2024 : 11 : 21
Saeed Khezri

Saeed Khezri

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId: 48161354800
HIndex:
Faculty: Faculty of Natural Resources
Address: Department of Physical geography, Faculty of Natural resources, University of Kurdistan, Sanandaj, IRAN
Phone: 00989126343252

Research

Title
Application of Satellite Images and Comparative Study of AnalyticalHierarchy Process and Frequency Ratio Methods to LandslideSusceptibility Mapping in Central Zab Basin, Nw Iran.
Type
JournalPaper
Keywords
Susceptibility mapping, Satellite Images, analytical hierarchy process (AHP), Frequency ratio model (FR), Zab basin
Year
2012
Journal International Journal of Advances in Engineering & Technology (IJAET)
DOI
Researchers Himan Shahabi ، Saeed Khezri ، Baharin Ben Ahmad ، Hamid Allawerdi Asl

Abstract

Preparation of landslide susceptibility mapping is one of the most important stages in landslide hazard mitigation. This study considers landslide susceptibility mapping in central Zab basin in west Azerbaijan province, Iran. Seven landslide inducing factors were used for landslide vulnerability analysis: slope, aspect, distance to road, distance to drainage, distance to road, land use and land cover, and geological factors. This study demonstrates the synergistic use of medium resolution, SPOT-5 Satellite, for prepare of landslide-inventory map and Landsat ETM+ for prepare of Land use. After preparation of the needed information layers by influential parameters on landslides, we drew the zoning maps of slide hazard using the following two methods analytical hierarchy process (AHP) and frequency ratio (FR) incorporating and evaluate their performance. The landslide susceptibility map was classified into four classes: low, moderate, high and very high. The models are validated using the relative landslide density index (R-index method) that results shows that more than 80 percent of landslides have happened in two classes, high hazard and very high hazard and showed that the frequency ratio model is better in prediction than the AHP model in study area.