G.I.S. technologies for data collection, management and visualization of large slope instabilities: two applications in the Western Italian Alps
- Dipartimento di Scienze della Terra, Università di Torino, Via Valperga Caluso 35, 10125 Torino, Italy
Abstract. Large slope instabilities are gravitational phenomena whose main characteristics are the multi-km2 area extension and the complex geometrical, geomorphological and geomechanical settings. Several studies outlined their importance in spatial and temporal occurrence of natural hazards on wide mountain areas and their possible interaction in human activities.
For the study of large slope instability and deep seated slope gravitational deformations in the Susa and Aosta Valleys (Western Italian Alps) a complete multiscale program (spatial and temporal) analysis has been performed, giving contributions to the reconstruction and settings of their possible evolution.
A complex geodatabase has been created, including thematic elements from field-data collection (geomorphology, hydrology, lithology, structural geology) and instability events analysis from data archives and remote sensing images. To facilitate the management of a large amount of collected data a G.I.S. (Geographical Information System) has been developed, including two main levels of information: local and regional.
Local information is mainly devoted to detailed geothematic mapping of single instability phenomena. Clot Brun case study is presented, where original and derived landslide features have been elaborated through arithmetical and statistical operations, in order to identify different instability zones and to assess displacements and state of activity through-time.
Regional information collected for a landslide inventory of Aosta Valley (IFFI project) summarizes historical and remote sensing data, combined with metadata from local analysis, in order to assess spatial and temporal hazards. To avoid problems of data accuracy (quality and positioning) due to different source archives, a semi-automatic system for selection and validation of data has been created, based on their spatial characteristics (buffer analysis and control).
G.I.S. technologies have been used to archive, manage and visualize collected data through 2-D and 3-D models of single case studies and regional distribution of large slope instabilities.