A Gis Spatial Analysis Model For Landslide Hazard Mapping Application In Alpine Area

This research describes an application of an existing method for evaluating landslide susceptibility in alpine contest that may be considered a useful support in better land-use planning and risk management. In order to perform the method and improve it creating landslide maps of probability, we investigated the several conditioning factors that in general affected these morphological processes. Firstly, a landslide inventory was prepared using both in-depth analysis of historical records and aero-photos (or orthophotos) investigation. Secondarily, a set of conditioning factors which may affect slope movement and failure (particularly lithology, geomorphology, land use, slope angle and aspect) was considered. Then, the method involved the application of GIS techniques, specifically, spatial Data Analysis application. The thematic maps of conditioning factors overlapping together with the support of the raster calculator allowed the susceptibility map creation. The method was applied to the Germanasca Valley, a small basin in the Italian Western Alps. This easy to use method allows one to individuate various classes of susceptibility and to identify slope, lithology and geomorphology, driven by old landslide events as the main conditioning factors. Furthermore, the individuation of area susceptible to landslides verification is strictly related to risk and, as a consequence, this method permits specific zone to be selected for detailed engineering geology studies in land-use planning.

[1]  Nicola Sciarra,et al.  Insights On The Application Of Some CurrentSPH Approaches For The Study Of Muddy DebrisFlow: Numerical And Experimental Comparison , 2014 .

[2]  L. Turconi,et al.  Historical datum as a basis for a new GIS application to support civil protection services in NW Italy , 2014, Comput. Geosci..

[3]  Nicola Sciarra,et al.  SPH modeling of fast muddy debris flow: numerical and experimental comparison of certain commonly utilized approaches , 2013 .

[4]  Antonio Pasculli,et al.  Sph numerical approach in modelling 2d muddy debris flow , 2011 .

[5]  F. Bulut,et al.  Landslide susceptibility mapping using GIS and digital photogrammetric techniques: a case study from Ardesen (NE-Turkey) , 2007 .

[6]  L. Highland,et al.  Landslide types and processes , 2004 .

[7]  L. Minatti,et al.  Dam break Smoothed Particle Hydrodynamic modeling based on Riemann solvers , 2010 .

[8]  R. Soeters,et al.  Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment , 2003 .

[9]  Giorgio Lollino,et al.  A GIS tool for historical instability processes data entry: An approach to hazard management in two Italian Alpine river basins , 2009, Comput. Geosci..

[10]  Nicola Sciarra,et al.  Geomorphological features of the Montebello sul Sangro large landslide (Abruzzo, Central Italy) , 2016 .

[11]  Paula L. Gori,et al.  National landslide hazards mitigation strategy : a framework for loss reduction , 2000 .

[12]  A. Clerici,et al.  A procedure for landslide susceptibility zonation by the conditional analysis method , 2002 .

[13]  L. Esposito,et al.  Particular features of the physical and mechanical characteristics of certain Phlegraean pyroclastic soils , 2013 .

[14]  E. E. Brabb Innovative approaches to landslide hazard and risk mapping , 1985 .