The disasters of recent years indicate that communities and individuals are getting increasingly vulnerable and risks are progressively growing. Nonetheless, the need to reduce risks and vulnerabilities are often ignored up until the occurrence of disasters. In the study at hand, which was done based on the descriptive-analytical method, it was tried to examine and predict the vulnerability perspective of the areas located within District six of Ahvaz metropolis during a potential earthquake based on the main purpose of this study. The theoretical data of the study was collected through library research method. After the extraction of the related indices, the spatial analysis of each index was carried out through fuzzy Delphi method, IHWP vulnerability model, and GIS software analyses. The analysis of the findings illustrated that considering the first and second priorities of the crises management, 15.03 percent of all areas of the district under study are highly vulnerable to earthquake. That is to say, in case of a strong earthquake in the district, they will be vulnerable. The study concluded that the physical qualities of the building are as important as the factors such as land use, population density, and time of earthquake occurrence. These have all effective roles in the vulnerability rate and the rescue activities.

The vulnerability appraisal is one of the prerequisites of risk analysis in disaster management. Vulnerability to earthquake, especially in urban areas, has increased over years due to the existence of complex urban structures and rapid development. In order to take preemptive measures and reduce the damages of earthquake, the determination of vulnerable areas and implementation of necessary measures seem inevitable. Accordingly, the present study set out to examine the vulnerability of Tehran urban blocks via a location-base model. To attain this objective, first the criteria effective on the evaluation of earthquake vulnerability were divided into three groups, namely exposure, sensitivity, and adaptation capability (16 location criteria in general). Using the expert opinions and network analysis model, the importance of each of the criteria was determined. Fuzzy functions and ordered weighted averaging method were used to normalize the criteria map and develop vulnerability maps under various scenarios. Finally, the sensitivity analysis of the criteria was carried out. The results showed that vulnerable population density and average slope were the criteria with the most and least importance, respectively. The vulnerability maps demonstrated that the areas to the north of the area under study are in the vulnerable class under all scenarios. The stability and dependability of the output results were assessed using sensitivity analysis. The results indicated that changing the weight of the criteria does not have a significant effect on the model outputs, a finding that clearly proves the stability of the model.