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This work presents a multi-temporal and multi-source approach for glacier cover classification, i.e. bare soil, glacier ice, firn, and snow. The method is based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) and can handle different kinds of satellite virtual constellations composed of high-resolution optical and/or SAR platforms. The proposed method is tested on a Sentinel-1 time series...
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...
This paper presents a study on the retrieval of snowpack biophysical parameters in mountain areas from satellite remote sensing imagery. More in detail, the integration of new generation X-band Cosmo SkyMed SAR imagery and land surface temperature (LST) information derived from optical thermal remote sensing is investigated. First, a sensitivity analysis is carried out, in order to understand whether...
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