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The present study investigated the potential of the proposed Salt Tolerance Vegetation Index (STVI) for Sentinel-1 data (5.35 GHz) in identifying salt-tolerant and stressed crops. The STVI was simulated by integrating the products i) imaginary part of the dielectric constant, ii) above-ground biomass, and iii) plant water content arrived from the SAR models, namely DSDM-SS (Density Space Dielectric Model for soil salinity), DPSVI (Dual Polarized SAR Vegetation Index), and WCM (Water Cloud Model), respectively. The STVI mapped the crops under the categories of stressed (0 − 0.5) and salt-tolerant (0.5 − 1). The results of the STVI was theoretically validated with the Vegetation Health Index (R 2  = 0.76, Bias = −0.007, RMSE = 0.118). Further, the STVI’s in-situ applicability was assessed using the accuracy assessment method with the ground truth observations. The results have shown substantial agreement with the field conditions (OA = 79%, AUC = 0.79).

Integrated SAR simulation to categorize the stressed and salt-tolerant crops using Sentinel-1 data