GIS-based landslide susceptibility mapping using hybrid MCDM models

Amin Salehpour Jam (), Jamal Mosaffaie, Faramarz Sarfaraz, Samad Shadfar and Rouhangiz Akhtari
Additional contact information
Amin Salehpour Jam: Soil Conservation and Watershed Management Research Institute (SCWMRI)
Jamal Mosaffaie: Soil Conservation and Watershed Management Research Institute (SCWMRI)
Faramarz Sarfaraz: Agricultural Research, Education and Extension Organization (AREEO)
Samad Shadfar: Soil Conservation and Watershed Management Research Institute (SCWMRI)
Rouhangiz Akhtari: Soil Conservation and Watershed Management Research Institute (SCWMRI)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 108, issue 1, No 44, 1025-1046

Abstract: Abstract Landslide susceptibility mapping plays an important role in integrated watershed management planning, especially in the field of land-use planning in landslide-prone areas. This study aims to evaluate the performance of widely used hybrid multi-criteria decision-making (MCDM) models including the integrated index method (IIM), AHP-TOPSIS, and AHP-VIKOR to produce landslide susceptibility maps (LSMs) in the Alamut watershed, Iran. Ten causal layers including slope angle, slope aspect, rainfall, lithology, altitude, land use, and the most common distance maps including distance to fault, distance to stream, and distance to road were used to produce LSMs. Meanwhile, the landslide distribution map was used to evaluate the accuracy of the produced LSMs. The weights of the causal factors were also calculated using the analytic hierarchy process (AHP) method based on the viewpoints of 14 experts. Finally, the quality sum (Qs) index as well as the receiver operating characteristic (ROC) curves were used to validate the performance of the MCDM models. The Qs values for AHP-TOPSIS, IIM, and AHP-VIKOR were calculated 0.355, 0.903, and 0.703, respectively. Therefore, IIM and AHP-VIKOR methods are more efficient than AHP-TOPSIS to create LSM. The area under the curve (AUC) values of the ROC curves for AHP-TOPSIS, IIM, and AHP-VIKOR were calculated 0.784, 0.853, and 0.844, respectively. Therefore, the accuracy of the MCDM models is acceptable for TOPSIS and excellent for IIM and AHP-VIKOR. In general, results of the performance assessment of MCDM models indicated the good performance of the models to produce LSMs, so that the IIM was introduced as the best model. Also, the performance of IIM and AHP-VIKOR are more than the AHP-TOPSIS model to produce LSMs. Overall, the application of the AHP method in combination with other MCDM models as a hybrid model to produce LSMs is recommended under the principles of group decision-making in AHP for land-use planning and landslide risk management.

Keywords: Causal factors; Consistency ratio; Group decision-making; Hybrid MCDM methods; Slope instability (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-021-04718-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:108:y:2021:i:1:d:10.1007_s11069-021-04718-5

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-021-04718-5

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().