A case study from Koyulhisar (Sivas-Turkey) for landslide susceptibility mapping by artificial neural networks

Abstract

A case study for the use of an artificial neural network (ANN) model for landslide susceptibility mapping in Koyulhisar (Sivas-Turkey) is presented. Digital elevation model (DEM) was first constructed using ArcGIS software. Relevant parameter maps were created, including geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index, stream power index, normalized difference vegetation index and distance from roads. Finally, a landslide susceptibility map was constructed using the neural networks. The drawbacks of the method are discussed but as the validation procedures used confirmed the quality of the map produced, it is recommended the use of ANN may be helpful for planners and engineers in the initial assessment of landslide susceptibility.