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Landslide Susceptibility Mapping Using Fuzzy-AHP

Landslide Susceptibility Mapping Using Fuzzy-AHP Landslides are as the movement of soil on slopes that they are one of the most common natural hazards in many mountainous areas. Landslides are recognized as an important natural hazard in many countries. So in the study, the geographic information system-based the fuzzy quantifier is used to determinate the landslide susceptibility modeling in the north of Khorramabad, west of Kermanshah Province, Iran. To determine the landslide susceptibility modeling generated aspect, some input data were prepared such as the digital elevation model, lithology, slope, land use, river, road, fault, and precipitation maps. Fuzzy map showed that almost all of the area was medium landslide susceptibility that had the value close to 1. Fuzzy-AHP model showed that 77.62% of the study area had medium landslide susceptibility and this method was a useful tool for forecasting of landslide susceptibility status in each case study. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Geotechnical and Geological Engineering Springer Journals

Landslide Susceptibility Mapping Using Fuzzy-AHP

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References (53)

Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer International Publishing AG, part of Springer Nature
Subject
Earth Sciences; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; Terrestrial Pollution; Waste Management/Waste Technology; Civil Engineering
ISSN
0960-3182
eISSN
1573-1529
DOI
10.1007/s10706-018-0583-y
Publisher site
See Article on Publisher Site

Abstract

Landslides are as the movement of soil on slopes that they are one of the most common natural hazards in many mountainous areas. Landslides are recognized as an important natural hazard in many countries. So in the study, the geographic information system-based the fuzzy quantifier is used to determinate the landslide susceptibility modeling in the north of Khorramabad, west of Kermanshah Province, Iran. To determine the landslide susceptibility modeling generated aspect, some input data were prepared such as the digital elevation model, lithology, slope, land use, river, road, fault, and precipitation maps. Fuzzy map showed that almost all of the area was medium landslide susceptibility that had the value close to 1. Fuzzy-AHP model showed that 77.62% of the study area had medium landslide susceptibility and this method was a useful tool for forecasting of landslide susceptibility status in each case study.

Journal

Geotechnical and Geological EngineeringSpringer Journals

Published: May 28, 2018

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