Global soil moisture retrievals from the Chinese FY-3D microwave radiation imager
IEEE Transactions on Geoscience and Remote Sensing, 2020•ieeexplore.ieee.org
The FengYun-3 (FY-3) series satellite is the second generation of Chinese polar-orbiting
meteorological satellite missions. The FY-3D satellite was launched on November 2017 and
has been providing valuable data for meteorological applications, including brightness
temperature (TB) data from the MicroWave Radiation Imager (MWRI). In this study, we
developed a global soil moisture retrieval algorithm, based on the radiative transfer equation
(RTE) for using the FY-3D MWRI TB to continue the soil moisture record from FY-3 satellites …
meteorological satellite missions. The FY-3D satellite was launched on November 2017 and
has been providing valuable data for meteorological applications, including brightness
temperature (TB) data from the MicroWave Radiation Imager (MWRI). In this study, we
developed a global soil moisture retrieval algorithm, based on the radiative transfer equation
(RTE) for using the FY-3D MWRI TB to continue the soil moisture record from FY-3 satellites …
The FengYun-3 (FY-3) series satellite is the second generation of Chinese polar-orbiting meteorological satellite missions. The FY-3D satellite was launched on November 2017 and has been providing valuable data for meteorological applications, including brightness temperature ( T B ) data from the MicroWave Radiation Imager (MWRI). In this study, we developed a global soil moisture retrieval algorithm, based on the radiative transfer equation (RTE) for using the FY-3D MWRI T B to continue the soil moisture record from FY-3 satellites. We adopted a new empirical model to compute vegetation water content (VWC) based on the leaf area index (LAI) and canopy height ( H) for vegetation effects correction. The Q p model, which addresses the soil surface roughness effects using dual-polarization information, is then used for soil moisture retrieval. Validation of the FY-3D soil moisture was conducted with the in-situ data and the validation results showed encouraging accuracy over a variety of landcovers, with bias and unbiased root-mean-squared difference (ubRMSE) at or below the level of 0.06 m 3 ·m -3 . Monthly averaged soil moisture products generated from FY-3D could represent the seasonal changes in soil moisture and show reasonable spatial distribution of soil moisture at a global scale.
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