Authors
Yansong Bao, Libin Lin, Shanyu Wu, Khidir Abdalla Kwal Deng, George P Petropoulos
Publication date
2018/10/1
Journal
International journal of applied earth observation and geoinformation
Volume
72
Pages
76-85
Publisher
Elsevier
Description
In this study, is presented a new methodology for retrieving surface soil moisture (SSM) under conditions of partial vegetation cover based on the synergy between Sentinel-1 Synthetic Aperture Radar (SAR) and Landsat Operational Land Image (OLI) data. To remove the effect of vegetation on SSM retrieval, the Landsat OLI spectral index is applied to build a model for the vegetation water content estimation. The model is substituted into the original water-cloud model, and thus a modified water-cloud model with a spectral index is built. Additionally, an SSM estimation model is developed based on the modified water-cloud model. The technique was tested at two experimental sites in the UK and Spain on which reference data of SSM are acquired operationally by ground observational networks. In overall, the key findings of our study were: (1) For a vegetation-covered surface, the normalized difference water index …
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