This study explores machine learning for classifying X-band Synthetic Aperture Radar (SAR) monovariate time-series from four cryospheric zones in the Mont-Blanc massif. We aim to classify ablation zones, accumulation zones, hanging glaciers, and ice aprons using log-cumulants and Dynamic Time Warping Barycentric Averaging. Our approach evaluates distances between time series and estimated reference centroids, employing HH and HV polarimetric channels. We propose an extension to this method by aggregating class membership probabilities from selected polarimetric combinations. Results are compared across polarimetric, revealing insights into classification performance.