EMERGENCY MANAGEMENT
Year:2015 | Volume:4 | Issue:7|Papers Count:7

Despite the traffic increases at the international airports, limited studies have been carried out to improve efficiency and accessibility of mechanics and servicemen to the plain and regarded facilities. GIS becomes a beneficiary tool for the airport managers to improve the process of managing of airports. This paper aims to apply GIS as an analyzing tool in the airport field. The main innovative contribution of this research is using offline spatiotemporal data analysis and introducing an efficient algorithm for service automobiles. The allocation optimization was carried out based on the reduction in departure time using deferment constraint. Allocation has been done by considering the aircraft push and tow required time and its distance for a service car. In this proposed solution service operation was optimized with considering two situations: returning the service car to its Equipment Parking Area or EPA when delivering service and the service car parks in Equipment Staging Area or ESA. The achieved numerical results in Mehrabad international airport indicate in both situations; departure delay is less than usual method. The outcomes of minimizing service cars are: traffic facilitation, increase management efficiency, decrease hazards due to the large number of service cars and increase safety in the airport field.

This paper is presented with the aim of finding optimum methodology to prioritize the seismic risk mitigation strategies in earthquake hazard prone areas and financing them, which could help decision makers in earthquake risk mitigation process. Therefore, a two-stage stochastic model is developed to optimize funds allocation for risk reduction measures (retrofitting of buildings) and reconstruction measures after potential earthquakes in a regional level. The proposed stochastic model seeks optimized strategy towards risk reduction based on minimizing various criteria such as mitigation expenditures, reconstruction costs, and excess reconstruction expenditures induced by probable earthquakes. This paper is presenting the methodology, main components of proposed model and practical application through a pilot study, taking into account, regional seismic hazard, building stocks and building vulnerability functions for Tehran. In order to investigate the consideration of uncertainty related to probable earthquakes in proposed model and illustrate the advantages and excellence capabilities of stochastic programming compared to other approaches, which consider the probability in the process of finding optimum earthquake risk mitigation measures and strategies, such approaches are discussed here and some pilot studies are designed and performed based on these approaches, as well. All model parameters related to these approaches are similar to the proposed stochastic programming model. The results of these pilot studies are compared with the pilot analyses done based on proposed stochastic programing. Furthermore, the key values: "the expected value of perfect information" and "the value of stochastic solution" which are used to demonstrate the advantages of considering stochastic programing are presented.

The climate change issue is dramatically risen by developing of urbanization. This matter of change resulted in more frequent flooding and inundation problems in the urban areas. The urban flood inundation modeling act as an efficient way to rapidly address these challenges by helping disaster managers. This paper introduces a new simulation model of urban storm-inundation. The proposed method uses commonly available input data to estimate the conditions of inundation quickly. The method is based on hydrologic models and geographic information systems. The effects of storm water infrastructures were also considered in inundation calculation. Terrain depressions are regarded as initial inundated area. The amount of surface runoff, the maximum storage volume, the flow direction and the water flow order between these depressions are all considered in the final inundation simulation. A part of region 22 of Tehran was chosen as study area. The results revealed that the proposed method could find inundation locations in the urban area. It can also calculate inundation depth and its volume while considering the effects of storm water infrastructures. A comparison of our proposed model with the USISM showed that the simulated amount of total volume and total depth in our methodology are reduced about 9.13 and 7.12 percent respectively. The lack of consideration of the effects of land-use type and stormwater infrastructures in USISM model is attributed to this difference. The proposed method can be used to create forcasting system for disaster management of flood inundation and helps managers reduce the effects of stormwater disasters.

This paper has focused on landslide hazard and risk zonation in the critical Ziarat watershed. Varnes equation and combination of Hazard map, elements at risk map and vulnerability map were used in the preparation of the risk map. Two quantitative models, including multivariate statistical (logistic regression) and LNRF model were used in the preparation of the hazard map. After applying the rate to the classes of parameters, Landslide hazard zonation was prepared for each of the models. The prior model was selected using four indices, including Quality summation (Qs), Precision of the predicted results (P), Receiver Operating Characteristic (ROC) and Chi-Square test and used in preparation of risk zonation. Results indicated that the logistic regression model shows a better performance for landslide hazard zonation and 13.63 and 9.04 percent of Ziarat watershed- including Ziarat village- were located in a high and very high zone of hazard and risk maps respectively.

In this paper, the site selection issues according to the warehouses and supply chain of crisis management, especially the inventory control of the unexpected demand was considered. Although, the extensive research on the site selection of warehouses was carried out previously, in the context of the theory and application, the chain of disaster relief was not considered precisely. The preliminary aim of this study is to identify the characteristic of the chain of the crisis relief. This model was progressed by inducement of the details of the crisis like damage level, relief process, necessities of injured people. Finally, the model was verified by analyzing and simulation of the real data in Iran, which achieved accurate results. It proves the contribution of this study to facilitate relief processing during natural events.

Fast relief and response is one of the responders 'tasks after the vigorous earthquakes in urban areas. Building damage maps can specify the relief and response priority. Remote sensing is one of the main sources in damage map production. Various research has been carried out on damage assessment using remote sensing data. In this research, the information about the classes has been extracted using pixel based classification from post-earthquake satellite image. By using the information about the classes and ANFIS model, a fuzzy system was designed that determines the rate of damage to the buildings using the percentage of the pixels engaged by building, shadow and debris in the building's polygon. The results of this study show that designed neuro-fuzzy system achieved the overall accuracy equal 0.92 in classifying buildings to the three damage level. Buildings were classified to undamaged, heavy damage and destroyed levels.

The purpose of this study is to assess earthquake risk analysis of Izeh urban catchment area located in the North East of Khuzestan province using the Multi-criteria models. The parameters used in this study include: the distance from the fault lines, seismic attributes such as magnitude of the earthquake, the geological structure and depth to the water table. In the first stage, five layers of the sesmic charachteristics were produced and classified by GIS 10 software. Then, the pairwise comparison method was employed, and the experts' opinions were weighted. The results of this study are two zoning map based on WLC and AHP methods. The results of the model indicate that the model based on the AHP and WLC, 10.92 and 16.58 Percents of the class area are at very high risk of earthquakes. By evaluating the models according to field observations; it is indicated that WLC model has better performance than AHP model for the seismic hazard zoning in the study area.