A new model for an improved AMSR2 satellite soil moisture retrieval over agricultural areas

Abstract

This study evaluates the potential of AMSR2 (Advance Microwave Scanning Radiometer2) data for the estimation of Volumetric Soil Moisture (VSM) for bare and agricultural areas. At the first step, the sensitivity of the Microwave Polarization Difference Index (MPDI) to variations in soil and vegetation characteristics were examined at different frequencies. At lower frequencies, the signal attenuation due to vegetation is minimal and thus, denser vegetation usually depolarizes the soil emission. Interestingly, the results also reveal that at higher frequencies, the sensitivity of V and H polarizations over relatively dense vegetation covers is not the same at all. Therefore, MPDI at both low and high frequencies can be a good indicator of the soil moisture and Vegetation Water Content (VWC), respectively. After evaluation of AMSR2 datasets, a model called Multi-channel/MPDI-based Land Parameters Retrieval Model (MMLPRM) is proposed. The MMLPRM optimizes optical depth of vegetation and soil dielectric constant, with simultaneous retrieval of soil moisture and surface temperature by using the AMSR2 brightness temperature data. This algorithm also includes the surface roughness parameters to increase the soil moisture retrieval efficiency. In this way, calibration and validation have been done, using in situ observations of 50 monitoring stations obtained from the International Soil Moisture Network (ISMN) over the United States. Consequently, the analysis on the MMLPRM retrieval model demonstrates its potential and usefulness for soil moisture retrieval. The outcome of this study will help in estimating the accurate soil moisture to optimize the irrigation management strategies and help in water conservation. © 2021 Elsevier B.V.