Retrieval of Surface Roughness Over Cropped Area using Modified Water Cloud Model (MWCM), Oh Model and SAR Data

Soil moisture is a critical factor for plant growth; therefore accurate information is needed for planning and protection measures. Surface roughness is an important factor that controls the near surface soil moisture in an agricultural field. The present aim of the work was to retrieve surface roughness using Sentinel-1A and Modified Water Cloud Model (MWCM) and Oh model. Inversion models were used to derive the surface parameters of crop with the aid of Sentinel-1A data. We have implemented the inversion algorithm of the MWCM and Oh model for vertical surface roughness estimation. Three Sentinel-1A images were collected and pre-processed before retrieval of backscattering coefficients (sigma o) of VV (or sigma o(VV)) and VH (or sigma o(VH)) polarizations using MWCM. In case of non-availability of sigma o(HH), Oh inversion algorithm was used as a calibration function to estimate surface roughness. The statistical accuracy of the results was found satisfactory (R-2 = 0.93).