IEEE Transactions on Geoscience and Remote Sensing · 2020 · 37 citations · 52 references
Natural SciencesEarth SciencesSoil SciencesRemote SensingSoil PhysicsSoil ScienceLand Surface ModelingLand Surface MonitoringSatellite SensorsSoil MoistureThermal Remote SensingMicrowave Soil Moisture RetrievalPolar Orbiting Satellite DataRadiative Transfer ModelingSoil Moisture EstimationSoil Moisture MappingSoil Moisture ObservationSoil Moisture Remote SensingSoil Moisture Retrievals
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 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> ) 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 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> 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 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> 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 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ·m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> . 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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Soil moisture retrieval from AMSR-E
E. G. Njoku, Thomas J. Jackson, V. Lakshmi et al. · IEEE Transactions on Geoscience and Remote Sensing · 2003 · 1.6K citations
Mapping forest canopy height globally with spaceborne lidar
Marc Simard, N. Pinto, Joshua B. Fisher et al. · Journal of Geophysical Research Atmospheres · 2011 · 1.3K citations · Full text