Microwave and Optical Data

Soil Moisture Retrievals by Combining Passive Microwave and Optical Data

This paper aims to retrieve the temporal dynamics of soil moisture from 2015 to 2019 over an agricultural site in Southeast Australia using the Soil Moisture Active Passive (SMAP) brightness temperature. To meet this objective, two machine learning approaches, Random Forest (RF), Support Vector Mach...

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Bibliographic Details
Main Authors: Cheng Tong, Hongquan Wang, Ramata Magagi, Kalifa Goïta, Luyao Zhu, Mengying Yang, Jinsong Deng
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Remote Sensing
Subjects:
soil moisture
SMAP
random forest
support vector machine
ordinary least square regression
Online Access:https://www.mdpi.com/2072-4292/12/19/3173

Internet

https://www.mdpi.com/2072-4292/12/19/3173

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