Estimation of Snow Surface Dielectric Constant From Polarimetric SAR Data.

A novel methodology is proposed in this paper for the estimation of snow surface dielectric constant from polarimetric SAR (PolSAR) data. The dominant scattering-type magnitude proposed by Touzi et al. is used to characterize scattering mechanism over the snowpack. Two methods have been used to obtain the optimized degree polarization of a partially polarized wave: 1) the Touzi optimum degree of polarization given by Touzi  et al. in 1992. The maximum (pmax) and the minimum (pmin) degree of polarizations are obtained along with the optimum transmitted polarizations (\chi t^{\rm{opt}},\psi t^{\rm{opt}}). 2) The adaptive generalized unitary transformation-based optimum degree of polarization mE^{\rm{opt}} proposed by Bhattacharya  et al. in 2015. This optimum degree of polarization is obtained either by a real or a complex unitary transformation of the 3 \times 3 coherency matrix. These two degrees of polarizations are used and compared in this study as a criterion to select the maximum number of pixels with surface dominant scattering. These pixels were then used to invert the snow surface dielectric constant. It has been observed that the mE^{\rm{opt}} have increased the number of pixels for inversion by \approx \text{9--10}\% compared to the original data. On the other hand, it was observed that the Touzi maximum degree of polarization pmax has increased the number of pixels for inversion by \approx 2\% compared to that of mE^{\rm{opt}}. The proposed methodology is applied to Radarsat-2 PolSAR C-band datasets over the Indian Himalayan region. It is observed that the correlation coefficient between the measured and the estimated snow surface dielectric constant is 0.95 at 95% confidence interval with a root mean square error of 0.20. [ABSTRACT FROM PUBLISHER]