Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Spatial Prediction of Landslide using Hybrid Multi-Criteria Decision-Making Methods: A Case Study, Saqqez-Marivan Mountain Road

Himan Shahabi
* ORCID logo ,
Rahim Tavakolifar
,
Mohsen Alizadeh
,
Sayed M. Bateni
ORCID logo ,
Mazlan Hashim
* ORCID logo ,
Ataollah Shirzadi
ORCID logo ,
Effi Helmy Ariffin
ORCID logo ,
Isabelle D. Wolf
ORCID logo ,
Saman Shojae Chaeikar
Version 1 : Received: 12 March 2023 / Approved: 15 March 2023 / Online: 15 March 2023 (09:19:41 CET)

A peer-reviewed article of this Preprint also exists.

Tavakolifar, R.; Shahabi, H.; Alizadeh, M.; Bateni, S.M.; Hashim, M.; Shirzadi, A.; Ariffin, E.H.; Wolf, I.D.; Shojae Chaeikar, S. Spatial Prediction of Landslides Using Hybrid Multi-Criteria Decision-Making Methods: A Case Study of the Saqqez-Marivan Mountain Road in Iran. Land 2023, 12, 1151. Tavakolifar, R.; Shahabi, H.; Alizadeh, M.; Bateni, S.M.; Hashim, M.; Shirzadi, A.; Ariffin, E.H.; Wolf, I.D.; Shojae Chaeikar, S. Spatial Prediction of Landslides Using Hybrid Multi-Criteria Decision-Making Methods: A Case Study of the Saqqez-Marivan Mountain Road in Iran. Land 2023, 12, 1151.

Abstract

Landslides around the main roads in the mountains not only cause fatal events but also cause ecosystem damage, including land degradation. This study aims to map the susceptibility of the landslides around the Saqqez-Marivan main rod of Kurdistan province, Iran, using ensemble Fuzzy logic with Analytic Network Process (Fuzzy Logic-ANP; FLANP), and with TOPSIS (Fuzzy Logic-TOPSIS; FLTOPSIS). A total of 100 landslides were first recognized by field surveys and then they were randomly divided into a 70% dataset (70 locations) and a 30% dataset (30 locations), respectively, for training and validating the methods. Eleven landslide conditioning factors, including slope, aspect, elevation, lithology, land use, distance to fault, distance to a river, distance to road, soil type, curvature, and precipitation were used. The performance of the methods was checked by the areas under the receiver operating curve (AUCROC). Results concluded that the prediction accuracy based on validating datasets were, respectively, 0.882 and 0.918 for FLANP and FLTOPSIS methods. Our findings demonstrated that although both models were known as promising techniques, the FLTOPSIS method had a better capacity for predicting the susceptibility of landslides in the studied area. Therefore, the susceptibility map developed by the FLTOPSIS method can be used for the proper management of areas with high landslide potential and also for managers and planners during the implementation of land allocation and development projects, especially in mountainous areas.

Keywords

Landslides; inventory; susceptibility; fuzzy TOPSIS; ROC curve; Iran 

Subject

Environmental and Earth Sciences, Geography

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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