Evaluation and improvement of temporal robustness and transfer performance of surface soil moisture estimated by machine learning regression algorithms

Author:

Jiaxin Qian,Jie Yang,Weidong Sun,Lingli Zhao,Lei Shi,Chaoya Dang

Funder

Natural Science Foundation of Hubei Province

Wuhan University

National Aeronautics and Space Administration

National Natural Science Foundation of China

European Space Agency

Publisher

Elsevier BV

Reference103 articles.

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2. Surface soil moisture retrievals over partially vegetated areas from the synergy of Sentinel-1 and Landsat 8 data using a modified water-cloud model;Bao;Int. J. Appl. Earth Obs. Geoinf.,2018

3. Toward global soil moisture monitoring with Sentinel-1: Harnessing assets and overcoming obstacles;Bauer-Marschallinger;IEEE Trans. Geosci. Remote Sens.,2018

4. Dual-polarimetric descriptors from Sentinel-1 GRD SAR data for crop growth assessment;Bhogapurapu;ISPRS J. Photogramm. Remote Sens.,2021

5. Soil moisture retrieval over croplands using dual-pol L-band GRD SAR data;Bhogapurapu;Remote Sens. Environ.,2022

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A novel vegetation-water resistant soil moisture index for remotely assessing soil surface moisture content under the low-moderate wheat cover;Computers and Electronics in Agriculture;2024-09

2. Computational methods to retrieve soil moisture using remote sensing data: A review;2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP);2024-07-11

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