Journal of Spatial Analysis

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Environmental hazards include all kinds of hazards in the environment such as natural and technological or natural and man-made. The natural phenomena such as rains or floods are the normal behaviors of the nature which only when they cause damage to the human life, are considered as hazard. The technological events such as road accidents, air pollution and chemical pesticides are always dangerous to human life. Both kinds of two hazards are produced in the context of human- nature relation. For example if human beings avoid flood prone areas there will be no harm or damage. And if human beings control their waste in the urban areas they will never pollute the city. Thus, this is the human who causes risk and damage to his life. The relation between human and the nature is governed by the thoughts and beliefs of human or in general terms his world perspective and philosophy. It is the human perspective and belief which controls his action at any circumstances. A person who believes in the nature as his mother and supporter of life differs from the one who thinks of nature as a sole source to use and enjoy. The first one gets only his basic needs from the environment, but the second person tries his best to exploit the nature for his benefits. Therefore to understand the intensity and frequency of environmental hazards, we should investigate the mental beliefs of people living in different places. A brief discussion of the historical development of hazards will help us to have a better understanding of the philosophical basis of the environmental hazards. From the ancient times up to around nineteenth century life was very simple and man had been using nature only for his basic needs, there was no consideration of environmental hazards. Hazards were considered only as diseases threatening the human life. But later, especially after the industrial revolution, due to the increase of human population and demands, the use of natural resources was exponentially increased far above the production and recovery of the nature. This process triggered the occurrence and expansion of environmental hazards.  The human- nature relation is studied by different scientific fields such ecology, anthropology, and geography from different aspects. The ecologists mostly emphasize on the relationship of individuals with his environment, as the characteristics of environment controls his life. While geography studies the spatial relations between human population and environmental assets. As a result, the philosophical stances of these fields differ substantially. Ecologists want to see whether this relation is dominated by the needs and intentions of man or by the capacity and potentials of the nature. From this point of view three kinds of philosophies were developed including anthropocentrism, biocentrism and ecocentrism. On the other side, geography emphasizes on the spatial distribution of human population on the basis of environmental resources. This spatial relation between human and natural resources is believed to be controlled by the nature or human conducing to the development of two philosophies of environmental determinism and possiblism. Ecological philosophy of anthropocentrism was dominated in the earlier centuries, focusing on the will of human to use and enjoy the nature. In this view, the nature has the instrumental value for human. The result of this philosophy was depletion and destruction of the environment in favor of the human development. But during the twentieth century some philosophers stated that the human does not have the right to harm and damage all living creatures including animals and plants. This view ended with the biocentrism approach.  During the second half of the 20^th century due to the over exploitation of nature by human, the philosophers and ecologists realized that the human kind in order to possess a sustainable living should not harm any members of the environmental system including even rocks, rivers, soil and etc. This approach developed the ecocentrism philosophy. The main controlling force in these philosophies is the ethical stance of humans. On the other hand, the older geographers believed that it is the nature that controls the human distribution and living conditions. The humans cannot change the natural arrangement of the environment and should limit their activities to the natural allowances. The development of the technology after the Second World War changed this view. Some geographers believed that human can change the environment by his techniques and developed the possiblism. The adoption of this philosophy and the growth of industrial development ended with the deployment and damage of the natural resources. It is clear from the aforementioned discussion that in all cases, the main reason for the depletion and destroy of the environment was lack of ethical considerations in human behavior toward the nature. If the ecologists have come with the ecocentrism, geographers developed the geocentrism philosophy. That is, to save the nature and prevent environmental hazards we, as human beings, should preserve the natural arrangement of resources. We should not disrupt the spatial order of any resources, because it will cause harmful results in the environment. For example eroding the soil will deteriorate the vegetation and cause floods and other hazards. The alteration of spatial order of surface temperature has caused the thermal imbalance and hence global disorder and warming. There is no doubt that the relation of each human should be controlled and put in the moral contexts, but to prevent the environmental hazards an overall effort is needed over the environment which is possible only through the preservation of spatial order of natural resources. Spatial management of land resources is the outstanding example of this philosophy and ethic.

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Thunderstorm is one of the most severe atmospheric disturbances in the world and also in Iran, which is characterized by rapid upward movements, abundant moisture, and climatic instability. Since this phenomenon is usually accompanied with hail, lightning, heavy rain, flood and severe winds, it can cause irreparable damage to the environment. Investigation of spring thunderstorms has a great significance regarding the irreparable damages can cause by them and also because of the higher frequency of this phenomenon in the spring and the necessity for preparedness and disaster mitigation actions. To identify the locations of the major thunderstorm risk areas, the entire country with an area of 1648195 square kilometers, which is located between the 25°-40° north latitude and 44°-63° east longitude is considered.     Spatial distribution of the occurrence of hazardous spring thunderstorms was analyzed using a series of monthly thunderstorm frequency data obtained from 25 synoptic stations over a 51-year-long period (1960-2010). Ward's hierarchical clustering and Kriging methods were used for statistical analysis. Initially, total number of thunderstorms in April, May and June were considered as the frequency of occurrence of thunderstorm in different stations in the spring. Measure of central tendency and dispersion which consists of the sum, minimum, maximum, range and coefficient of variation, standard deviation, and skewness were used to clarify the changes of thunderstorms and to determine the spatial and temporal climatic distribution of spring thunderstorms. An appropriate probability distribution function was chosen to determine the distributions of the data.  Due to the large volume of data and the uneven distribution of stations, cluster analysis and kriging methods were used to classify different regions into homogeneous groups for zoning and spatial analysis of spring thunderstorms, respectively. The statistical characteristics of spring thunderstorms were reviewed and fitted with a 3-parameter Weibull distribution. Regions considered for this study were classified in four separate clusters according to the simultaneity of thunderstorms in the spring. After zoning, it was found that the highest rates of thunderstorm took place in the northwest and west of country. The northeast of Iran has the second highest number of thunderstorm occurrence. The least number of thunderstorm event had happened in the central and southern half of the country.     According to the descriptive statistics parameters, maximum number of thunderstorms occurred in May.. Based on the results of the cluster analysis, there is a similar trend in the central and eastern regions, the rest of the country was clustered into five distinct homogeneous regions, including the northwestern, western, southern, northern, central northern and northeastern regions. Zoning results indicate that the highest number of the occurrence of this phenomenon in the country is concentrated in the northwestern and western regions. Higher frequency of occurrence of thunderstorms in the northwestern and western regions may be attributed to local topographic conditions like high mountains, orientation of the terrain, solar radiation on slopes and existence instability conditions, hillside convection, the presence of water resources and specific climatic conditions in these areas. In addition, as a result of a continuous surface obtained by the method of interpolation with the least amount of systematic error and also the use of correlation functions for recognizing the spatial structure of the data and estimating the model error when using the Kriging method, the weights are chosen in order to have a more optimized interpolation function. Also the cluster analysis may significantly reduce the volume of operation without affecting the results and will help in finding a real band due to more appropriate classification of different geographic areas with greater spatial homogeneity and minimal variance within the group. Based on the results of the spatial analysis, it is clear that Kriging and Ward cluster analysis methods are appropriate for thunderstorm zoning and classification of different regions according to occurrence of thunderstorm, respectively.

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Today urban livability reflects a powerful discourse in urban development and city design that is prevalent in urban planning literature suggests that there is an ideal relationship between the urban environment and the social life .On the one hand, the livability indicates the strong urban influence and attraction. On the other hand, the livability will further strengthen the urban connectivity and influence by attracting more investment, human and cultural resources. The livability of a city is closely related with a healthy and ecological city and sustainable urban development. This study aimed to measure the livability in the neighborhood of  region(2) of Sanandaj city and research methodology is descriptive-analytical.  A base map of the study area was prepared using Arc view Software. The region (2) is located in the central parts of the Sanandaj city.and the population of region is 239,965. The sample size was calculated using the formula Cochran. Therefore, 370 residents of neighborhood filled the questionnaire and expressed their viewpoint about the indicators of livability. A data collection method with respect to the merits of subject is Library and field method. The filled questionnaire by residents of different aspects of livability is measured. According to the Social features, facilities, geographic, economicfacilities and services available in the region , urban managers and experts have weighted the dimension and index of urban livability.The index of economic, social and environmental livability was calculated and  the sum of these three dimensions is considered as total livability.To assess the livability of neighborhoods, data from filled questionnaires by people have been analyzed by the software GIS, SPSS and Excel. Using hot spots, three indicators and total livability of each neighborhood displayed.The results of the analysis of economic indicators showed that the areas in  the western parts of the city  are hotter and more color spots, But in the East and South East areas neighborhoods, like Shahrdari, Sepahdegaran  have  in colder and less color spots. This actually shows the cluster distribution of economic indicators. Also the results of the analysis of social indicator showed that spatial distributon is cluster neighborhoods like Khosow Abad, Masnav, Chahar Divari, Mobarak Abad are in the hotter spots and neighborhood Adab, Varmaghani, Hassan Abad are in colder spots.The resualts for environmental indicator reveals  that spatial distribution is cluster. Mriginal neighborhoods are in colder spots and Nezam Mohandsi and Shardari town and Degaran allocated the lowest Z. In contrast neighborhood like Mobarak Abad and Khosrow Abad are in hotter spots. Analysis of hot spots for total livability implies that neighborhood in West area of city follow clusters of  hotter spots and the South East neighborhood follow colder spots. This can result in injustice in space services and  the lack of performance in order to improve the quality of the environment and quality of life in area, livability is defined as one of the aspects that could contribute to a high quality of living, because high quality of living will affect citizen's lifestyles, health condition and shows stability of the built environment. most researchers agree that livability refers to the environment from the perspective of the individual and also includes a subjective evaluation of the quality of the place so measurement of urban livability   for all places promote the perception of urban managers and planners and with such knowledge, the path will be open for practical, creative and futuristic management of the urban environment. In relation to the livability of neighborhoods to each other, spatial and non-spatial analysis shows that areas with different ratings are compared to each other. With respect to results of measurements of livability: centrally located neighborhood is more livable than their peripheral counterparts which may calculate that location has significant importance in the pattern of livability. Therefore spatial distribution of dimension and index of livability is not the same extent.The results showed that between main dimensions of neighborhood livability is not different. But in terms of spatial distribution, three dimensions are not equally distributed and it is cluster. Ranking based on total index indicate neighborhood of Khosrow Abad with score (3.279) is ranked at first and Sharif Abad with score (2.228)is ranked at last.

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Precipitation is one of the important aspects of the Earth’s climate that has both spatial and temporal variations. Understanding the behavior of this element and analyzing its spatial and temporal variation is importantwhich can lead to a comprehensive and detailed planning for water resource management and agriculture. Geostatistical techniques and spatial autocorrelation analysis are the most widely used techniques in the field of the spatial continuity. Spatial autocorrelation analysis is applied to help researchers understand the spatial patterns in the area.

      The purpose of this study is to identify the heavy precipitation spatial patterns in Guilan Province. For this purpose, the 6- hourly sea level pressure of the network from  0 to 120 Easter longitude and 0 to 80 Northern latitude with 2.5×2.5 degrees spatial resolution were obtained from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) for the period 1979-2010. The daily precipitation data of 21 stations were obtained from the Islamic Republic of Iran Meteorological Organization and Ministry of Energy.

      Guilan province is one of the most humid regions in the country. The heavy rain days were selected as days when more than 30 percent of the all stations had daily rain amount more the 95^th percentile. As a result, 321 days were selected as heavy and widespread rainy days. By using principal component analysis these 321 days were reduced to 9 factors. These factors then were subject to cluster analysis with Ward method and resulted in three surface pressure patterns of heavy rainy days. Within the resulted pressure patterns by using local geostatistical techniques we identified the heavy rain spots and their spatial orientation. These spatial methods include Kriging,  Geostatistical Analysis, and Anselin local Moran index.

According to the results of this research, the first pattern was characterized with a high pressure over northern part of the Black Sea causing the highest Variance of heavy rainfalls. The second pattern is identified as a low pressure on the Black Sea. But the third pattern showed a precipitation distribution with low variation caused by the Siberian high-pressure. The results of Spatial Statistics techniques indicated that heavy rains were clustered in all there patterns. The clusters of heavy rains were localized mostly over the coastal areas and some over the central regions. The clusters of the western high-pressure patterns penetrated somewhat inside the province, while clusters of the Siberian high pressures was located on the shoreline of the province. The precipitation of western migratory high-pressures was heavier than of the Siberian high-pressure. The results of the standard deviation ellipse showed that heavy rain clusters were oriented in the east-west direction and were nonhomogeneous. While the ones oriented in the south east direction were more homogeneous and clustered. Because of this arrangement, the entry of moisture from the Caspian Sea is relatively concentrated on the East or North East. Because of the concentration of heavy rains in the central areas of the coast, the risks of floods and soil erosion is very high in these areas. This study showed that contrary to the popular belief, the heavy rains of Guilan were produced by western systems and the role of the Siberian high pressure is less important and is limited only to the coastline.

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Groundwater resources are important sources for the supply of water in agriculture, industry and drinking in Ardabil plain, therefore underground water resources planning and sustainable management of these resources are important. The purpose of this study is grading the villages in the plain of Ardabil in underground water crisis and changes during the years 1360-1391. The information obtained from 39 wells, piezometers in plain of Ardabil. Using simple techniques and fuzzy cumulative weighting and interpolation methods, the piezometers interpolation of shallow water table and how it changes during the period is showd.

Introduction
     Groundwater is one of the main sources of drinking water supply for many people around the world, especially in rural areas. Groundwater can be contaminated by natural or human activities are numerous. All activities including residential, municipal, commercial, industrial and agriculture can affect groundwater quality. Groundwater contamination can result, such as the loss of a source of water supply, high cost of clearing the high cost of alternative water supply or cause potential health problems. Given the importance of determining the results of the plains of the country, the aim of this study was to determine changes in aquifer storage of Ardabil using statistics and analysis on multi-criteria decision-making and evaluation of groundwater is a crisis situation.

Data and Methods

     In this study, the data of piezometers wells in of Ardabil plain scattered through the city of Ardabil Regional Water Authority have been prepared. Also, the surface layers and point to the plains of Ardabil, political divisions and the location of wells, piezometers villages for final maps have been used. The data of deep wells, as well as cultivation of four major product with a high water requirement of wheat, barley, potatoes and forage to determine the relationship between ground water and water harvesting has been a drop in water table.

The study area

     Plain study area is located in the north-west of Iran in Ardabil province (Figure 2 and Figure 3).  The average height is about 1360 meters above sea level  It covers an area of approximately 820 square kilometers and is located in the Gharasoo watershed.

• Inverse Distance Weight;
• Global Polynomial Interpolation;
• Local Polynomial Interpolation;
• Radial Basis Functions;
• Straight Ranking;
• Fuzzy Normalized;
• Fuzzy multi-criteria decision-making;
• FSAW.

   The first step is to evaluate each process and required hydrological data collection, and the coordinatingits location. The geostatistical methods of IDW, GPI, LPI, and RBF in the ArcGIS software were used for  interpolating all existing data and a drop in water table in the area of standards for grades 10 class (raster) within restricted fields of Ardebil were determined.

    Finally, using simple collective weight, weight-bearing layers and layers of loss data water table for the years 60 and 90 is obtained. To get the final map of water table drops, the two layers are deducted and the final map of Ardabil plain water table drop that phase is obtained.

     Analysis showed the reduction of water table almost 47 percent in 1391 compared to 1360. As can be seen in Figures 12 and 13, maximum of 45 meters water table wells, piezometers in 1360 to more than 70 m in 1390 has come to reveal the deterioration of the aquifer Ardabil.

    Pholadloo_e_Shomali district with the highest concentration of deep wells in the near future to continue the removal of existing deep wells, groundwater resources will go into sharp decline.

    Sharghi Village goes to the crisis and in the meantime, the central Vilkij district includes the eastern part of the plain, the drop in water table aquifer at greatest risk to the two villages in East and Central Vilkij.

• Due to the limitations of traditional agricultural development potential ground water;
• Increase the efficiency of irrigation, changing crop patterns of water needed to fill low-power consumption;
• Efficient use of water resources and prevent unauthorized digging deep wells to exploit the nutritional front, especially in the East and Southeast plains.

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Spatial analysis as the main approach of geography was reviewed and searched through its historical development. The results of this exploratory research showed that this approach was born after the Second World War due to the overall interest of geographers to develop universal theories and laws. The advocators of this field believed that the old regional geography was not able to develop a scientific and applied knowledge. The main motivation of the development of the spatial analysis was the quantitative revolution of the 1960’s which was triggered by the article published by Shaeffer in 1953. This was followed by some prominent geographers such as Bungeh, Ulman, Barry, Hagget, Chorley and others. Bungeh and Harvey strengthened the philosophical foundation of spatial analysis and others such as Hagget , Chorley and Hajestrand published important books in the field of quantitative geography. The main objective of spatial analysis is to analyze the distributions through the identification of their global and local structures and reasoning these structures by their spatial relationship with other distributions. In this regard it uses quantitative data and mathematical language to achieve the spatial theories and laws.

     The spatial analysis studies the spatial distributions and structures. These are the entities that are not subject to the human interpretation and thinking. This approach is true in the both physical and human geography. The knowledge it tries to achieve is the theories and laws about the spatial distributions. The methodology of spatial analysis is the quantitative methods such as experiment and survey. Thus in terms of ontology the entities of spatial analysis are independent of human mind and objective. The spatial characteristics of distributions are not constructed but discovered. The methodology used in spatial analysis is quantitative and objective including some methods such as experiment and survey. In 1980 and onward, human geography tried to move toward qualitative methods such hermeneutics but during 21^st century all branches of geography are using quantitative methods more frequently than qualitative ones; but the use of the combined version of quantitative and qualitative methods is becoming more frequent day by day.

  The introduction of Geographic Information System as the operational environment for spatial analysis works the approach has become more widespread and dominant. Geographers are now able to analyze more spatial data and discover more spatial theories to solve the spatial problems. GIS is the main tool for spatial analysis and by introducing the science of geostatistics has improved the scientific and applied power of spatial analysis. The application of quantitative geography including geostatistics and GIS requires improved knowledge of mathematics, geometry and statistics; the main language of today geography. The spatial analysis covers the important topics of geography including spatial distributions, regions, spatial relations especially the relation between human and environment, spatial structures, spatial reasoning, interpolation, and the most important topic of spatial planning. The spatial analysis is the only scientific field to define and develop spatial planning. With correct and logic spatial planning there won’t be any environmental hazards. Because in any region all human settlements and activities are planned according the potentials of the region.

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The process of urbanization and development in high-risk areas such as river banks has increased the vulnerability of urban communities to environmental hazards. The banks of Khoshk River in Shiraz is one of these areas. These hazards are two parts : hazards resulted from river and waterways erosion (destruction, transportation and sedimentation) and the hazards resulted from floodings over the surrounding urban areas.

In order to prepare the literature review for this study, the various books, theses and articles were applied. Also, in order to determine the spatial position of this section, the Satellite Images and Google Earth pictures were used. The Global Positioning System (GPS) was also applied for the field observations such as collecting spatial data, extracting the kind of formations, Geological structures and faults. ArcGIS and Global Mapper 16.2 were also used for data processing and mapping.

 The geomorphological hazards in Khoshk River bank were evaluated in two parts:

1. The evaluation and analysis of the role of river and flooding processes in creating the environmental hazards for Shiraz.
2. The evaluation and analysis of the role of humans as the intensive factors of riverine and floods hazards in city.

 The evaluation of longitudinal profile in the river indicates that when the stream is entered to plain, the water moves with more speed because of faults and high steepness over the  Drake alluvial fan. One indication of this process is the presence of coarse sands and angled gravels. In this part, the erosion of riverbank is much higher than the erosion of river bed. In this section, the longitudinal profile of the river has a regular trend of concave and convex sections due to the erosion in convex parts and sedimentation in concave parts. In addition, there is a balance between deposition and digging process. The erosion is very intensive in regions where arc meander is close to  the flooding plain of the bank and causing the destruction of all facilities.

 The longitudinal profile in the river indicates that the height and slope of river has been reduced from North West to Maharloo River. The average slope of the river is 2.40%.

         In order to determine the role of flooding in creating risks for Shiraz, the floodwater discharge data were collected from Regional Water Organization. Furthermore, in order to understand the role of maximum discharge values, various experimental relations were used in the basin. The un- ordered development of urban areas especially in the north west, destruction of natural areas intensified the amount of  runoff and reduction of vegetation cover.

 The pick values of maximum discharges in Khoshk river  with the return periods of 50 and 100 years waere estimated 115m³/s to 131.4m³/s respectively which may result in overflowing of water on the streets. The human factors include the construction of bridges on the river, fencing river with stones and construction of beach, construction of bypasses for public transportation and reducing the traffic in the riverbed and trespassing to the river bed in Shiraz caused the overflowing of water from the river. The last floods in Shiraz occurred in 1987 and 2002 that caused major losses to the houses and commercial places close to Khoshk River. In order to analyze parts of river that are close to the town and have more important influences on the hazards and disasters, the satellite images of khoshk river basin in the town were taken and the river was classified in three sections with regard to risks level, river morphology and river classification based on its hazards for close areas as high risk (Maali abad Bridge limits to Fazilat Bridge and Sardkhaneh Bridge to Maharloo River), low risk(Tange sorkh to Maali abad Bridge) and medium risk (Fazilat Bridge to Sardkhaneh Bridge).

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Human and social crisis and natural hazards are of great importance and urgency in urban development planning. As a result, in order to reduce the loss of life and financial damages, one of the necessities of urban planning and spatial analysis is identification of vulnerable areas. In Piranshahr city due to its sensitive geographical location and zoning the implementation of passive defense in urban planning is of utmost importance. The importance of this study is to examine vulnerabilities in order to operate an optimal crisis management. The main objectives of the study are:

- Identifying the most vulnerable neighborhoods of the city.

- Identification of vulnerable facilities and equipments.

The research method is descriptive - analytical and research space is Piranshahr city limits. In order to identify the characteristics and distribution of facilities and equipment in the border town Piranshahr library and field methods have been used. The results of the last census (1390) of Statistical Center of Iran, observation and interviews with local people and experts was used. The master plan and detailed studies of 1391 and relevant maps of the municipalities, the aggregation and dispersion of urban facilities and equipments were used. To value the passive defense importance in the city sixteen vulnerability variables were defined and measured according to opinions of people and experts. Then the data were analyised with the  Delphi software. The main variables include: Lifeline, crisis management centers, military bases, equipment and support centers. After determining the rating of each factor and sub-sectors, by using AHP and Expert Choice software vulnerability of each of the following criteria were calculated. For mapping the city Piranshahr fuzzy model is used.

The results showed that the variables of vital artery with coefficient of (0.469), crisis management centers and joint support centers with coefficient (0.201), municipal equipment by a factor of (0.086) and military centers coefficient (0.043) are among the most vulnerable facilities and equipments in Piranshahr city. The neighborhood of western, central and south-west of the city, including the Kohneh-Khaneh and Grow of a cultural1 neighborhoods, Ghods, Isargaran, Zrgtn and Mom-Khalil, were the most vulnerable neighborhoods in the city regarding the military attacks. Spatial analysis of vulnerability of the city resulted in three vulnerability regions. The neighborhoods of the West, Central and South West (Kohneh-Khaneh and Grove neighborhoods and part of a cultural1 neighborhoods, Ghods, Isargaran, Zrgtn and Mom-Khalil) are the most vulnerable neighborhoods of the city. The reason for this situation are the physical characteristics of the city such as texture, organic, fine texture and high density residential units, existence of urban infrastructure, core founding of the city (the Kohneh-Khaneh neighborhood) and the secondary core (Zrgtn neighborhood). whereas the neighborhood (Park City and part of Koy-e-Khayyam and new neighborhoods of Mohammadkhan in the north and the south and southeast of the city) due to the preparations made for the perfect skeletal indices as well as the extent of large open spaces are somewhat immune and safe regarding the passive defense.

Keywords: Spatial analysis, vulnerability, Passive defense, city of Piranshahr.

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Climate risks are the inherent features of Earth's climate. The occurence of heat wave is one of these natural phenomena. Heat waves, one of the basic appearances of climate change, are very important because of frequency and damage of life and property, (Haddow et al, 2008). Frequency of heat wave occurence in recent years, is one of the aspects of climatic changes and extreme weather (Matthies et al, 2008), and resulted in heavy financial loss and increasing p mortality. From statistical point of view, heat waves are the positive changes and upper extremes of maximum average daily temperature, which continuing during consecutive days, weeks or months in certain geographical areas. According to the available definitions, two dimensions of time and space are important in the occurrence or non-occurrence of heat waves  (Smith,2013). Due to the positive slope of temperature and increase in temperature extremes and many changes in values of maximum temperature in Iran, main purpose of this study is the spatial and time distribution of heat waves on the plateau of Iran.

The daily maximum temperatures recorded in 49 synoptic stations of 31 years (1980-2010) climate normal period were used for the spatial distribution of heat waves. In order to determine heat waves, using the 95th percentile index, the temperature threshold for each month and each station was determined separately. The reason of studying heat waves in the monthly scale is temperature differences and different consequences in different parts of Iran, as an example, maximum temperature 30 degrees in May for south of Iran is normal, but for the northern regions of Iran is a heat wave and causes damage. So the basis in this study is determining heat waves and spatial differences of these phenomena in monthly scale. In this study, the heat wave has been defined as temperatures above the 95th percentile threshold per month, continuing for three days and more. So with specifying the threshold temperature for each month at each station in different parts of the country, temperatures above the threshold continuing for three days and more, defined as a heat wave for each month and the spatial distribution of heat waves was plotted in the whole area of Iran plateau for each month. In order to determine changes in heat waves in the whole country, the number of heat waves has been specified for the whole country in three decades (80-90-2000).

The spatial distribution of heat waves: Maximum temperature thresholds are related to the southeastern, southwestern and southern stations; and the lowest thresholds are northern coast and northwest mountains stations. In general, the minimum temperature thresholds are visible in the northern half and towards the heights; however, the maximum thresholds are visible in southern half. In this temperature variable, the role of latitude and altitude is dominant in lines with the same threshold of extreme temperature like other temperatures properties in Iran. Spatial variations of this temperature parameter throughout the year, increased from the Caspian Sea and North West of Iran to the South East and South West of Iran. In the entire study period, the number of heat waves in different parts of Iran indicates that most heat waves were occurred in the mountainous regions of Iranbased on the zoning temperature Alijani. The number of heat waves decreased from this area to the north and south coastal areas and East of and Central of Caspian has the lowest number of heat waves during the entire period of the study in Iran.

Time, temporal and decade distribution of heat waves: Time changes in heat waves shows increasing trend, As we can see the increase in the number of heat waves, from mid-90s and then, in 2010 most of it.Also, the 5-year average and decade-long average of heat waves, show a significant increasing trends and the most of the heat waves occur in Iran during 2000s. Time series of heat waves in Iran; show a significant increase over time.Hence, from the late 90's onwards, the spatial average of heat waves rather than the average before these years has increased. Iranian plateau in 1992 and 2010 has experienced the minimum and maximum of heat waves, respectively.

The results showed the minimum temperature threshold along the heights in northern half of the country and maximum temperature threshold at the southern half. Spatial variations of this thermal parameter throughout the year, is increased from the Caspian Sea coast and the North West of Iran toward the South East and the South West of the country. In general, this parameter that is associated with the extreme temperatures in Iran is under latitude and heights distributions the same as distribution of maximum temperature areas in Iran. But spatial distribution of heat waves as a natural hazard is different from the distribution thresholds and maximum temperatures. So that, the most heat waves are in Zagros Mountains, the East foothills of Zagros, South of Western and central Alborz and also southern Binalud foothills in the North East. The number of heat waves is reduced toward the center of Iran and the Great Plains (Lut and Kavir deserts). The minimum heat waves occur on the coasts of Caspian Sea, southern coasts of Iran, South-West and West Zagros and central Iran. The occurrence of heat waves in Iran have an average between 9 and 14 heat waves during all months of the year except for May with a maximum of 6 heat waves and June, with a maximum of 16 heat waves (months of minimum and maximum occurrence, respectively). This shows minimum increase in cold months and maximum increase in warm months. Therefore, the occurrence of heat waves in Iran is possible in warm and cold periods of whole year and there is a little difference between these two periods. This indicates both internal (local) and external factors (air masses) involved in occurrence of heat waves in Iran. The number of heat waves increase and decrease since January and June, respectively. This temporal sequence is disrupted by a sharp decrease in May (6 heat waves less than previous month).

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Probability of earthquake hazard		Distance to fault lines		Relative area
		Active Faults	Passive Faults	Active Faults	Passive Faults
Very low risk	0-20	60-76	32-42	7.29	1.42
Low risk	20-40	45-60	24-32	13.82	3.96
Medium risk	40-60	30-45	16-24	16.66	8.13
High risk	60-80	15-30	8-16	21.51	22.04
Very high risk	80-100	0-15	0-8	40.72	64.45
sum		-		100

Probability of earthquake hazard		urban Settlement		Population (2011)		Relative population frequency (percent)
		Active Faults	Passive Faults	Active Faults	Passive Faults	Active Faults	Passive Faults
Very low risk	0-20	3	1	135846	17106	1.14	9.07
Low risk	20-40	6	4	86133	144021	9.62	5.75
Medium risk	40-60	10	8	739095	754968	50.43	49.37
High risk	60-80	14	18	380908	273137	18.24	25.44
Very high risk	80-100	18	20	155188	307938	20.57	10.37
sum		51		1497170		100

Probability of earthquake hazard		Rural Settlement		Population (2011)		Relative population frequency (percent)
		Active Faults	Passive Faults	Active Faults	Passive Faults	Active Faults	Passive Faults
Very low risk	0-20	162	42	54240	30236	5.51	3.07
Low risk	20-40	379	147	183718	92018	18.68	9.35
Medium risk	40-60	481	291	255412	176183	25.96	17.91
High risk	60-80	553	766	245392	340448	24.95	34.61
Very high risk	80-100	1350	1679	244942	344819	24.90	35.05
sum		2925		983704		100

1. Meticulous supervision on safety of building from the stage of plan-making to administration which have to be based on engineering principles for earthquake-prone cities including Baresar, Ataqur, Asalem, Haviq, and Roodbar which are next to active faults
2. Prevention of formation of suburbs and towns on southern and northern parts of Gilan because these parts are really vulnerable to earthquake
3. Prediction of temporary accommodation in central Gilan because this part is less vulnerable to earthquake
4. To equip buildings, hospitals, schools, and other buildings located in big cities including Rasht, Bandar-E Anzali, Fuman, and Lahijan with facilities required in case of earthquake
5. To hold training courses in rural and urban parts of the mentioned province to make residents prepared for earthquake and for emergency evacuation
6. To prioritize reformation of old and historical buildings in Rasht because Rasht is mostly laden with old buildings which are really vulnerable to earthquake

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As 7 Stations include; Ardebil, Sarab, Shahrekord, Ahar, Takab, Zanjan, and Saghez were experiments on average every year less than 30 days with thermal stress. From these 7 stations, Ardebil and Sarab regions, having 3 and 7 days with thermal stress, respectively, have the least amount of days with heat stress. All the days with the heat stresses obtained for these stations have been the days of the first class of heat stress map, and all of them were randomly distributed over the warm period of the year.
But in contrast to this stations that had the fewest days of thermal stress, southern Iranian stations, especially those stationed at the Persian Gulf and the Gulf of Oman Sea coasts, were the most frequent days of heat stress.
The two Jask and Chabahar stations with the annual average of 304 and 301 days, with the highest thermal stress, were the most frequent regions of Iran. The lower latitudes, lower elevation, higher temperatures and relative humidity are factors that make the conditions for having the most frequencies of days with heat stress in this part of Iran.
The spatial pattern of five classes this index also show different patterns in comparison with each other so that as all stations in Iran experience at least 3 days of thermal stress in the first class during the year. But with increasing intensity classes, the number of stations that experience the conditions of these five classes over a year will be reduced. As for the second class, 16.2% of the stations, for the third class, 55.4% for the fourth class, 83.7 %, and finally for the fifth class, 90.5% of stations, do not experience comfort in any way during one year. Finally, with regard to the important role of the elevations in the spatial distribution, the relationship between the total frequency of days with thermal stress and elevation was modeled using classical linear regression model. The results of this model showed that per 100 meters above sea level, 9 days from the total frequency of days associated with Iran's thermal stress is reduced. This downward trend is such that there is no thermal stress in Iran at 2300 m above sea level. In other words, the height of 2300 meters is the elevation border between the occurrence and absence of days with thermal stress in Iran.
 

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Analysis and Measurement of Environmental Resilience of Villages in Gorganrud Watershed against Flood (Golestan province, Iran)
 
Abstract
Environmental hazards are inevitable phenomena that always place serious risks on the development of human societies, especially rural development. In the recent years, however, significant changes have been made in crisis management approaches, and the prevailing view has shifted from the "reduction of vulnerability" approach to "resilience improvement". Resilience is a new concept often used in the face of unknowns and uncertainties. Therefore, along with this change of attitude, it is important to examine and analyze natural hazards in terms of resilience. According to global statistics, floods, as one of the most devastating natural disasters, have caused the greatest losses and casualties to human settlements, which is true both in our country and in Golestan province. Investigations show that only in the statistical period of 1991-2014, 106 rainfall cases have led to the occurrence of floods in this province. These floods have damaged natural resources, the environment and the prevalence of environmental pollution; In addition, other natural and human factors have contributed to the heightened risk of flood damage. But if it was planned for the restoration of villages, then the damage could be reduced. Therefore, this research was conducted with the general purpose of determining the relationships between environmental factors and factors of rural communities of Gorganrud watershed on their resilience and numerical values. Finally, the residual spatial analysis of rural limited settlements was studied. Accordingly, the research questions are as follows: a) What is the relationship between environmental factors and factors in the villages of Gorganrud watershed in Golestan province with the resilience of the communities living in them in the face of flood? b) What are the resiliency values ​​of these communities in the environmental dimension and which zones? This is an applied research with descriptive-analytical method. A library of researcher-made questionnaires was used for collecting data using library resources. The statistical population consisted of 106 villages with 22,942 households. First, 31 villages were selected by cluster sampling. Then, using Cochran formula, 318 families were selected as sample size and selected by simple random sampling method. Also, for assessing the validity of the questionnaire, using Delphi collective wisdom methods, it was determined by using historical studies and opinions of experts in rural areas. The reliability of the questionnaires was also determined by using the Cronbach's alpha coefficient in the pre-test method. The value for the household questionnaire was r_a1=0.841 and r_a2=0.862, respectively. All steps for statistical analyzes have been performed by Excel and SPSS software. Additionally, the development of mapping, risk-taking, risk and resilience was also done with the help of ArcGIS software and the weight of each criterion was determined by the Super Decision tool; Then, using the weighted and linear overlapping methods, each of the sub-criteria of the main indexes was multiplied in its weights. The study area is divided into two distinct sections in terms of geological and geomorphological structure. The southern and eastern parts of it are the ripples of the eastern Alborz mountains, which are taller in the southern part and extend along the east-west direction. Also, the northern part of the studied basin is the Gorgan plain, in which the main branch of Gorganrud flows from east to west and all branches of the south and east are drained. Following the general slope of the main branch and its long-standing walls in the mid-east, it is usually not flooded; but as far as the west is concerned, its slope is very low and one of the flood plains is considered as the basin. The results of the research show that there is a significant relationship between the environmental factors of the studied basin villages and the resilience of the communities inhabited by them in the face of floods. Also, the average environmental resilience of the whole region was lower than the average (2.76 average), rural households in the sub-basins of TilAbad and ChehelChai with an average of 3.24 and 3 had relatively good environmental resilience, But most of the rural households in the sub-basins of Ghurechai and Lower of Gorganrud, Mohammad Abad-Zaringol, Madarsoo and Sarisoo, with an average of 2.89 to 1.85, had a poor environmental resilience. In addition, According to the flood risk resilience map, it can be said that of the total 31 sample villages studied, about 29 percent of sample villages have "medium upward" resilience in facing flood risks; conversely, most of these villages (71%) also have relatively low degree of resilience. Also, comparing the findings of this study with the results of most other researches, such as the studies of Olshansky and Kartes (1998) regarding the necessity of considering the environmental factors of settlements, observing the necessary environmental standards and the necessity of using proper land use management tools to reduce risk hazards and improve resilience, Center of Emergency Management Australia (2001) on the need to consider the state of the infrastructure, including the level of communications and accesses, biological conditions, including the status of pollution, as well as geographical characteristics, such as distances and proximity, climate, topography, as well as the general results of studies by Rafiean et al. (2012) in special selection of the most suitable model of resilience based on the combination of carter and socioeconomic model due to the simultaneous attention of this model to its geographical features and its comprehensiveness, as well as attention to the local communities' participation, Rezaei (2010), Shokri Firoozjah (2017) and Anabestani et al. (2017) Regarding the low value of the calculated population, the resiliency number of the society is consistent and consistent with the lack of attention to infrastructure issues, locations, etc., which is below the baseline (3). As a result, all of the aforementioned components of the resilience of inhabitants of sample societies have been affected by its environmental dimension, which is often due to insufficient attention and insufficient handling of them, which reduces resilience of rural residents to flood risks.
 
Keywords: Environmental hazards, Flood, Vulnerability, Resilience, Spatial analysis, Golestan Gorganrud basin.
 

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The geographical location of Yazd province has greatly influenced the creation of spatial and climatic diversity and the provision of appropriate facilities for the formation of various natural and cultural attractions. Nevertheless, these areas need more attention in terms of the potential of tourism development for social sustainability. This research is done with the aim of spatial analysis of tourism capacity of desert areas and its role in social sustainability, and according to its nature, it is an applied type. The research method is descriptive-analytic. Documentary and field data are used to collect data. The data were analyzed quantitatively (one-sample T-test, Pearson test and AHP and Barda methods). The findings show that according to the experts' opinion, the effective indicators in identifying tourism capacities are distance from roads, distance from historical attractions, distance from residential centers, distance from natural attractions, type and soil suitability, distance from water resources , Elevation, direction of gradient, slope, land use and precipitation. The results show that 24 percent of the total area of the area has relatively good capacity and is located in the central, eastern and northeastern parts of the province. The most important criteria that have made these areas selected as optimal areas are the density of natural-ecological elements such as the existence of diverse deserts and deserts, geotops, glacier cirques, and historical-cultural elements such as traditional water reservoirs, markets, shrines and temples And so on. Also, 26% of the area has average power, which is mostly located in the east and northeast of the province. Finally, areas with inappropriate and relatively inappropriate power are found in parts of the eastern province of Karshra that occupy 51% of the total area of the zone. The results of measuring the social sustainability status of desert and desert areas based on indicators (population distribution, transport infrastructure, immigration status and deprivation rate) show that Yazd city has the highest ranking and Ardakan, Bafgh, Mehriz , Taft Meybod and Abarkuhh moderate sustainability, and finally Khatam, Saduj and Bahabad are among the unstable and less developed cities of Yazd province. The results of Pearson correlation coefficient showed that there is a significant relationship between tourism development and social sustainability in different regions of Yazd province at 99% level. This means that areas with demographic, demographic, and low levels of social sustainability have lower attraction and tourism capabilities than other Yazd province cities.

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Zoning and Spatial Analysis of Potential Environmental Hazards
Case study: Silvana District
Abstract
Natural hazards can be considered as one of the most important threats to humankind and nature that can occur anywhere in the world. Natural hazards are one of the main obstacles to sustainable development in different countries and one of the important indicators of the development of world countries is their readiness to deal with natural hazards. Therefore, it is important to pay attention to it and appropriate measures should be taken to reduce the vulnerability of human settlements. Nowadays with increasing population growth, population dynamics and the large number of people exposed to various types of disasters, the need to identify environmental potential hazards and identification of hazardous areas are felt more and more. Meantime, some people may not be aware of potential hazards of their place of residence. So by identifying and evaluating potential hazards and their Risks before the occurrence, we can significantly reduce the severity of the damages and contribute to sustainable regional development. The negative effects of natural disasters can be minimized by the availability of comprehensive and useful information from different areas and Multihazard mapping is one of the most effective tools in this regard.
According to the above mentioned, in this study, the spatial analysis of potential hazards in Silvana district in Urmia County has been studied. This study area due to specific geographic conditions such as position, complexity of topographic and ecological structures, in general, the existence of environmental factors for hazards has been selected as the study area. There have been a number of hazards in the past and assessing of this area is necessary, because of the lack of previous studies. For this purpose, by reviewing various reports and doing field observations, three hazards including Flood, Landslide, and Earthquake are identified as potential hazards of the study area.
For assessing hazards, 12 factors in 6 clusters such as Slope, Aspect (Topographic factors), Lithology, Soil type, Distance to Faults (Geological factors) Precipitation (Climatological factors), River Network Density, Groundwater Resources (Hydrological factors), Land use, Distance to Roads (Human factors), Observed Landslide Density and Seismicity (Historical factors) as the research factors has been selected. For weighting factors, Analytic Network Process (ANP) Method in Super Decisions 2.6.0 software environment has been used. The results of the analysis show that Slope (0.201), Precipitation (0.161), Lithology (0.112), Distance to Faults (0.106), Land use (0.096), Rivers (0.078), Seismicity (0.06), Soil Type (0.055), Landslide Density (0.047), Aspect (0.033), Groundwater (0.03) and Distance to Roads (0.016), Respectively have maximum to minimum relative weight. Then, weighted maps are standardized with using FUZZY functions. For this purpose, Fuzzy membership functions such as Linear, Large and Small has been selected based on each factor. For some factors such as Slope, Aspect, Lithology, Soil type, Rivers density, Land use, Seismicity and Landslide density, Fuzzy linear function has been used. For some others such as Groundwater and Precipitation, Fuzzy large function has been used and for distance to Faults and distance to Roads, Fuzzy small function has been used. Finally, weighted maps were overlay in ArcGIS 10.4.1 environment with Fuzzy Gamma 0.9 operator and potential hazards zoning maps is obtained.
Final results indicate that major parts in the Northwest, West and South of the study area located in high risk zones and 59 percent of the total area exposed to high risk. Based on hazard zoning maps, 44 percent of the area exposed to Flooding, 48 percent exposed to Landslide and 44 percent exposed to Earthquake. Also, 61 percent of the population or 37394 people exposed to one hazard, 7 percent or 3817 people exposed to two hazard and 8 percent or 4914 people exposed to three hazard. According to surveys, only 21 percent of the study area is considered as a low risk area but that does not mean that environmental hazards will never happen in these areas. In general, and based on results, it is concluded that Silvana district has a high potential for environmental hazards. Final results of the research show that potential hazards identifying and preparation of hazard zoning maps can be very useful in reducing damages and achieving sustainable regional development. Therefore, considering the ability of hazard zoning maps to identify areas exposed to risk and assess the type of potential hazards, These analyzes should be considered as one of the most appropriate and useful tools in different stages of crisis management that can be the solution to many problems in preventing and responding to natural disasters and therefore, it is recommended that they be used in the crisis management process.
Keywords: Spatial Analysis, Environmental Hazards, Silvana, ANP Method, Risk
 

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Introduction
Geographical situation of Iran is a place for interacting many physical and human processes which lead to specific precipitation climatology in the country. The month to month variation of precipitation is one of  the features which the precipitation climatology may reflect due to tempo - spatial characteristics. In fact, monthly distribution of precipitation is one of precipitation normal features building up the climate structure. In order to recognize this fundamental characteristic three following questions have been raised:
1) Have the month to month distribution of precipitation changed over recent four decades?
2) How is the pattern of relationship of month to month distribution of precipitation and spatio - topographical variables?
3) Is it possible to find a spatial pattern for decadal changes of precipitation of month to month distribution?

Data and Methods
In order to find a responses for the abovementioned questions the distribution of month to month precipitation and its decadal changes was considered by adopting coefficients of variations (CV) for 46 years (1970-2016)  and using the third version of Asfazari dataset. The relationship of precipitation data and spatio-topographical variables calculated based on regression techniques. Moreover, the spatial pattern considered by using cluster analysis.  The CV calculated as follow:

here ،،  are ith raw's and jth column's CV, standard deviation, and monthly mean, respectively.
CV and its relationships with spatio-topographical variables were calculated in two temporal scale, for whole the under investigation period (1970-2016) and in decadal period for four decades (1977-1986, 1987-1996, 1997-2006, 2007-2016).
Discussion
 The results of current study proved that the month to month different in precipitation amounts have had spatial variations, whilst the temporal trends is not statistically significant. In addition, the minimum, maximum, and consequently, the range of values also the averages have not experienced significantly changes. However, the region experiencing the same values of precipitation illustrated oscillatory behavior. Accordingly, the decadal variations have happened in different areas. Although the there have been statistically significant relationships between monthly CV and spatio - topographical factors, the correlations were low. Based on cluster analysis, we found 5 regions according to CV and its anomalies in compares with normal CV for all under investigation period. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.
Results
Precipitation is known a chiastic and complicated climate element. One of chiastic behaviors which precipitation shows in its different time - scale behavior is its month to month distribution among a given year. In current research the decadal variation of  above-mentioned behavior among recent four decades and the variation of its relationships and the spatio - topographical features , as parts of climate structure of the country, have investigated in details. 
Our finding illustrated that the month to month different in precipitation amounts have had tempo - spatial variations, whilst the temporal long - term trends is not statistically significant. Moreover, the values of minimum, maximum, and consequently, the range of month to month CV also the decadal averages have not experienced significantly changes over four under study decades. However, the region experiencing the same values of precipitation depicted oscillatory behavior. consequently, the decadal variations have happened in different areas. Although there have been statistically significant relationships between monthly CV and spatio - topographical variables, the correlations were not considerably high. Based on cluster analysis technique, we found 5 regions according to CV and its anomalies in compares to normal CV for all under study decades. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.

KeyWords: Iran precipitation, Month to month changes in precipitation, Inter annual variation of precipitation, Precipitation anomaly, Spatial analysis of precipitation

 

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Dust fall means the dust that in the air fall down on the ground (Hai et al, 2008). it is important to study the extent of heavy metal contamination of dust fall due to their threats that could affect human health. Due to the fact that the metropolis of Tehran has a population of over eight million people and One of the major cities in the world is currently facing a severe air pollution problem. The purpose of the present study was to determine  the level of pollution and health risk of heavy metals such as Cd, Cr, Cu, Ni, Pb in the dust falling of Tehran city. the Dust fallout samples were collected using Marble Dust Collector (MDCO) from 28 different locations across Tehran during the statistical period (2018/03/21- 2018/06/21). We used XRF analysis To identify and determine the concentration of heavy metals (Cd,Cr,Cu,Ni,Pb,Fe) in the collected dust. we used to spatial analysis to  determine Dispersion of pollution levels and health risk in different Zone of Tehran  city. In order to determine the level of pollution and Health Risk Assessment we used the pollution index (PI), integrated pollution index (IPI), Non-Carcinogenic Risk and Carcinogenic Risk. Based on the results of the calculations performed in the statistical period studied, the values of pollution index (PI) and integrated pollution index (IPI) are Pb> Cd> Cu> Cr> Ni, respectively. Accordingly, the regional trend of pollution from west to east is increasing. Therefore, Tehran's pollution index is high level of pollution in the most zone and and extremely high level of pollution in the eastern zone, which is a more worrying situation. Probably one of the reasons is the western winds, which are faster in the west than in the east. Also, Tehran's topographic pattern plays a role in this issue. Health risk assessment (HQ, HI, CR) showed that the contamination of the heavy elements studied was lower than the acceptable threshold for carcinogenic and non-carcinogenic risks. Therefore, it is not dangerous in terms of carcinogenicity. The risk of carcinogenicity and non-carcinogenicity in children and adults is higher in the southern and eastern zone of Tehran. Probably one of the reasons is the establishment of metal industries, cement production, sand mines and combustion processes in the south and west of Tehran metropolis.

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The statistical and spatial analysis of extreme rainfall is considered as one of the components of the management tool to prevent or control the risks caused by this phenomenon. The purpose of this research is to statistically investigate and spatially analyze the extreme precipitations in the Kashan Plain.The extreme rainfall of Kashan synoptic station were statistically analyzed in the period of 1971-2022 AD and the water year of 1350-1351 to 1401-1400 for a total of 18618 days.Then six cases of widespread extreme rainfall were selected and analyzed with the rainfall data of 13 synoptic stations and 11 rain gauge stations using geostatistics and spatial analysis methods.The extreme rainfall zonation maps of Kashan plain were prepared using by variogram models and kriging method.The results showed that the frequency of heavy and super heavy rains in winter and very heavy rains in spring is more than other seasons.The very high correlation of annual rainfall with the total and frequency of extreme rainfall shows that the volume of annual rainfall is more affected by the concentration of rainfall in short periods of a few days than by the distribution of rainfall throughout the year.Therefore, it was found that extreme precipitation plays an important role in the total precipitation and surface runoff, and as a result, the water balance of the region.The zoning maps showed that the rainfall of April 8, 2020, which is concentrated on the western belt and the heights of the basin, causes the erosion of the heights and causes floods in the foothills and low-lying areas of the plain. Also, rains such as the rains of March 8, 2019, which are most concentrated in the central areas, have a high potential to cause flooding.

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Spatial analysis models provide a single model and solution to solve various problems in the field of study, one of the applications of these models is in measuring urban risks. In recent years, with the occurrence of various crises in urban communities, the urban management system and development plans are seeking access to models of prevention and dealing with these crises. The purpose of this research is to review the literature about the use of spatial analysis models in measuring urban risks in a meta-analytical way, so this research is conducted by reviewing and summarizing foreign articles (research statistical community) in relation to this issue in order to identify, analyze and Analyzing and summarizing the solutions of the investigated backgrounds.
The statistical population is discussed with four standard criteria of spatial analysis, including description and identification of hazard dispersion, hazard dispersion argument, interpolation, and spatial planning. The statistical population is research, studies, and articles indexed in Sciencdirect, Willey, Web of Science databases in the period 2021-2000. Out of 99 articles, 78 articles have been selected and analyzed by screening method according to research objectives and indicators. The analysis was performed in two ways: descriptive statistics in SPSS software and inferential statistics in CMA2 comprehensive meta-analysis software.
The results indicate that in the component of hazard dispersion descriptions, most of the researches in their used models have not been able to provide a tangible and appropriate general description, but in the three components of hazard dispersion, interpolation, and spatial planning of urban hazards based on score The average effect size, the applied models used in the research, have been able to provide a proper justification and tangible results with the applied model of spatial analysis in their studies.