Locating the Establishment of Rescue and Rescue Centers in Nahavand City Using the FAHP Fuzzy-AHP Model

The hazard is an inevitable part of life [1]. Population growth and urbanization have made it necessary to reduce the negative effects of human and social damage on natural and human hazards. Geologically, the county of Nahavand has the coastline near the Gamasiab river basin, which turned Nahavand into a seismic zone [8]. Garon and Nahavand faults were accompanied by a massive earthquake movement, between 1997 and 1963. This county is the most densely populated area in Hamadan province [14]. In Nahavand, most villages are located in the Nahavand Plain due to good agricultural conditions and on the active fault zone of the region. This county has 170 hectares of Worn-out urban texture [18]. Considering above mentioned cases, the need to locate relief and rescue centers in order to maximize coverage of rescue operations in the minimum possible time, far from urban services, is highlighted. Increasing the number of service centers is not due to better service, but the optimal distribution of these centers has a significant impact on the type of operation [20]. However, the location of relief centers for crisis management is one of the few cases that have been dealt with in practice. This research has been carried out with the aim of planning and locating spaces to provide relief and rescue centers in Nahavand earthquake.

The county of Nahavand has an area of 1570 km2 in the province of Hamedan. The city is located between 48 ° 20 ' and 48 ° 25' longitude, and 34° 0' and 34 ° 5 ' latitude, between high mountains of Zagros and Alvand. In the present study, two clusters with twelve priority criteria were used to locate these centers. Flood plain, landslides, distances from faults, distance from landslide, drainage networks, soil and geology within the framework of environmental cluster criteria and demographic characteristics (urban centers, rural density, rural population), communication networks and land use as the most important human cluster criteria. These criteria are associated with a high population density that meaning more casualties and more damage during an earthquake [11]. Therefore, these centers should be closer to areas with high population density. After preparing the above criteria in the vectorized database, polygon, line, and point data were converted to raster maps in order to be capable to process. Then the spatial data domain was identified. Using spatial data inputs its matrix is formed to descriptive data based on the suitable and not-suitable of criteria and the fuzzy threshold of each layer. Before the fuzzy layers overlap with the final map, the weights of all layers were obtained to construct the weight matrix of the layers using the Solver AHP Fuzzy software. The weights were standardized by the Chang method and the fuzzy pair comparison matrix was determined. After multiplying the normalized weights in the layers, the layers were overlaying through the Fuzzy sum method. During the analyzation, based on functions and thresholds of fuzzy logic, the data output will map the zones of appropriate locations for the establishment of rescue and rescue centers in the Nahavand earthquake. Finally, the correlation matrix was used to validate the layers and the relationship between 12 criteria of this study by SUM layer.

At first, urban centers map, rural centers, communication networks, and village population, and maps of distances from faults, river, and floodplains rasterized according to the incompatibility of the greatest distances. Then, after evaluating the vector layers, geology, soil, land use, and in field, the coding of the layers was determined from 1 to 6 in terms of the coefficient of the significance of each layer. This means that 1 is very important and 6 is the most important. Before layers fuzzification, the fuzzy pair comparison table will be specified. For this purpose, weights of each layer were obtained. So, in the Fuzzy AHP solver software, all weights were defined for the construction of the matrix. The weight of each criterion was then standardized according to Fuzzy Chang, from normalized weights, because the total weights are 1. In the next step, the obtained weight for each criterion in the process of analyzing the AHP network is multiplied in its fuzzy layer and the final value of the areas is obtained .In order to select the appropriate method for maps overlay, the best method that presented the result was the Fuzzy sum operator. The output of the final map was made on five levels. The results showed that 12 percent of the city's area, equivalent to 186 square kilometers, is very suitable for natural and human areas. These centers were seen along the longitudinal plane. The correlation matrix was used for validation. The first layer is the SUM layer and its relationship to the other layer is identified. There is a relationship between all layers that can show the correctness of the model.

The fault map of Hamedan province shows that the concentration of active faults in Nahavand is more than other parts of Hamedan province. Therefore, the present study addresses the issue of locating suitable spaces for the establishment of relief and rescue centers during natural hazards. Then, by providing the criteria and indicators that were the result of scientific and targeted research, the location of these centers was carried out with the view that such environments should be safe and away from high-risk environments with maximum coverage. Locating relief and rescue centers using GIS, and AHP hierarchical evaluation of the combination and the Fuzzy model by overlapping the fuzzy layers based on the suitable and Not-suitable layers. The findings showed that near 12 percent of the area has potential to create these centers, which spread across the plain of Nahavand, and cover the entire plain. Such a specialty for crisis management in this area, which has a great potential for seismicity, can be of great importance, because, in the event of an earthquake, it is possible to quickly provide services to earthquakes.