Combining RADARSAT-2 and COSMO-SkyMed data for alpine permafrost deformation monitoring

With this work, we present a method for the detection of alpine permafrost surface deformations by using DInSAR (Differential SAR Interferometry) technique, integrating RADARSAT-2 and COSMO-SkyMed data through Support Vector Machine (SVM). On our test dataset, the combination of the two sensors produces an increase of classification accuracy equal to 8.5% with respect to the case in which only one sensor is employed, leading to an overall accuracy equal to 86.9%. We are also showing here how COSMO-SkyMed data time series acquired in the snow-free period are well suited to estimate surface deformations on some particular alpine rock glaciers. The velocities estimated with the SBAS (Small BAseline Subset) algorithm are well correlated with velocity measurements obtained by means of a ground based total station, showing a root mean squared error (RMSE) and R square value equal to 3.5 cm and to 0.67 respectively.