Daniele Giordan, Martina Cignetti, Davide Bertolo, 2017, The Use of Morpho-Structural Domains for the Characterization of Deep-Seated Gravitational Slope Deformations in Valle d’Aosta, IV World landslide forum, pp. 59–68, 29/5/2017,2/6/2017,
URL: http://www.cnr.it/prodotto/i/377678

Deep-seated Gravitational Slope Deformations (DsGSDs) are widespread phenomena in mountain regions. In the Valle d'Aosta alpine region of northern Italy, DsGSDs occupy 13.5% of the entire regional territory. A total of 280 phenomena have been inventoried in the IFFI (Italian Landslide Inventory) project. These large slope instabilities often affect urbanized areas and strategic infrastructure and may involve entire valley flanks. The presence of settlements on DsGSDs has led the regional Geological Survey to assess the possible effects of these phenomena on human activities. This study is aimed at implementing a methodology that is based on interpreting Synthetic Aperture Radar (SAR) data for recognizing the most active sectors of these phenomena. Starting from the available RADARSAT-1 dataset, we attempt to propose a methodology for the identification of the main morpho-structural domains that characterize these huge phenomena and the definition of different sectors that make up the DsGSDs, which are characterized by different levels of activity. This subdivision is important for linking the different kinematic domains within DsGSDs with the level of attention that should be given to them in the studies that support the request for authorization of new infrastructure. We apply this method to three case studies that represent significant phenomena involving urban areas within the Valle d'Aosta region. In particular, we analyze study areas containing the Cime Bianche DsGSD, the Valtourenenche DsGSD, and the Quart DsGSD. These phenomena have different levels of evolution that are controlled by the interaction of diverse factors, and involve buildings and other infrastructure. This setting has been useful for testing the development of the methodology, which takes advantage of remote-sensing investigations, together with the local geological, geomorphological and structural setting

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