Uncertainty Analysis of GIS-based Ordered Weighted Averaging Method for Landslide Susceptibility Mapping in Urmia Lake Basin, Iran

نویسندگان

  • Bakhtiar Feizizadeh
  • Thomas Blaschke
چکیده

GIS-based Multicriteria Decision Analysis (GIS-MCDA) provides a rich collection of techniques and procedures for landslide susceptibility mapping. In this study landslide susceptibility was evaluated by applying different analytical GIS techniques based on Ordered Weighted Averaging (OWA) criteria. The OWA-MCDA is complemented by a Monte Carlo Simulation (MCS) and a Dempster-Shafer Theory (DST). The authors first employ a twostage analysis for landslide hazards in the Urmia lake basin, North Iran. Two landslide susceptibility maps were produced based on GIS-OWA and GIS-MCS-OWA. In doing so, the results of both approaches are qualitatively evaluated using an existing detailed inventory of known landslides for the study area. Finally uncertainty maps are created while applying DST. The results show a strong support for the high susceptibility categories of the landslide susceptibility maps. The results also allude that the integration of MCS and GIS-MCDA can improve the accuracy of the OWA method significantly.

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GIS-based ordered weighted averaging and Dempster-Shafer methods for landslide susceptibility mapping in the Urmia Lake Basin, Iran

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تاریخ انتشار 2012