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The aim of the research was to monitor and assess landslide hazards by remote sensing data processing and GIS spatial analysis. The automatic classification of remote sensing images pro-vides many useful land use information to combine in a GIS environment with other spatial factors influencing the occurrence of landslide.
The upper part of Susa Valley, in the Italian Western Alps, was chosen as test area because of a large variety of remote sensing data available by ISPRS WG VIII/2 with the aim to exchange infor-mation and experience in the field of geomatic techniques.
It is well known that the occurrence of landslides is controlled by a lot of morphological, geological, and human factors. We have chosen, regarding the available data, the following factors: acclivity, aspect, lithology, land use and precipitations. We have built up a mathematical predictive model enabling ac-tual/potential unstable slopes. It is a linear model where the hazard score depends on instability factors and the coefficients are based on a statistical evaluation. The hazard score is classified into hazard rating to produce a landslide hazard assessment map in GIS environment. This model gives also indi-cations about the relevant factors influencing slope instability. This tool makes the GIS a Spatial Deci-sion Support System (SDSS) for land management.
Tasseti, N. et al. (2008): Use of Remote Sensing Data and GIS Technology for Assessment of Landslide Hazards in Susa Valley, Italy. EARSeL eProceedings 7, 59-67.