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.