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Landslide Susceptibility Estimation Using GIS. Evritania Prefecture: A Case Study in Greece

Landslide Susceptibility Estimation Using GIS. Evritania Prefecture: A Case Study in Greece

作     者:Georgios Ntelis Stavropoulou Maria Lekkas Efthymios 

作者机构:National and Kapodistrian University of Athens—Sector of Dynamic Tectonic & Applied Geology Athens Greece 

出 版 物:《Journal of Geoscience and Environment Protection》 (地球科学和环境保护期刊(英文))

年 卷 期:2019年第7卷第8期

页      面:206-220页

学科分类:1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主  题:Natural Hazards Landslide Susceptibility Frequency Ratio 

摘      要:Nowadays, natural hazards constitute an integral part in the everyday reality of people’s lives. A landslide event, although usually occurring at a low frequency (compared to other hazards), may develop into a major natural disaster involving extensive and adverse effects, both in the natural and man-made environment. Thus, by making this assumption and combining it with the human mentality that has the tendency to reassure and resist extreme physical processes, the underlying danger “in total, is multiple of what is expected. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic and geomorphologic characteristics of the region, the purpose of this study was the landslide hazard assessment by using Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method in the Evritania prefecture. At first, landslides occurring in Evritania prefecture, were identified using a landslide database from Institute of Geology & Mineral Exploration of Greece and by primary field studies. The influence landslide factors used in this study were slope, aspect, elevation, lithology, precipitation, land cover, distance from faults and distance from rivers, were obtained from different sources and maps. Using these factors and the identified landslides, the fuzzy membership values were calculated by frequency ratio. Then, to account for the importance of each of the parameters in the landslide susceptibility, weights of each factor were determined based on the Analytical Hierarchy Process method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method and at the end—for computing prediction accuracy—the produced map was verified by comparing to existing landslide locations. These results indicate that the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslid

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