Bakhtiar Feizizadeh

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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.(More)
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(More)
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—The main objective of this research was to establish a semiautomated object-based image analysis (OBIA) methodology for locating landslides. We have detected and delineated landslides within a study area in northwestern Iran using normalized difference vegetation index (NDVI), brightness, and textural features derived from satellite imagery (IRS-ID and(More)
Uncertainty is associated with GIS-Multi Criteria Decision Analysis (GIS-MCDA) when applied to disaster modeling. Technically speaking, GIS-MCDA model outcomes are prone to multiple types of uncertainty and error. In order to minimize the inherent uncertainty, within this research we introduced a novel approach of spatial explicit uncertainty and(More)
This research aims to employ a novel methodology for modelling uncertainty in the GIS environment. The spatially explicit sensitivity and uncertainty analysis was applied on Multicriteria Decision Analysis (MCDA) for an economic vulnerability assessment within the Salzach Basin. The main objective of this research is to demonstrate how a unified approach of(More)