A Modified Triangle with SAR Target Parameters for Soil Texture Categorization Mapping

This research investigated soil texture information extraction in agricultural soil using SAR imagery of C band (5.36 GHz) frequency. The soil backscattering coefficient (\(\sigma_{soil}^{o}\)) could act as an effective estimator to the relative percentage of sand, silt, and clay when the influence of vegetation is considerably reduced from the total backscattering energy (\(\sigma_{total}^{o}\)). The contribution of vegetation in the SAR imageries of VV (\(\sigma_{vv}^{o}\)) and VH (\(\sigma_{vh}^{o}\)) polarization has been significantly reduced by Water Cloud Model, and Dual polarized SAR Vegetation Index. One of the target parameters, namely roughness (h_rms), was derived from the cross-polarization ratio between \(\sigma_{vh - soil}^{o}\), and \(\sigma_{vv - soil}^{o}\) and Dielectric Constant (\(\varepsilon_{soil}^{{\prime }}\)) was obtained from the modified Dubois model. The extracted target parameter such as h_rms is adequately correlated with in situ Sand texture measurements (R² = 0.81) and, \(\varepsilon_{soil}^{{\prime }}\) was sufficiently correlated with in situ Clay measurements (R² = 0.78). The positively correlated regions of the correlation coefficient (CC) analysis between h_rms and \(\varepsilon_{soil}^{{\prime }}\) were extracted and thus represented the percentage of silt with reasonable accuracy (R² = 0.77). From the soil triangle formed with three estimated parameters, we found that the Clay category shared around 36% of the total area followed by Sandy loam (24%) and loamy sand (19%).