Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran
نویسندگان
چکیده
منابع مشابه
Landslide Susceptibility Mapping with Support Vector Machine Algorithm
This paper introduces one current machine learning approach for solving spatial modeling problems in domain of landslide susceptibility assessment. The case study addresses NW slopes of Fruška Gora Mountain in Serbia, where landslide activity has been quite substantial, but not inspected in detail. Regarding this lack of precise landslide inventory, an expert-driven zoning of landslide suscepti...
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The objective of this study is to investigate a potential application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Geographic Information System (GIS) as a relatively new approach for landslide susceptibility mapping in the Hoa Binh province of Vietnam. Firstly, a landslide inventory map with a total of 118 landslide locations was constructed from various sources. Then the lands...
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The efficiency of three statistical models, AHP surface-weighted density bivariate (semi-quantitative models), stepwise multivariate regression and logistic multivariate regression models were compared in Chehel-Chai watershed in Golestan province, Iran. In current study the hazard map was prepared according to the top model of landslide hazard map. Chehel-Chai watershed is located as one of Go...
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In this paper, bivariate statistical analysis modeling was applied and validated to derive a landslide susceptibility map of Peloponnese (Greece) at a regional scale. For this purpose, landslide-conditioning factors such as elevation, slope, aspect, lithology, land cover, mean annual precipitation (MAP) and peak ground acceleration (PGA), and a landslide inventory were analyzed within a GIS env...
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ژورنال
عنوان ژورنال: Journal of Earth System Science
سال: 2013
ISSN: 0253-4126,0973-774X
DOI: 10.1007/s12040-013-0282-2