On the parsimony, interpretability and predictive capability of a physically−based model in the optical domain for estimating soil moisture content

Author:

Zhang Zheyue,Chen Yiyun,Wu Kaixin,Hong Yongsheng,Shi Tiezhu,Mounem Mouazen Abdul

Publisher

Elsevier BV

Reference58 articles.

1. Soil moisture mapping with moisture-related indices, OPTRAM, and an integrated random forest-OPTRAM algorithm from landsat 8 images;Acharya;Remote Sens.,2022

2. Retrieving soil moisture in rainfed and irrigated fields using Sentinel-2 observations and a modified OPTRAM approach;Ambrosone;Int. J. Appl. Earth Obs. Geoinf.,2020

3. Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands;Anne;Int. J. Appl. Earth Obs. Geoinf.,2014

4. Ground, proximal, and satellite remote sensing of soil moisture;Babaeian;Rev. Geophys.,2019

5. MARMIT: a multilayer radiative transfer model of soil reflectance to estimate surface soil moisture content in the solar domain (400–2500 nm);Bablet;Remote Sens. Environ.,2018

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