首页|A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

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  • NETL
  • NSTL
  • Elsevier
Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

GIS based MCDAFuzzy-AHPMembership functionsLandslide susceptibility mapsIzeh River basin

Bakhtiar Feizizadeh、Majid Shadman Roodposhti、Piotr Jankowski、Thomas Blaschke

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Department of Remote Sensing and GIS, University of Tabriz, Tabriz, Iran

Department of GIS and Cartography, University of Tehran, Tehran, Iran

Department of Geography, San Diego State University, San Diego, CA, United States,Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Poznan, Poland

Department of Geoinformatics-Z_GIS, University of Salzburg, Salzburg, Austria

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2014

10.1016/j.cageo.2014.08.001

Computers & geosciences

Computers & geosciences

SCI
ISSN：0098-3004
年,卷(期)：2014.73(Dec.)
  • 117
  • 68