Evaluation of SMAP Passive Soil Moisture Products using in-situ data from a dense observation network over Agricultural Area in Northeast China

摘要

Introduction: 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. 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. The microwave is the optimal mean to obtain soil moisture in large scale due to its strong penetration capability 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. 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. 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. 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.