Landslide susceptibility assessment at the Suichuan area (China) using support vector machine model

ABSTRACT: Landslide is a disastrous hazard around the world and landslide susceptibility is very important and useful in land use planning and government management. The aim of the present study was to apply Support Vector Machine (SVM) model with four kernel function named polynomial, RBF, sigmoid, and linear to verify the accuracy of each other. In conclusion, this paper provides a case study of landslide susceptibility assessment using SVM model that the polynomial function with high degree is the most suitable.