Estimating Soil Moisture over Winter Wheat Fields during Growing Season Using RADARSAT-2 Data

Soil moisture content (SMC) is a significant factor affecting crop growth and development. However, SMC estimation, based on synthetic aperture radar (SAR), influenced by variety of surface parameters, such as vegetation cover roughness. As result, determining the across agricultural areas (e.g., wheat fields) remotely (i.e., without ground measurement) difficult to achieve. In this study, model-based polarization decomposition method was used decompose original SAR signal into different scattering components that represented mechanisms. The volume models were applied, then results compared in order remove contribution from canopy, extract related soil moisture. Finally, combining extensively CIEM Dubois), roughness parameters optimization, lookup table developed estimate during period. When R2 RMSE are 0.534, 5.62 vol.%, for Dubois model, 0.634, 5.16 respectively, which indicates approach provides good estimation performance measuring growing season.