نشریه جغرافیا و مخاطرات محیطی
پیاپی 32 (زمستان 1398)

Landslides are one of the most important geological hazards worldwide (Chen et al., 2018). Despite advances in science and technology, these events continue to result in economic, human, and environmental losses worldwide (Alimohammadlou, Najafi, & Yalcin, 2013). Globally, landslides cause about 1200 deaths and 3.5 billion dollars of loss each year (Zhang, Han, Han, Li, Zhang, & Wang, 2019). About 66 million people live in landslide-prone areas (Chen et al, 2018). Landslide susceptibility (LS) mapping is essential in delineating landslide prone areas in mountainous regions. Landslide susceptibility is the propensity of soil or rock to produce various types of landslides (Chalkias Ferentinou, & Polykretis, 2014). From the beginning of the 1970s, the interest of both geoscientists and engineering professionals in LS zonation and the increasing emphasis on the use of Geographic Information Systems (GIS) technology led to the development of many methods such as weights-of-evidence model (Karami, 2012; Wang, Guo, Li, He, & Wu, 2019) logistic regression (Pham, Pradhan, Bui, Prakash, & Dholakia, 2016; Raja, Çiçek, Türkoğlu, Aydin, & Kawasaki, 2017), artificial neural networks (Chauhan, Sharma, Arora, Gupta, 2010؛ Tsangaratos & Benardos, 2014), neuro-fuzzy (Aghdam, Varzandeh, & Pradhan, 2016; Lee, Hong, & Jung, 2017; Chen et al., 2019). Support vector machines model (SVM) is currently a new pattern recognition method based on statistical learning theory, which shows unique advantages in solving small sample, nonlinear and high dimensional pattern recognition problem (Yao, Tham, & Dai, 2008).Iran has vast mountainous areas that make up more than half of the country due to geological characteristics, seismicity, rainfall and climate change and topographic conditions are among the countries that have experienced numerous landslides. In the meantime, Aharchai basin is located in northwest of Iran. This basin is prone to landslide due to topographic and geological conditions, slopes and other factors. Such conditions reveal the necessity of zoning sensitivity and assessing the potential for landslides in planning and implementing development plans. In this study, SVM model and GIS technology are applied to the evaluation of the susceptibility of landslides for the Ahar-Chai Basin. In addition, the purpose of this study is to evaluate the performance of support vector machine algorithm functions.

Support Vector Machine (SVM) is currently a new pattern recognition method based on statistical learning theory, which shows unique advantages in solving small sample, nonlinear and high dimensional pattern recognition problems (Yao et al, 2008). SVM was first proposed by Vapnik (1995). Landslide inventory mapping is an important step in landslide susceptibility assessment. In this study, historical records, satellite images, field surveys, and Google Earth® were used to analyze landslide locations. Landslide conditioning factors used in the current study are slope angle, slope aspect, altitude, valley depth, NDVI, rainfall, distance to rivers, lithology, distance to faults, land use, topographic wetness index (TWI),  stream power index (SPI), plan curvature, and profile curvature. Using this DEM, slope degree, slope aspect, altitude, plan curvature, profile curvature, were produced. In this study, a Landsat/ETM+ satellite image and sentinell were used for the year 2017. The plan curvature map was produced using a system for automated geoscientific analyses (SAGA) GIS. In this research, a support vector machine with four types of kernel classifiers such as linear, polynomial, radial basis function (RBF) and sigmoid were used in GIS for landslide susceptibility mapping in the study area. A total of 200 landslides were mapped using satellite image and subsequently were verified through field checking. Validation is an essential part of landslide susceptibility and landslide susceptibility maps are meaningless without validation. At present, the area under curve (AUC) method is used by most scholars in the prediction capability of a landslide susceptibility model. The AUC displays the success rate and prediction rate percentage of the model and is obtained for both the training data and the validation data. In general, the larger the AUC value, the better is the model (Intarawichian & Dasananda 2011; Lee and Dan, 2005).

In this study, using the 70% of the landslides as training dataset, the success rate curve was drawn. Using the remaining 30% of the landsides as testing dataset, the prediction rate curve was also drawn. Susceptibility maps were verified and compared using the area under the curve (AUC) method. The success rate curve demonstrated that the AUC for the radial basis, sigmoid, polynomial and linear functions was 0.988, 0.938, 0.652 and 0.506, respectively, and the prediction rate curve showed that the AUC was 0.958, 0.928, 0.642 and 0.543, respectively. Furthermore, results showed that RBF function had the highest accuracy in comparison with other methods. Generally, the three methods showed reasonable accuracy in landslide susceptibility mapping. Results of this study can serve as guidelines to managers and policy makers regarding the prevention and mitigation of landslide hazards. Finally, the landslide susceptibility maps were reclassified into five susceptibility classes: very high, high, moderate, low and very low.

The validation results showed that success rates for four types of function models varied from 98% to 50%. Similarly, results of prediction rates showed that RBF (98%) and sigmoid (93%) functions performed better than other types of functions (polynomial = 65%, and linear = 50%). The result of zonation show that 26.61 % of study area were located in high and very high susceptibility classes.

One of the most important hazards that has always changed the natural environment is landslides. Landslides are catastrophic and widespread, causing significant damage in many parts of the world. Landslide is the movement of downward or integrated bulky loose weathered material and sediments which always quickly occurs across slopes. Landslides are very important natural hazards that exert high damages to human and economic property every year especially in mountainous area. According to this reason, in recent years, evaluation of landslide in terms of regional and small scale has been under attention of experts. Therefore, landslides are among the disasters that can be predicted and prevented. To study the risk of landslide, there are several ways in which zoning is one of the most important methods. Landslide hazard zoning is the mapping of areas with the same probability of occurrence at a given time. Identifying sensitive and endangered areas and preparing a landslide hazard zoning map is an important step in preventing and reducing landslide damage.Khalkhal County with an area of 2688 square kilometers is located in the south of Ardebil province. The study area in view of specifically regional situation such as topography (mountainous area), high slope, the existence of soft surface formation, non-resistant material above the resistant layers, and condition of dominate climatic has high potential for mass movement occurrence. It results in enormous and irreversible damage if no action is taken. Therefore, zonation of township area in view of sensibility to landslide is very necessary.

In this study, firstly, the factors affecting landslide occurrence (including slope, aspect, lithology, land use, soil, precipitation, distance from the road, distance from the river and distance from fault), according to the natural and human conditions of the area were identified. In the next stage, maps of effective factors in landslides of study area by Geographical Information System (GIS) were produced. Data set layers of access roads, stream network, elevation classes, slope and aspect were derived from digitizing topography map at 1:50000 scale. Layers related to fault and litology were derived from digitizing of 1:100000 Khalkhal geological map. In order to obtain the land use layer, land use map of Khalkhal township and satellite image were used. In so doing, soil map of area and soil of Ardabil Province were inserted. We exerted climatology station data and gradient equation to obtain precipitation map.Criteria weighing using the ANP method, which is a developed form of the AHP method is able to model the correlation and feedback between the elements in a decision making and to integrate all the internal effects of the components involved in the decision making process into computations. The final analysis and modeling was done by using Hot Spot Analysis as a method of spatial statistics as well as WLC method as one of the multi-criteria decision-making methods.

According to the results of the study, areas with a hot spot of 99%, mainly involved the slopes of 20 to 35% are investigated. It can also be said that the high-risk areas are located in areas with high rainfall (400-650 mm), and the landslides of the Khalkhal County are formed after heavy rainfall or after the melting of the snow in the spring.
Investigating the lithology factor also shows that non-nominal and semi-resistant formations, which are mostly Quaternary loose formations, have a high sensitivity to landslides. Hot spot spots are also found in soils with high clay, silt and marl, and on the northern and northwestern slopes. The survey of land use criteria also showed that the agriculture area has the highest percentage of the area of high risk areas. In addition, the high risk areas (hot spots), introduced by the research method, show that high risk areas are located relatively close to roads, rivers, and faults.Also, the results of the overlap of the study with the distribution of landslides, showed that 74.80 from the landslide distribution points in the Khalkhal county are in high risk classes (hot spots 99% to 90%) and 9.93% slip dispersion points are in low risk classes (cool spot is 99% to 90%). The lack of a meaningful model accounted for 15.27% of the slip dispersal points.

The study results showed that the slope, land use, precipitation, and lithology factors were 0.663, 0.646, 0.639, and 0/379, respectively, with the highest weight coefficient. Also, the results of this study indicate that 9.28, 14.33, 15.89% of the study area in the classes with 99%, 95% and 90% stain is analyzed. It can also be said that according to the results of the study, Khalkhal County has a high potential for landslide risk and management measures should be taken in it.According to the zoning map of the study, the study of high risk pixels resulting from the research method and its comparison with the distribution map of field surveys as well as climatic conditions, topography, geology, hydrology, and human governing the region can be the result of using the combination of Hot Spot, ANP, and WlC methods having a high degree of relative landslide study. It is expected that this study and the results of this research will pave the way for better and more knowledgeable management and planners in this field.

As cities are expanding as the best form of human habitation, and every day, more urban breakdowns occur in communities, increasing the resilience is a major concern for cities. The resilience in the context of crisis management can be seen as the birth of a new culture to respond to disasters. The city of Ilam has also been considered as a high risk city due to its location in the Zagros region. In today's changing world, natural disasters, based on socio-physical characteristics, have different implications for human societies. Of course, despite the tremendous advances in technology and the achievements it has been impossible for centuries, man is still helpless against unexpected natural disasters, such as earthquakes, floods, and so on(Agudelo and Claudia, 2012). And sometimes it leads to human and financial damage (Folke, 2010). Therefore, on the other hand, the vulnerability of different groups of people living in the squatters of the city varies depending on the level of their life and their social and economic status. Therefore, the resilience is not the only result of the risk of the regions, but also the result of physical, socioeconomic and political processes, and the accident is a final condition that results from these processes. Regarding the approaches and theories, people are not vulnerable to natural disasters because of the proximity to the place of occurrence of the risk factors, but their social and economic conditions also increase and decrease. The city of Ilam, like other major cities of the country has urban instability in its physical, economic, social and environmental dimensions. The objective consideration of these problems is mountainous region, borderline situation, strategic sensitive conditions and the possibility of vulnerability caused by it, although itself, due to crisis management considerations, necessitated the formation of some biotechnologies during the forties in Ilam (Mavedat, 2018).

The method of the present study is a combination of methods (descriptive, exploratory, survey and analytical). It should be noted that the research has a practical-developmental approach.The statistical population of the research is all urban areas of Ilam in the form of 14 urban districts. Data analysis was performed using HMR models and factor analysis using KMO and Bartlett's test as RAFA model. It should be noted that SmartPLS, Grafer, SPSS, ArcGIS, Visio, EXCEL have been used to output data.

The city of Ilam is located on 45 minutes and 47 degrees east longitude and 15 minutes and 34 degrees north latitude. According to the Bureau of Statistics and Information Office of Ilam Governorate, the population of his city was 213579 in 2014 distributed in the form of 52474 households. Among the 21,357 people in Ilam, 50.66 percent (10,800) are men and 49.33 percent are women (105,379). It should also be noted that the city of Ilam has four urban areas and 14 urban areas.The RAFA[1] model is adopted as a combination of two factor analysis models and a hierarchical weight regression model. The factor analysis, first proposed by Thorston in 1931, is a method used in two ways to reduce the number of variables and discover the structure of relationships between variables; and the hierarchical regression model is more often used in correlation research with the aim of predicting several dependent variables from one or more independent variables.Based on the correlation matrix:- The highest negative correlation among total variables of city Ilam volatility is the cultural factor with the rate of 517.0%.- The RAFA model is a combination of two models of factor analysis and hierarchical weight regression model.According to the calculations made regarding the resilience of Ilam city, the value of Bartlett's test was equal to (0.000) and the value of KMO test was equal to (0.203).Ilam city resilience Based on factor analysis method, only 4 factors have been able to play a key role in Ilam city resilience.Of these variable factors, the population of the areas of Ilam city alone is 5

The present study was carried out with a quantitative research approach in the city of Ilam. According to the results of the study, two factors of urban area and residential use had the most impact on Ilam’s vibrational calibration. The results of the study showed two factors area and residential land use. It had the greatest impact on the resilience rating of Ilam city. The most positive correlation in all variables is the factor of urban facilities and infrastructure with a rate of 0.8 percent. Also, Bartlett's test was equal to 0.000 and the KMO test was equal to 0.203, which indicates that the data were suitable for factor analysis in the areas and the subject of urban sustainability. And only four factors have been able to play a major role in alleviating the city of Ilam, and among these variables, the population of the districts of Ilam alone has a 51.5% role.

Natural disasters are fundamental obstacles to achieve the sustainable development of human societies. Since natural hazards have the potential to cause risky and devastating disasters in the absence of risk-decreasing systems for human societies and rural regions (Davis & Izadkhab, 2006), understanding problems of villages and presenting regional strategies for them is one of the basic measures for sustainable rural development. To decline the effects of such disasters, the resilience approach is introduced. The world resilience means return to the past which is from Latin root “Resili” that means jump to the past. For the first time, the term is used by Hauling in 1973 in a paper titled “Resilience and Sustainability of Ecological Systems” having an environmental point of view. Resilience is a multi-dimensional concept that include social, economic, institutional, and physical-peripheral dimensions (Klein, R. J, 2003). Resilience in the economic dimension is defined as people and societies reaction and compatibility in such a way that they are able to reduce the effects and consequences of actual damage caused by disasters and can be measured under the influence of various factors such as savings, level of damages, ability to return to working and living conditions, insurance, recovery of post-accident economic activities, financial services, access to facilities, diversification of economic activities, the existence of alternative ways of earning income, external resources, employment and income, ownership, and so on (Rafiian et al., 2010). Considering geographical situation and its location on the earthquake belt and climate variation, Iran has faced natural and unnatural hazards in various periods. Among them, earthquake as a natural hazard more or less has effects and consequences in different dimensions such as social, economic, environmental ones, especially in rural regions. In the current study, the considered area includes the village settlements of the village of Silakhor that has 20 villages and 1539 householders based on 2016 census. The occurrence of a 6-Richter earthquake on 31st March, 2006 had economically caused damage to the rural settlements of the region with different severity and weakness. Over 10 years, some parts of these villages were rebuilt which could somehow return to their previous condition but some others could not return to the previous conditions before the disaster and had to adapt themselves to the conditions that have been affected by their economic and social foundations. Given the importance of resilience, the purpose of the present study is to evaluate the factors affecting economic resilience of rural settlements after earthquake in Silakhor province. Regarding the difference in degree and the ability to return or the inability to return to pre-earthquake conditions, in other words, the resilience of settlements, the present research seeks to answer the following questions:What is the status of economic resilience of rural settlements in Silakhor rural district?
Which factors are contributed to the severity and weakness of the economic resilience of rural settlements in the village of Silakhor?

The present study is an applied one with a descriptive-analytical method. Methods and tools for collecting data in this study include both library and field methods. In this paper, the population include rural settlements in Silakhor (Dorood County) having 1539 households based on 2016 census. Depending on Cochran’s test, a sample of 308 households being affected by 2006 earthquake is selected. The indicators studied in this research include (economic capital and assets, employment, cost and income, damage, capacity and ability to compensate, ability to return to working conditions and appropriate income, and the use of banking resources). One-sample t-test was used in the villages of Silakhor rural districts to examine the resilience situation. Furthermore, exploratory factor analysis is also used to identify the factors that affect the resiliency.

A one sample t-test was used to assess the economic resilience. Findings show that in economic dimension, Kangane is the only village that is in good resilience condition while the villages of Azna, Alamabad, Upper Laban, Azizabad, and Jahan Abad are in low resilience in economic terms, and the rest of the villages are somewhat resilient. To answer the question, what factors did contribute to the severity and weakness of the resilience of rural settlements in the village of Silakhor, the exploratory factor analysis is used. The two effective identified factors in economic resilience were economic and employment context and the income and facility capacity. It can be inferred that the characteristics and indicators of employment, cost and income, economic capital, and damage in this field have a positive role. These features have formed the main factor in the context of economic resilience that called the factor of economic and employment fields with 2.741 factor load. In addition, the indicators such as capacity and ability to compensate for losses, use of banking resources and the ability to return to appropriate working conditions and income have significant role which can influence the resilience of residents in Silakhor Plain in which it is the former actor of income and facilities with 2.111 factor load.

Nowadays, the analysis and increase of resilience to natural disasters has become an important and widespread field. The purpose of this study is to assess the economic resilience of rural settlements in rural areas as well as to study the factors affecting this vibration. The results of the research show that only the village of Kanganeh has a good resilience condition and the villages of Azna, Alamabad, Upper Lebanon, Azizabad, and Jahan Abad have a low resilience in economic terms while the rest of the villages are somewhat resilient in this regard. In general, the studied rural settlements are somewhat resilient. The results of exploratory factor analysis represent that indicators of employment, cost and income, economic capital, and losses in this field have a positive and effective impact, and the main factors in the context of economic resilience are the economic and employment grounds. Moreover, indicators of capacity and ability to compensate, the use of banking resources, and the ability to return to working and income conditions have a significant role and effect on the resilience of residents, which is the factor of income and facility capacities. Generally, according to the results of this research, the above-mentioned factors have a significant role in the return of residents of rural areas to normal conditions, therefore, identifying these factors can be used to strengthen and increase the resilience of rural settlements in this area while it is also useful in other areas exposed to natural disaster. In this way, the damage caused by these disasters that is considered as one of the main obstacles to sustainable development in disaster-prone communities will be prevented.

Wind erosion is one of the important aspects of land degradation in arid and semi-arid areas. Countries in arid and semiarid belt of the world, including Iran, have always been associated with this phenomenon. In some studies, wind erosion index of IMDPA model is used to evaluate the wind erosion. Wind erosion assessment models use different scores to determine the erosion rate in a given class. However, due to the spatial and temporal complexities and the multiplicity of factors affecting the ecological conditions of the region, it is impossible to fully rely on the results and use them for targeting, prioritizing the areas and providing suitable solutions for management. But Bayesian Belief Networks (BBN) are based on probabilistic approaches which show the uncertainty in the evaluation of phenomena in terms of probability. These Networks are essentially developed as tools for analyzing decision-making strategies under uncertainty. Accordingly, the purpose of this study is to estimate the rate of wind erosion based on the IMDPA model, and to assess the potential of the BBN as a relatively new and probable means for estimating the wind erosion, and finally, to evaluate the management scenarios for controlling wind erosion in Dehloran plain in Ilam province.

The wind erosion criterion of IMDPA model was used in this study. Three indicators were used to weight the wind erosion criterion. The "percent vegetation cover" and" emergence of erosion facies" indicators were valued based on existing maps and field visits. Data were collected from Dehloran synoptic station for a period of 30 years in order to evaluate the DSI index which stands for the number of the days with dust storm. The final score of wind erosion in each area was obtained based on the geometric mean. The information layer for each wind erosion criteria was prepared based on the weights given in the GIS environment and the final map of the wind erosion criterion was prepared. In order to begin the process of modeling the networks of Bayesian beliefs with regard to the purpose of the study and by a review of the resources and assisting experts, suitable variables were selected for modeling the BBN. In the next step, the relationships between the variables should be determined using the impact graph. The impact diagram shows the relationships and effects of the variables on each other and on the output node of the model (the amount of wind erosion). Finally, in order to create a model and formulate the conditional probability tables of model variables, the impact diagram was transformed into a BBN model using the Netica software.

After evaluating and scoring indices to measure wind erosion and calculating the geometric mean of work units, the emergence of erosion facies index indicates the lowest, and the dust storm index shows the highest weight with the greatest impact on the severity of wind erosion in the area. Based on the weights given to each standard wind erosion indices at the work unit level, the facies of sediment source, abandoned lands and fine-grained ridge plains have the most roles in the wind erosion of the area. Using the final model of Bayesian’s belief network, the causal relationships between the variables affecting the rate of wind erosion were shown. The target variable in this model is wind erosion. Based on the results, geological variables, land management, topography of the area, soil texture, rainfall and frequency of wind speed at speeds of more than 6 m/s were considered as key variables of the model. In order to run the model, information about each of the key variables was taken from the area at the unit level and fed to the model. Finally, the model was designed to estimate the amount of wind erosion in each unit. Based on the output of the model, the probability of wind erosion in each unit was used to zone the probability of wind erosion in the study area. The overall sensitivity analysis of the model also indicates that the wind erosion rate of the area has the most sensitivity to the wind velocity and speed, the frequency of wind speeds of more than 6 m/s and the protection of the earth's surface. On the other hand, the least sensitivity is to variables like soil texture, geology and topography. A high correlation between the results of the two models was found. There was a suitable and significant correlation coefficient at the level of α = 0/05 between the high probabilities of the BBN and wind erosion criterion of the IMDPA model.

It was shown that the BBN presents the probability of different wind erosion rates for each unit in the study area. In the BBN, the uncertainty of the evaluation results is expressed in terms of probability and managers are to choose and implement timely and appropriate management decisions to reduce the risk of wind erosion in the region. The designed model in this study can be implemented in all regions. However, depending on the conditions of each region, the number of variables in the model can be increased or reduced. In the model of Bayesian belief network, the data presented in this study show that land management and vegetation density are factors that affect the amount of wind erosion and, with regard to the environmental constraints of the area, they can be partially rectified. But other factors such as land form and soil texture cannot be changed due to the size of the area and economical instability.

Wildfires cause substantial losses of property and human lives in ecosystems in Iran and all around the world. Every year, about 6000 ha of forests are affected by fires in Iran (Jahdi, Salis, Darvishsefat, Mostafavi, Alcasena, Etemad, Lozano, & Spano, 2015).These fires can occur naturally due to climate change or abnormally caused by human activities in the forests. In fact, fire is one of the most important factors in disrupting the structure and dynamics of forest in natural conditions that produces a large amount of dead wood caused by the destruction of trees (Coban & Mehmet, 2010). As a result, there are significant costs to prevent fire every year in countries it takes place, and managing ecosystems is a way to reduce the effects of fire on war and maintain perspectives. To manage fire in forests, understanding the behavior of the fire and the factors causing it in a prone environment and factors affecting its behavior are essential (Artes, Cencerrado, Cortes, & Margalef, 2013). One way to manage fire is FARSITE model. This model has become popular due to its steady structure and simplicity of popularity in the modeling of fire spreading. This model is considered as one of the main fire simulation systems used to describe the behavior and release of horrific fires and is a semi-experimental model (Shen, Prince, Gallacher, Fletcher, & Fletcher, 2017).

For the FARSITE Fire Extender simulator, we need 5 layers of GIS height, slope, direction, fuel type, and canopy. All of these spatial data describe the landscape of the area. Topographic data (elevation, slope and tilt direction) were extracted from 1: 25000 maps of the country's mapping organization, which were converted to ASCII (Kanga & Singh, 2017) format using ArcGIS10 to prepare for entering the FARSITE model. Meteorological data is another input similar to the FARSITE firewall, which includes the degree of heat, relative humidity, and wind speed. To obtain climatic data, synoptic stations in Ilam province were recorded at 3-hour intervals. The appropriate burning model of the research area was selected based on the description of 53 standard burning model developed on the basis of the fire extension model. This selection was made using vegetation maps, map coverage of the area and observations and field studies based on similarity of the existing vegetation characteristics and description of this model. In the last step, in order to simulate the GIS layers (slope, direction, height, combustion and canopy), the FARSITE model was entered in an appropriate format. Then, the area was classified according to the extent of the fire.

The results showed that fire in four areas where it occurred had different behaviors, which is also due to different natural conditions in these areas. Also, fire hazard zoning, in the province of Ilam shows that, 1.5% of the area has a high risk of fire. Therefore, it can be stated that the study of different factors (topography, vegetation, burning and climatic conditions) in the studied areas shows the complexity of fire behavior in these areas. It is under the control of various factors. To identify the behavior of the fire, all the parameters and influential factors must be considered together and in conjunction with each other.

Also, according to the results of FARSITE simulation and its accuracy evaluation in the region, using kappa coefficient, all points are in agreement with real values, which indicates the performance of the model in this region, and in none of the regions the coefficient value Kappa has not been negative. Therefore, the implementation of this model is a useful guide for forest fire management, and based on it, a fire prevention crisis management program can be implemented in the three phases of initial operations or pre-occurrence measures (prevention plan), action plans (coping plan), and post-operation operations (recovery plan).

One of the most important environmental challenges in recent years in Khorasan Razavi province is the dust storm phenomenon. A survey on the average number of annual dust storm days in the Khorasan Razavi province shows that it has risen from an average of 6 days to 21 days from 1951 to 2016. And since 1993, it has grown strongly, which shows that reviewing and forecasting the coming years is of high importance. For the purpose of the study Gstat, Space time, SP, Raster, Spdep, and R Google Maps packages of R software are used alongside with Kriging method of spatial-temporal changes to investigate the number of annual dusty days and to predict their occurrence in the coming years.

In this study, the wind speed of 15 meters per second and more and a horizontal view below 1000 meters were considered by the World Meteorological Organization as a dusty day. Then, the SP Data array (Pebesma, 2013) was constructed as a combination of the matrix and vector in STFDF and STF classes (Hengel et al., 2015) according to the following equation:Where the index i refers to the location number (position of view) and the j index to the time number. After that, the empirical Spatial –Temporal variogram were calculated using the Kriging method (Mohammadzadeh, 2012) and were calculated from the following equation:where in:    Represents the set of all couples of observations whose distance is in the neighborhood of the vector  and its time interval near   . Then all the separable and non-separable models were fitted to experimental data model, where the metric variogram with the least average square error was selected as the best model for predicting the number of dust storm days in the year.

The output of the model showed that data up to 5 years have a spatial-temporal dependence, and it is possible to estimate the number of dust storm days until 2022. Therefore, the most important spatial points are the annual number of dust storm days from higher values. They include: Northeast, Northwest and South East of Razavi Khorasan province. The predicted values of annual dust storm days in the central areas of Khorasan Razavi province in 2018 and 2019 shows that these areas will have the smallest number of dust storm days, but will gradually face with an increase in the number of dust storm days.Accordingly, in 2022 most points except the limited points in the east, west and south east will have a significant increase in the number of dust storm days in the central areas.  The results show in 2019, Ghochan, Mashhad, Sarakhs, Sabzevar, Khaf, Torbat Jam and Fariman stations, with a maximum reliability of 95%, will have 40.48.41.46,56,47.41,41 dusty days, respectively. The highest number of dust storm days is related to Sabzevar station with 56 days, and after that Sarakhs with 47 days. Spatial-temporal forecasting trend of the number of dusty days in 2022 indicates that Gonabad Station has the best air quality index of 7 days. Furthermore, the maximum probability of occurrence of dusty days in Ghouchan, Mashhad, Sarakhs, Sabzevar, Khaf, Torbat Jam, and Fariman stations reaches up to 51, 46, 49, 61, 51, 44, and 45 days respectively, and will increase from 39 days to 43 days throughout the province in 2022.

According to the increasing number of dusty days in Khorasan Razavi province, investigating the prediction models is very important. Spatial-temporal Kriging method can use the intrinsic stability of the data to predict the number of dusty days in three dimensions of x, y, and t. This means that we can predict the number of dusty days in different places and times. Indeed, the intrinsic structure of the data plays a significant role in this regard. If the data algorithm is annual, monthly or daily, the output of the model will be proportional to the algorithm. Annual algorithm was able to deliver acceptable results in this research.

Dust aerosols, a type of air pollution, are emitted from the arid and semi-arid areas. The Middle East constitutes the second largest desert in the world after North Africa deserts. More than 65% of the Middle East land surface has the potential for dust emission (Prospero et al. 2002). Dust storms frequently occur throughout the desert regions of the world. This event enhanced large amounts of dust into the atmosphere. Atmospheric dust plays an important role in the regional climate and environment which can affect the air quality and human health. They can scatter and absorb the solar radiation and thermal radiation at the Earth's surface and top of the atmosphere. Dust storm events may occur as a result of local meteorological events with convective systems in local scale, or synoptic-scale systems. Dust storms are not only occurred in the source region but also can be transported very far from this region. Dust aerosols are removed from the atmosphere by dry and wet deposition. The main dust sources for the west of Iran are Iraq, Syria, and Arabian Peninsula deserts. The Zagros Mountain Rang is always exposed to a dust storm by being in the vicinity of the dry and semi-arid areas of the country of Iraq, Syria, and Saudi Arabia. The modeling of dust storms is important for distinguishing its sources, prediction of dust event, simulating of formation, diffusion, transportation, and deposition of dust. The regional WRF-Chem model is used for simulation of temporal and spatial dust concentrations. Numerous dust models exist and have been applied for simulation air pollution. The WRF/Chem system is available online with the chemistry part and meteorology part running simultaneously. The chemical part and meteorological part use the same horizontal and vertical grids, time intervals, parameterizations for cloud-resolving microphysics, and sub-grid convections. The understanding of the atmospheric controls and mountain impact on dust emissions in Zagros Mountain Range is still uncertain. The focus of this work is to investigate the effect of the Zagros mountain range in dust concentration using the fully coupled chemistry within WRF (Weather Research and Forecasting), and WRF-Chem model.

To analyze the effect of the Zagros mountain on dust storms in the west of Iran, two dust storm events which occurred between 12 and 14 April 2011 and between 16 and 18 June 2016 were selected to be investigated along with studying the horizontal visibility in several synoptic stations across the Zagros Mountains in the west of Iran and its adjacent areas. The Weather Research and Forecasting model coupled with the Chemistry module (WRF-Chem model) is implemented over the Zagros mountain range. In this study, we used the WRF-Chem model Version 3.6.1 (Grell et al., 2005) to the dust simulations. To validate the model, we compared the observations of horizontal visibility and WRF-Chem simulations over Ilam and Kermanshah synoptic stations. Meteorological observations were obtained from the country's meteorological organization. WRF/Chem model was run in three states including the natural topography, the reduced topographic height of Zagros Mountains to 1000 meters, and the removed topographic height. WRF-Chem model is configured to cover the Zagros mountain range, the Syrian desert, and the Iraq Desert with 250x160 grid points, a 7 km grid resolution, and 32 vertical levels to 50 hPa. Boundary and initial conditions are assimilated with GFS data.

The WRF/Chem model simulates two dust storm events in the west of Iran that occurred in April 2011 and June 2016. Simulations of dust transport tracks and satellite data highlight two main transport paths of the dust storm. In April 2011, dust storm originated from northern Saudi Arabia and southeastern Iraq, and most likely in Khuzestan province, while in June 2016, the dust originated from Iraq. These events were caused by the passage of air masses associated with low-pressure systems in deserts of the western part of the Zagros mountain range. At first, the potential of the WRF-Chem model was investigated to quantify the ability of this model to simulate dust sources and dust concentration. Although the times with low values of dust are less accurate, the comparisons between the model simulations and the horizontal observation at the two synoptic sites and the satellite measurements show that the WRF-Chem model satisfactorily resolves evolution and spatial distributions of the dust stor The three states in the WRF/Chem model simulated comprised of the natural state, the reduced topographic height to 1000 meters, and the removed topographic height. On 13 April 2011, dust was accumulated on the winding slopes of the mountain range, but the simulations for the removed topographic height show that the intensity of the dust is reduced, and it is transferred to the center and north of the country. On 17 June 2016, the dust distribution profile shows that in places where the height of the dust column is equal to or less than the height of the mountain, the dust is stopped and accumulated on the winding slopes. In cases where the height of the dust column was higher than the height of the mountain, the dust will transfer from the mountain. The dust concentration on the winding slopes is maximum.  Model simulation results in the three states with different height topography indicating that the decrease in the topographic height lifts the dust towards the east of the mountain. The concentration of dust in the west of this mountain range is propagating more toward the east. In April 2011, the spatial distribution of the simulated dust concentration showed that the mountain barrier could not wholly prevent the passage of the dust. But in the case of the second storm in June 2016, which had less dust intensity, the mountain completely stopped the transfer of the dust. However, in both cases, the maximum dust concentration was on the western slopes, which had a long shelf life in these areas.

The purpose of this research was to examine how to treat dust storms in the confrontation with the Zagros Mountain and to determine the effect of this mountain to dust in the west of Iran. In this study, the behavior of the two dust storms over the Zagros Mountains range is investigated. Simulations of the dust event with the (WRF-Chem) were verified using horizontal visibility from the country's meteorological organization. To ensure the model simulations, the dust concentration simulated by models with horizontal visibility data received from the country's meteorological organization for two synoptic stations was compared. In general, despite some errors in some hours, the results of the simulation dust conformed to the horizontal visibility. The results of the three states of simulation in the WRF/Chem model indicate that the Zagros Mountain is prevented from the progress of the dust to central regions of the country. In the natural state, the accumulation of dust in the western Zagros Mountain range is increased. The removed topographic height causes moving the dust towards the east of the mountain and the concentrations of the dust in the west of the mountain range are reduced. According to the results of this study, wind-blown mountain-mountainous areas (western slopes) experience dust storms with higher intensity and durability.

Villages in Sistan region are facing natural disasters due to drought and 120-day storms that have had devastating effects on their social, economic, environmental, and hydrological conditions. The occurrence of droughts and strong winds of 120 days in Sistan due to heavy dust in Hamoon area has severely affected the lives of villagers, especially farmers and ranchers. On the other hand, humanitarian hazards such as ethnic conflicts and insecurity conflicts in border areas, fires in rural crops, delinquency, and social harm in rural communities can also lead to crisis. In the event of a crisis and failure to deliver an action on time, the severity of the damage will reach a maximum level, and the vulnerability resulting from these crises will go beyond the normal range and cause death or loss of life and damage to rural residents. Therefore, designing the network of specific villages to reduce the damage caused by natural and human crises seems necessary. Certain villages can function like central villages. In this regard, the central villages are characterized by population, access to health services, access to roads, infrastructure (plumbing, electricity and telephone), construction facilities, communication and transportation facilities, and land slope. In time of crisis, priority is given to helping other neighboring villages. Therefore, certain villages can provide timely and reliable services in order to timely resolve the rural crises and reduce the resulting vulnerability. Therefore, the purpose of this study is the spatial analysis of specific villages in disaster relief in neighboring rural areas (case study of Hamoon County). In this regard, the following question arises:What is the current situation of certain villages in disaster relief in neighboring rural areas?

This research is based on descriptive-survey method and is of practical purpose. The present article has two main parts, as with other researches. The first part is devoted to library and documentary studies in the field of theoretical literature on the subject and background of the research, and the second part to field research and surveying (questionnaire, interview) for data collection and completing the questionnaire among the experts. The statistical population of this study includes all villages of Hamoon city including 66 villages (these villages have a population of more than 50 households because villages with less than 50 households do not have the necessary facilities and services to assist neighboring villages in times of crisis). A total of 8725 individuals were selected as sample village units (Table 1). In order to achieve the research objectives in the context of field studies, a wide range of indicators has been studied in the form of expert-based questionnaires (Table 2). After data collection, AHP software and SPSS were used for data analysis. Expert Choice software was used to perform pairwise comparisons, hierarchical production, and calculation of weights in the fuzzy hierarchical process. Fuzzy paired comparisons performed by experts were used to weight the benchmarks and sub-benchmarks, and GIS software was used for spatial analysis of the villages. A paired comparison questionnaire was designed and completed by 15 experts. The validity of the questions was confirmed by expert groups and its reliability was calculated using Cronbach's alpha coefficient. This coefficient was 0.839 indicating acceptable reliability.

The results showed that the villages of Hamoon had an unfavorable situation when faced with natural and human crises. In fact, in this study, 4 levels (very desirable, desirable, undesirable and very undesirable) were used to rank the villages and the final result showed that out of 66 villages studied, 10 villages were in very poor condition and 56 Village in poor condition. This indicates the weakness of the facilities and services in the villages under study. The results are in line with the findings of Riahi et al. (2014), Bozgeram, Javan, and Katby (2015), where the authors stated that the current condition of providing safety services in rural areas is inappropriate and lacks a scientific model. Also, the results of Sadeghi et al. (2015) showed that based on the cynical scenario, all rural settlements in the study area have a standardized value of environmental vulnerability of more than 0.75% and are in unfavorable conditions.

Looking at the natural position of the area, one can see that the city of Hamoon is located on the river Hirmand. The presence of this river is a major cause of the massive floods from Afghanistan to Iran and can pose a serious threat to the residents of this area, especially the farmers and the villagers. On the other hand, the location below the Hamoon Lake has caused the crisis of 120-day wind to drain rural people's lives during droughts, and in addition to blocking the village's access roads, respiratory problems for local people. It is especially beneficial for the elderly and children. In this regard, suggestions are made to improve the situation in the region.Regarding the functioning and distribution of relief agencies at the village level, it is suggested to facilitate relief by utilizing grassroots mobilization or the participation of nongovernmental departments and, thereby, to provide uniform relief at the village level of each district so as to increase and develop pre-crisis trained human resources, which can reduce vulnerability among the population in times of crisis. Besides, it is recommended to establish local crisis management hierarchies to increase efficiency and speed up relief.

In recent decades, the growth and development of the tourism industry and its adoption as one of the major economic activities by developed and developing countries and competition for major tourism destinations in order to attract tourists has led planners to increase tourism revenues (Farrel & Mation, 2002). In recent years, rural tourism has been considered as a tool for achieving economic, social and recreational growth. Rural tourism promotes economic growth, creates diversity and stability in employment, dynamics of trade and industry, expands opportunities for income-generating activities, creates new markets for agricultural products, and expands the base of a regional economy. Although rural tourism has been considered as one of the strategies of rural development in recent years, the level of environmental vulnerability in tourism target villages is still high for tourism development and is not well prepared (Munar, 2002). On the other hand, the rapid growth of the tourism industry in the last half century has led to increasing pressure on the environment. Studies have shown that prioritizing the economic benefits of tourism development has undermined the principles of sustainable development in different areas and has put the environment at risk (Mexa & Coccossis, 2004). Therefore, one way to reduce environmental pressure is to determine the capacity of different tourism areas and to determine the amount of space required by users based on this capacity. Determining the amount of space required for each user depends on various factors, and the most important is the number and the type of tourists and travelers who use tourist sites for different purposes. The number of tourists allowed to enter the place is also determined by the capacity of the tourist complexes. Among the main purpose of this research is to determine the amount and number of tourists in terms of environmental potential of Kong village.

The research methodology is applied in terms of purpose and is descriptive and analytical. Data collection was done in both library and field formats and field studies were conducted through observation and interview with villagers. In the present study, three types of physical, real and effective acceptance capacity were used to measure the capacity of tolerance in Kang village. According to observations and field studies, the most important limiting factors for tourists in the Kang village are estimated to be climatic characteristics. In this study, 4 factors including severe sunshine, number of frost days, highest maximum temperature above 30 ° C. The highest minimum temperatures below 5 ° C were considered as the main constraints of the region for tourism development. This research was carried out in the tourism area of ​​Kang village, in Khorasan Razavi province, 29 km southwest of Mashhad city with 160 hectares with latitude of 59° 11'85 east longitude and 36° 20'59 north latitude in a mountainous position. This region is located in the north of Nangarhar village and in other directions among the Binalood mountains and is temperate and has mild summers and cold winters. This range has many highs and lows and ranges in altitude from at least 1200 meters to up to 3300 meters. The dominant slope of the region is between 25-35%. The area has high tourism values ​​in terms of diverse mountain landscapes, lush valleys and gardens and natural landscapes.

As it was mentioned in the specialized studies of tourism feasibility study and for loading of tourism activities, one of the important issues in this field is the capacity of tolerance or acceptance of the area which has to be studied from both physical and human dimensions. The number of visits per day to the village is due to the attractions available in the village under study based on interviews with local managers. Finally, based on the maximum daily minimum temperature below 5° C for the village, about 90 days has been set. Tourism capacity of Kong village is estimated at 52,240 people per year, taking into account the stated environmental and climatic conditions.

In the process of planning the development of the tourism industry, identifying the appropriate areas for tourism development and leisure time, categorizing and prioritizing and ultimately determining the levels of equipment according to their functions and functional status is very important. In fact, the planning of tourism areas should take into consideration the type of tourists, their preferences, the types of resources and attractions of the regions, market segmentations, and so on. The study area is a type of centralized tourism with the aim of providing diversified services to tourists in Kang village. The most important tourism resources of the region have been the beautiful natural landscape, the surrounding altitudes, the existence of gardens in the area, the existence of two permanent rivers, the enjoyment of indigenous culture, historical and stepping-stone habitats and so on. Due to the type of tourists that are mainly regional and come from Mashhad to this village, the needs and limitations of tourists and the amount of facilities required have been discussed. According to the surveys, these facilities mainly include accommodation, catering, services, recreation and more. In this study, in order to calculate the physical tolerance capacity of the tourism area of ​​the village, this amount was estimated to be 1536,000 people per year considering the hours of tourist presence and required space the amount of effective tourism bearing capacity was calculated, taking into account the maximum physical capacity, environmental constraints and available tourism services and facilities, which was calculated as 303015.
Based on the calculations made for the study area, the physical capacity of tourist acceptance in the target village of Kang tourism is 1536,000 persons per year. It should be noted that according to the field studies and interviews with local managers, the number of tourists visiting the village during the year is about 96,000, with a large difference in physical reception capacity and actual number of visitors, indicating that the village Kang still has a high physical capacity to attract tourists. Also, in terms of actual bearing capacity, the number of tourists was 52,240 people per year, well above the current number of visitors (96,000). Thus, the effective bearing capacity was calculated to be 303,015 persons per year, which is more than the current number of visitors. But the important point is that since the physical reception capacity of the area is calculated only on the basis of area, it cannot be a criterion for rural planning and tourism but because of the actual reception capacity, tourism constraints and effective reception capacity, facilities and services available. The results are somewhat closer to reality and more effective in rural planning.

Nowadays, the key role of mining industry in economic development, technology and urban growth in many countries around the world, including Iran, is not unknown. However, the mining industry is one of the high-risk industries and causes major environmental problems. Despite the positive achievements of mining, which has led to sustainable development in various countries around the world, due to the formation of huge volumes of waste materials from mineral activities, pollution from acidic drains, transfer of hazardous elements to surface and groundwater resources, and natural land and landscape destruction, it is one of the most dangerous industries and is one of the most important environmental problems. For this reason, environmental risk assessment has become particularly important in this industry. The purpose of this study was to evaluate the environmental risks of Sungun copper tailings dam using EFMEA method. The Sungun Dam tailing dam is considered a type of environmental threat because it is located in the upstream of agricultural lands and villages as well as one of the branches of Sattarkhan-e-Ahar river. To the best of authors’ knowledge, no study has been conducted on tailing dams risk assessment in the country; hence, the present study has analyzed the risks and threats of the Sungun tailing dam using the new EFMEA method.Study Area The tailing dam of the Sungun copper complex of Tabriz and its associated facilities is located on an area of ​​1400 hectares near the copper mine and its average elevation is 2313 meters above sea level and is located 130 km north of Tabriz and 30 km from Varzaghan city. It is a rock fill dam with clay core and has been built for the purpose of storing waste material extracted and processed from various activities of Sungun concentrator plant which is in operation since September 2006. Tailings dam infrastructures include: 1- Primary or initial dam (built for early storage in early years of operation), 2- Seepage or returned water (all foundation and body leakages are collected in this dam’s reservoir and pumped to the tailing dam reservoir station. Moreover, it has a maximum depth of 37.5 meters and length of 130 meters and prevents leakage of seepage water from the tailings dam to downstream) and 3- River diversion system (dam upstream cofferdam, temporary diversion channel, and diversion pipeline). Figure: Location of the Sungun Complex

At the beginning of the research, the background and history of past studies and the guidelines related to the research problem are identified. Gathering information about the study area will be conducted using library studies (theses related to the studied area, reports of the environment agency, etc.). Then, to determine the risks, a visit to the Sungun complex was carried out to identify the activities and potential risks of the tailing dam. After identifying the risk generating activities, a questionnaire was distributed to 18 environmental, safety and health professionals and personnel of the Sungun tailing dam. In the next step, to prioritize the risks, another questionnaire was again given to the same experts.  Finally, based on the opinions expressed by experts, the risk factors in the three accepting environments (physico-chemical, biological and socio-economic) were determined. Due to the fact that the data collected from the questionnaires were qualitative, EFMEA method was used to quantify and analyze them. In this method, to determine the severity and probability of detection and occurrence of any potential risk in the receiving environments, specific tables related to the method of EFMEA were used.

Risk Priority Number (RPN) was calculated for each of the risks in the physico-chemical environment. The results show that seismicity with numerical value of 21.08 has the highest and flooding rate and flood risk with numerical value of 2.45 has the lowest numerical risk value. The results of numerical calculation of risk in biological environment show that noise pollution with numerical value of 18.24 has the highest numerical risk value. The lowest risk priority number was associated with an animal mortality with risk value of 3.99. Furthermore, the results of numerical calculation of the risks identified in the socio-economic environment show that the highest numerical value of the risk is related to the effect on the landscape with 24.12 and the lowest numerical value of risk is related to the risk of reducing or closing the mine production with 0.81. Comparison of the results of this research with previous studies shows that the results of the present study are in good agreement with previous research.
According to the results of the present study, the most important risk in the physio-chemical environment was the seismicity of the region. In the literature review, it has been observed that the importance of this risk has been such that several studies have examined the effects of this risk in the field of mining and waste dams as a very important risk and concern of those in charge. Moreover, according to the regulations for designing buildings against earthquakes in Iran (Standard 2800), the main area of the Sungun copper mine tailings dam area is located on a relatively high seismic risk zone, which also confirms the importance of seismic risk in this dam.Furthermore, the present study identified noise pollution as the most important risk in the biological environment of the project under study, which is affected by the sound of explosions in mines and the operation of machinery. According to researchers, for many mining activities, the management of noise emission levels is a very important point in the operational phase of mining. For this reason, the use of noise reduction equipment for employees should be seriously put on the agenda.The risk of destructive effects on the landscape was also obtained as the most severe risk in the socio-economic environment of the Sungun copper mine tailings dam. Researchers have found that waste dams have a negative impact on the environment, such as the extinction of plant and animal species and the disturbance of the ecosystem's balance. In another study, ecosystem degradation was identified as the most important environmental risk in the Angoran zinc and lead mineral complex, which is consistent with the results of current research.

The main purpose of construction of tailings dams is to manage, collect and maintain tailings waste and effluents from mining activities. On the other hand, hazardous pollutants in acidic waste and scrap stored in tailings dams have the potential to cause adverse effects on the environment. In the present study, the environmental risks of the Sungun copper mine dam were evaluated by using EFMEA method in order to prevent accidental dam leakage or failure. In order to reduce or eliminate the risks and factors that cause environmental risks, inspection and monitoring periods in accordance with the identified risks should be considered as one of the most important objectives of the management programs. Moreover, it can also be concluded from the results of this research and its discussion that the method of analyzing the modes and effects of environmental failure (with regard to the non-detection parameter) is a suitable and efficient method for assessing environmental risks in tailing dams. Applying fuzzy logic as well as assessing environmental opportunities can be considered as topics for future research.

By raising the number of wars, especially during the last century, and by increasing the harm and loss of human lives and financial and psychological damage to people, efforts and movements were studied and considered in scientific terms under the passive defense. Today, the aim of targeting the cities with weapons and destroying urban infrastructures, primarily through aerial strikes, is to disrupt morale and cause harm to economic conditions and social systems, which can cause many disasters in case of destruction of such centers because of the high numbers of service users. Considering the importance of urban infrastructures during war, especially during air fights, proper attention to the principles of the passive defense approach has much higher priority in site selection and design. Mashhad is one of the most vulnerable cities of Iran in terms of war for having a high density of population and buildings, vast quantities of deteriorated texture. Since the aerial attack in this city has not been applied, we are trying to investigate the spatial safety of its urban infrastructures.Many researches have been carried out in Iran on various topics related to passive defense. This research is modeling with the ANP-DEMATEL-GIS approach of boundary protection and vulnerability of urban infrastructures against airstrikes. The following are some of the most significant research activities in this field. Parisi, et al . (2014) used passive defense criteria in Saqqez to enhance urban safety and the need for it at the national and regional levels. Mohammadi Dehcheshmeh (2014) applied passive approach to civil defense on the Ahvaz, which led to the recognition of local standards for particular land use. Sajjadian, Alizadeh and Parvizian (2016), analyzed the risk associated with hospital location in Ahvaz from the perspective of passive defense. Iraqi (2011), Kamran and Hosseini Amini (2012), Zarehpour (2012), Hosseinzadeh (2013), Khmer (2015), and Alizadeh (2015), showed the importance of passive defense studies in urban development and safety of cities.

To achieve the objectives of the research, infrastructure Indicators were extracted, including particular infrastructure, emergency services, public and management facilities, and 1560 infrastructure with desk studies and questionnaire planning. To measure the neighborhood pattern, fourteen significant layers in infrastructure vulnerability were identified and determined by distance operator for each layer against the Mashhad airstrikes and weighted using ANP-DEMATEL's combined methods. By adding these weights, standard distance maps were prepared by the ArcGIS spatial analyst and fuzzy overlay tools, and through the Geoda software regression tool, the trend pattern of four category infrastructure were calculated for urban infrastructure distribution against airstrikes.

The vulnerability can be considered an inherent flaw in the specific dimensions of the city's environment, which is prone to damage to the biological and physical properties of the city and modeling spatial vulnerability in terms of passive defense for the city's potential safe prospects. In the present study, after extraction of damage indices in the urban infrastructure of Mashhad in airstrike, using a hybrid model ANP-DEMATEL-GIS, the analytical level and spatial relationships, as well as the priorities of the vulnerability level from very high risk to very low risk were determined. The results of the vulnerability distribution of urban infrastructure in Mashhad is separable in two levels:After analyzing the neighborhood trend using ANP-DEMATEL, in the field of effectiveness and influence, health and industrial are recognized as most effective indicators and warehouses and religious buildings classified as most affected indicator. The effectiveness and affectedness of indicators are of the most critical factors in such a way that the risk is recognized from the viewpoint of passive defense and partly on the safety of the effects. The final weight of the model also indicates that police centers, urban facilities and administrative centers respectively have the highest weights of 0.12, 0.118 and 0.117. Religious centers and health centers have the lowest weights of 0.008 and 0.009, respectively. The pattern trend in the evaluation of useful indicators classes in vulnerabilities shows that the highest coefficient between the influential factors of vulnerability is for particular infrastructures and management infrastructures with a coefficient of 1.55 and 1.18 and the lowest coefficient is related to the public infrastructure which is 0.002.

Spatial results clearly show that more than 60 percent of the infrastructures are in a vulnerable and insecure condition and that just 5 percent of all urban infrastructures are in a safe or low-risk condition.