The proposed experimental study is aimed at contributing to the landslide susceptibility evaluation using a multidisciplinary approach: geological, geomorphological and geo-engineering survey, together with multivariate statistical analysis and GIS technique. It is included in a wider research project, aimed at defining the landslide hazard in the area of the map no. 250 ‘‘Castelnuovo di Garfagnana’’ (1:50 000 scale). This study is based on the realization of a landslides inventory map and statistical data analysis using probabilistic methods. The methodology applied in ranking slope instability proceeded step by step. At first, geomorphologic investigation was performed in order to realize a landslide inventory map. A GIS database was created to collect the characteristics related to landslides geometry, type of movement and state of activity. Geo-engineering survey and characterization with in situ and laboratory tests allowed assessing Rock Mass Classification and geotechnical properties of soils (texture and consistency). The statistical approach for evaluating the landslide susceptibility is based on the assumption that the landslide probability for the currently landslides-free areas could be evaluated studying the conditions which led to past and present instability. A set of environmental factors, thought to be related to landslides, were analysed and their spatial distribution organized in different layers. Then, GIS-supported spatial analysis, conditional and multivariate analysis, allowed to calculate the connections between instability factors and landslide distribution. This step evolved towards two distinct statistical methods, both indirect and quantitative, leading to a classification of the land surface in some different susceptibility domains. Conditional analysis was applied to a particular type of terrain unit named Unique Condition Unit (UCU) that is a unique combination of the instability factors. The computer-aided evaluation of the landslide index within each UCU represents the probability of landslide occurrence, according to Bayes statistical concept. Multivariate analysis was applied to the same set of instability factors, but to a different type of terrain unit, the grid cell. The results showed a quantitative response, more reliable about the effectiveness of each instability factors, with the possibility of verifying their statistical significance.
Multidisciplinary investigations in evaluating landslide susceptibility. An example in the Serchio River valley (Italy)
PUCCINELLI, ALBERTO;D'AMATO AVANZI, GIACOMO ALFREDO;GIANNECCHINI, ROBERTO;RIBOLINI, ADRIANO;SALVATI, NICOLA;
2007-01-01
Abstract
The proposed experimental study is aimed at contributing to the landslide susceptibility evaluation using a multidisciplinary approach: geological, geomorphological and geo-engineering survey, together with multivariate statistical analysis and GIS technique. It is included in a wider research project, aimed at defining the landslide hazard in the area of the map no. 250 ‘‘Castelnuovo di Garfagnana’’ (1:50 000 scale). This study is based on the realization of a landslides inventory map and statistical data analysis using probabilistic methods. The methodology applied in ranking slope instability proceeded step by step. At first, geomorphologic investigation was performed in order to realize a landslide inventory map. A GIS database was created to collect the characteristics related to landslides geometry, type of movement and state of activity. Geo-engineering survey and characterization with in situ and laboratory tests allowed assessing Rock Mass Classification and geotechnical properties of soils (texture and consistency). The statistical approach for evaluating the landslide susceptibility is based on the assumption that the landslide probability for the currently landslides-free areas could be evaluated studying the conditions which led to past and present instability. A set of environmental factors, thought to be related to landslides, were analysed and their spatial distribution organized in different layers. Then, GIS-supported spatial analysis, conditional and multivariate analysis, allowed to calculate the connections between instability factors and landslide distribution. This step evolved towards two distinct statistical methods, both indirect and quantitative, leading to a classification of the land surface in some different susceptibility domains. Conditional analysis was applied to a particular type of terrain unit named Unique Condition Unit (UCU) that is a unique combination of the instability factors. The computer-aided evaluation of the landslide index within each UCU represents the probability of landslide occurrence, according to Bayes statistical concept. Multivariate analysis was applied to the same set of instability factors, but to a different type of terrain unit, the grid cell. The results showed a quantitative response, more reliable about the effectiveness of each instability factors, with the possibility of verifying their statistical significance.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
