Methodology for Estimating Landslides Susceptibility Using Artificial Neural Networks

Abstract

Abstract. In this study, the susceptibility to landslides at Sevilla township, Valle del Cauca, located at southwest of Colombia was evaluated. The conditioning factors that involve the generation of landslides were evaluated using Geographic Information Systems (GIS) and Remote Sensing (RS) techniques. For the estimating susceptibility, an Artificial Neural Network (ANN) was implemented by applying the “Backpropagation” method to extract the synoptic weights of the conditioning variables (slopes, flow length, curvature, geology, fracture density, and land cover) on an automatic way with a data training module. The data for the analysis of the conditioning factors were carried out through a Digital Elevation Model (DEM) obtained through Radar Interferometry techniques, with Sentinel-1B satellite images for the year 2018. The results showed that Sevilla’s township has areas with high susceptibility, high slopes, and that it’s crossed by an active geological fault which implies that the earth's dynamics will condition the terrain stability.

Landslide Susceptibility Mapping Using Machine Learning Algorithms Study Case Al Hoceima Region, Northern Morocco

“…After reviewing 12 scientific papers published between 2017 and 2021 in different journals (Ayalew and Yamagishi, 2005;Benchelha et al, 2019;Byou et al, 2020;Can et al, 2021;Karakas et al, 2020;Lee et al, 2017;Muñoz et al, 2020;Onagh et al, 2012;Sevgen et al, 2019;Tien Bui et al, 2012;Yordanov and Brovelli, 2020;Youssef and Pourghasemi, 2021), 10 conditioning factors were selected in terms of disponibility and their higher influence on Landslides occurrence can be grouped into 3 groups: geological factor (including lithology, distance-tofault), topographical factors (including elevation, slope, aspect, curvature, profile curvature, plan curvature), anthropogenic (including distance to roads) and land used (Normalized Difference Vegetation Index NDVI). The processing of landslide conditioning factors was done by a spatial analysis tool (ArcGIS software) with a common pixel size of 30 m and a common spatial reference (Merchich North Morocco) and the Mediterranean Sea was excluded from the calculation.…”