ABSTRACT
Climate change and glaciers are the most debatable topic in recent times. Glaciers are one of the most important resources available for human survival, in the form of ice and snow. The capacity evaluation of fully polarimetric L-band data for glacial facies identification is examined in this chapter. In the Indian Himalayan region, several characteristics are utilized to distinguish between dry snow, wet snow, ice, and debris moraine–covered areas, including backscattering coefficient σ0, eigenvalue–eigenvector, and Freeman–Durden three-component decomposition, and finally, the Stokes vector–based approach circular polarimetry ratio (CPR). To examine the physical characteristics of the targets, the H-A-α decomposition approach was employed to obtain scattering information. The entropy (H) and alpha angle (a) are calculated using the eigenvalues and eigenvectors obtained from the coherency matrix decomposition. Based on the results of decomposition models, the scattering mechanism for different glacier facies is analyzed, but it produces quite contrasting results.
