The influence of slope aspect on the distribution of landslides was studied in the Milia and Roglio basins in Tuscany, Italy. For each basin, the new Tuscany region landslide inventory that was initiated in 2010 was used. The landslides were split into separate datasets based on their prevailing movement typology. To assess the results that were obtained from the different slope aspect values, maps of the lithology, slope angle, distances to streams, and distances to tectonic lineaments were included in the bivariate statistical analysis as comparison terms. For each basin, all of the geo-environmental factor maps were compared with the different landslide typologies with GIS software. Pearson's Chi(2) (chi(2)) coefficient was used to test the degree of spatial association between each predictor variable and landslide type. In addition, Cramer's V test was used to quantify the strength of the degree of association. Next, a conditional analysis was applied to all of the possible combinations that occurred between the slope aspect and other landslide-predisposing factors. Overall, the slope aspect significantly affected the distribution of superficial landslide types, but apparently not that of other landslide types. (C) 2013 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.
The slope aspect: A predisposing factor for landsliding?
CAPITANI, MARCO;RIBOLINI, ADRIANO;BINI, MONICA
2013-01-01
Abstract
The influence of slope aspect on the distribution of landslides was studied in the Milia and Roglio basins in Tuscany, Italy. For each basin, the new Tuscany region landslide inventory that was initiated in 2010 was used. The landslides were split into separate datasets based on their prevailing movement typology. To assess the results that were obtained from the different slope aspect values, maps of the lithology, slope angle, distances to streams, and distances to tectonic lineaments were included in the bivariate statistical analysis as comparison terms. For each basin, all of the geo-environmental factor maps were compared with the different landslide typologies with GIS software. Pearson's Chi(2) (chi(2)) coefficient was used to test the degree of spatial association between each predictor variable and landslide type. In addition, Cramer's V test was used to quantify the strength of the degree of association. Next, a conditional analysis was applied to all of the possible combinations that occurred between the slope aspect and other landslide-predisposing factors. Overall, the slope aspect significantly affected the distribution of superficial landslide types, but apparently not that of other landslide types. (C) 2013 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
