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Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran
2013
Proceedings of the Indian Academy of Sciences, Earth and Planetary Sciences
The main goal of this study is to produce landslide susceptibility map using GIS-based support vector machine (SVM) at Kalaleh Township area of the Golestan province, Iran. In this paper, six different types of kernel classifiers such as linear, polynomial degree of 2, polynomial degree of 3, polynomial degree of 4, radial basis function (RBF) and sigmoid were used for landslide susceptibility mapping. At the first stage of the study, landslide locations were identified by aerial photographs
doi:10.1007/s12040-013-0282-2
fatcat:7ynpc5ilc5ei7kxjv2q3tgficm