Optimization of Model Parameters for Sm Estimation using Sentinel-1 Data with Efficient Analysis of Wheat Growth Cycle

Soil moisture(SM) estimation in agricultural area using microwave data is still a challenging task; due to numerous sources of signal contributors present other than soil dielectric like vegetation, soil roughness, etc. For minimization of the effect of these sources, there is a requirement for fully polarized SAR data or multi-sensor data, i.e., optical and microwave. But the optical data is not easily available in cloudy season, and fully polarized SAR data is less available in comparison to dual-polarized data like Sentinel-1, which is available with a high revisit cycle. Therefore in this paper, an attempt is made to use Sentinel-1 data to estimate SM by minimizing the effect of other signal contributors. Also, for the minimization of SM error, a complete wheat crop cycle is considered, and by using constrained nonlinear multivariable optimization technique, optimum values of WCM parameters and soil roughness are estimated. Obtained results are compared with ground truth SM. Results show that the retrieved SM is very close to ground truth SM.