Natural Hazards

, Volume 65, Issue 3, pp 2105–2128 | Cite as

GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran

  • Bakhtiar FeizizadehEmail author
  • Thomas Blaschke
Original Paper


The GIS-multicriteria decision analysis (GIS-MCDA) technique is increasingly used for landslide hazard mapping and zonation. It enables the integration of different data layers with different levels of uncertainty. In this study, three different GIS-MCDA methods were applied to landslide susceptibility mapping for the Urmia lake basin in northwest Iran. Nine landslide causal factors were used, whereby parameters were extracted from an associated spatial database. These factors were evaluated, and then, the respective factor weight and class weight were assigned to each of the associated factors. The landslide susceptibility maps were produced based on weighted overly techniques including analytic hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA). An existing inventory of known landslides within the case study area was compared with the resulting susceptibility maps. Respectively, Dempster-Shafer Theory was used to carry out uncertainty analysis of GIS-MCDA results. Result of research indicated the AHP performed best in the landslide susceptibility mapping closely followed by the OWA method while the WLC method delivered significantly poorer results. The resulting figures are generally very high for this area, but it could be proved that the choice of method significantly influences the results.


Landslide susceptibility Multicriteria evaluation GIS-multicriteria decision analysis Uncertainty analysis Urmia lake basin Iran 



The authors would like to thank the reviewers for their helpful and constructive comments on earlier versions of the manuscript and the Department of Geoinformatics (Z_GIS) University of Salzburg for partial financial support. We also appreciate the help of Dr. Hasan Ahmadzadeh, University of Tabriz, for his help and in particular for providing rights for Fig. 2. This work was carried out as part of a PhD study funded by the Iranian Ministry of Science, Research and Technology and including a study period at the University of Salzburg.


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© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Department of Physical Geography, Centre for Remote Sensing and GISUniversity of TabrizTabrizIran
  2. 2.Department of Geoinformatics (Z_GIS)University of SalzburgSalzburgAustria

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