A snow cover mapping technique is proposed in this letter by exploiting the ratio of the seasonal variation of copolarized (hh-vv) correlation coefficient and the total scattering power. This ratio provides a very efficient index for snow characterization. The difference image is obtained by temporal (winter–summer) ratioing of this index. The snow cover map is obtained by thresholding the difference image using the standard method of Otsu.
Conventional snow cover mapping algorithms using SAR data have seldom utilized target scattering information for land cover characterization. In this paper, an approach is proposed for snow cover mapping that utilizes the Touzi eigenvalue-eigenvector-based decomposition parameters. The seasonal variation of these parameters is used as an indicator of scattering mechanism dominance in the proposed algorithm.
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.