Abstract
As a result of vital role of soil moisture in governing water and energy cycles of land-atmosphere, the remote sensing of soil moisture has become a key component of the observation and research programs involving water and energy cycles on the earth's surface [1] - [2] . In addition, the accurate monitoring and prediction of soil moisture plays a crucial role in crop growth, flood and drought monitoring and prediction, research of hydrological and land surface process and global water cycle [3] - [5] . The microwave is the optimal mean to obtain soil moisture in large scale due to its strong penetration capability [6] and sensitivity to the change of surface soil moisture. And the L band microwave is considered to be the best band for monitoring soil moisture [7] - [10] . The Soil Moisture Active Passive (SMAP) satellite with an L-band (1.26 GHz) radar and an L-band radiometer (1.41 GHz) was launched on January 31, 2015 by the NASA [4] . The baseline science requirement for SMAP is to provide estimates of soil moisture in the top 5 cm of soil with an error of no greater than 0.04 cm 3 /cm 3 at 10 km spatial resolution and 3-day average intervals over the global land area [12] . The soil moisture baseline algorithm of SMAP is single-channel algorithm using horizontally polarized TB (SCA-H). In SCA-H, the emissivity model of bare land uses a semi-empirical Hp model and the value of H is determined by using empirical method for different land cover types; The vegetation model with zero-order radiative transfer model to describe the influence of vegetation on the surface emissivity; The dielectric constant model is one of the three models of Mironov model, Dobson model and Wang model.
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