Evaluation of Smap Passive Soil Moisture Products Using In-Situ Data from a Dense Observation Network

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 cmvcnr 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.