The contribution of polarimetric synthetic aperture radar (PolSAR) images compared with that of single-channel SAR images in terms of temporal scene characterization has been found and described to add valuable information in the literature. However, despite a number of recent studies focusing on single-polarized glacier monitoring, the potential of polarimetry to estimate the surface velocity of glaciers has not been explored due to the complex mechanism of polarization through glacier/snow. In this paper, a new approach to the problem of monitoring glacier surface velocity is proposed by means of temporal PolSAR images, using a basic concept from information theory, i.e., mutual information (MI). The proposed polarimetric tracking method applies the MI to measure the statistical dependence between temporal polarimetric images, which is assumed to be maximum if the images are geometrically aligned. Since the proposed polarimetric tracking method is very powerful and general, it can be implemented into any kind of multivariate remote sensing data such as multichannel optical and single-channel SAR images. The proposed polarimetric tracking is then used to retrieve the surface velocity of the Aletsch Glacier in Switzerland and the Inylchek Glacier in Kyrgyzstan with two different SAR sensors: the Experimental SAR airborne L-band (fully polarimetric) and Envisat C-band (single-polarized) systems, respectively. The effect of the number of channels (polarimetry) into tracking investigations demonstrated that the presence of snow, as expected, affects the location of the phase center in different polarization and frequency channels, as for the glacier tracking with temporal HH compared to temporal VV channels. In this paper, it is shown how it is possible to optimize these two different contributions, considering the multichannel SAR statistics.