New explanatory variables to improve landslide susceptibility mapping: testing the effectiveness of soil sealing information and multi-criteria geological parametrization
Keywords:Landslide susceptibility, random forest, geology, soil sealing
Landslide susceptibility maps (LSM) define the spatial probability of landslide occurrence based on the spatial distribution of predisposing factors. In this work, a LSM is produced for Norther Tuscany (3100 km2) with a Random Forest algorithm. The element of novelty is the use, besides 15 state-of-the-art parameters, of some newly proposed parameters. Starting from the national soil sealing map updated yearly by ISPRA, we derived a parameter accounting for the degree of human interference on hillslope systems. Soil sealing is the most intense form of land take, and it can be defined as the destruction (or covering) of soil by completely or partly impermeable artificial material. A multi-criteria approach was introduced to get a more complex and complete geological information into LSM. Usually, lithology is the only geological variable used, leaving the potential of geological maps largely unexploited. We used a 1:10,000 geological map to define a set of parameters based on lithological, genetic, structural, paleogeographic and chronological criteria, and found that the joint use of all the geology-derived parameters improved the susceptibility assessment. The outcomes of this study could be easily reproduced elsewhere in Italy, since the newly proposed parameters were generated from easily accessible datasets.
How to Cite
Copyright (c) 2021 Italian journal of engineering geology and environment
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.