Estimation of Soil Moisture for Different Crops Using SAR Polarimetric Data

Soil moisture is an essential factor that influences agricultural productivity and hydrological processes. estimation using field detection methods takes time challenging. However, Remote Sensing (RS) Geographic Information System (GIS) technology, soil parameters become easier to detect. In microwave remote sensing, synthetic aperture radar (SAR) data helps retrieve from more considerable depths because of its high penetration capability the illumination power light source. This study aims process SAR Sentinel-1A estimate Water Cloud Model (WCM). Many physical empirical models have been developed determine sensing platforms. gives accurate results. this study, WCM model used for mixed crop types. The experimental was determined in-situ samples collected various areas. backscattering values corresponding different sampling locations were derived Sentinel data. Using linear regression analysis, laboratory's results correlated arrive at a model. validated secondary set content taken during same period. R2 RMSE observed be 0.825 0.0274, respectively, proving strong correlation between satellite-derived paper explains methodology arriving estimation. recommend suitable types in large, complex areas based on predicted content. Doi: 10.28991/CEJ-2023-09-06-08 Full Text: PDF