Journal of Spatial Analysis

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Hot, humid weather causes to the sultry feel. Sultry condition is usually accompanied with loss of physical ability and human respiratory and it has an adverse effect on peoples who have circulatory or other heart problems and this feeling is more than others. Sultry feel is a feeling like any other sensitive reflections of mental state. And this state apparently can’t be measured by special instruments. With this description, there are a lot of efforts has been done to identify this phenomenon by meteorologists and climatologists. And a series of psychological climate tests show that we can examine the creation and incidence of this sense based on empirical studies as a scientific and objective attitude. Therefore, this study aims to classify the sultry days in the southern half of Iran based on sultry continuous hours. And the obtained results are presented as a form of zoning maps.

     The studied zone in this research is selected stations in the southern half of the country located in the province of Sistan & Baluchestan, Kerman, Hormozgan, Fars, Bushehr and Khuzestan. This area is located between two latitude 25 and 35 north and length of 47 to 63 east degrees. To achieve this goal, hourly partial pressure of water vapor of 13 selected stations were obtained for a period of 15 years (1995-2009) from Meteorological agency. After obtaining data and creating the database, to separate sultry conditions from non-sultry conditions, threshold of partial pressure of water vapor of Scharlou which was equivalent to 8.18 Hpa were used.

    Based on these data, the hours and days that the partial pressure of water vapor was equal or greater than 8.18 hpa will have sultry conditions and otherwise, they have non-sultry conditions. Then, based on this threshold, sultry days were divided into eight categories. The basis of this classification is that if in a particular day among eight branches of observation, one station, only in one observation record a pressure equal to or greater than 8.18 hpa was observed, it will be placed in first class and if only two observed records a value equal or greater than defined value, it will be placed in second catagory and finally, if all eight observations amounts equal to or greater than 8.18 had been recorded, it will be placed in eight class. After placing the sultry days in one of eight branches of classes, long-term averages of monthly, quarterly, quarterly and annual were calculated and mapped.

    Based on defined thresholds, sultry days were separated from non-sultry days, then sultry days were extracted and it was placed in first to eighth classes. The results of this classification showed that on monthly scale, January has the fewest sultry days in twelve months of the year. In this month, only two stations of Chabahar and Bandar Abbas had the sultry days of eighth classes. It means that 24 hours, they were in sultry conditions. Other stations that have a sultry day in this month, often their sultry days are from first to fourth classes and it means that they had maximum 3 to 12 hours of sultry conditions during the day. Most sultry days can be seen in two June and July months. So, in these two months, all studied stations have at least one sultry day,Specially  in three stations of Chabahar, Bandar Abbas and Bushehr. And all 61 days, they have sultry conditions. In terms of classification of sultry days, all 61 days of Chabarhar station are part of sultry days of eighth class. In two stations of Bandar Abbas and Bushehr, except few days that are from sixth and seventh classes, other days are from eightth class, other stations experienced one of the eightth classes of sultry days with different ratios. , and at the seasonal scale, winter has the lowest days of sultry and summer has the most days of sultry days. In term of classification of sultry days in seasonal scale, there are conditions as monthly scale. The interesting point in summer season is that sultry days on two stations of Zabul (35 days) and Iranshahr (51 days) are considered due to their Geographical locations. In Zabul station, the reason of these sultry days can be due to the neighborhood of this station with Hamoon Lake. But it should be mentioned about Iranshahr stationthat the reason of its sultry condition is entrance of monsoon low pressure and moisture transfer by the system on the south-east of Iran an especially Iranshahr. On an annual basis, it was also observed that always in south east of Iran (Especially Chabahar station), the number of sultry days is much more than south west of Iran, also occurring sultry days with eighth, seventh and sixth classes in this zone is so different from south-west of Iran. The reason of these differences in number of sultry days and sultry classes  related to the latitude of south east of Iran which is lower that south west and in other words, we can say that climate of south East of Iran is more similar to tropical climate than subtropical climate. 

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  Iran is a wide and great land that is located on Alps earthquake belt of Himalaya. Great part of the urban and village residency of the country have been exposed to the intensive earthquake and destructive. Sarab city with several other cities, including Tehran, Karaj, Abyek, Qazvin, Roudbar, Khalkhal ,Tabriz, Marand and khoy are located on Earthquake belt that Earthquake risk is too high.   In Eastern-Azerbaijan and Sarab, potential earthquake risk is very high, since there are a lot of active faults and historical evidences show the horrific and destructive earthquakes.   Sarab city located in the Sarab plain which have abundant faults in various directions. Earthquake as a natural phenomenon doesn’t have good results but what can make it a catastrophe, is the lack of prevention from its effects and no preparation for coping with its aftermaths.   The unsuitable establishment of structural elements and urban land-uses and atypical web of urban open spaces, the old ages of and low quality of the structures in the decayed area of the factors like this have main role in the increasing the amount of damage entered to the cities against to the earthquake.   It is necessary to reduce the vulnerability of the cities against the earthquake and to consider it as one of the main goals of the urban planning.   Main objective of this paper is planning for reduction of damages arising out of earthquake in Sarab city. The study area is the Sarab city with four urban regions and 15 districts. The present research is an applied study.   For this purpose, considering the goal of the study, nine factors including the type of structural materials, the quality of the buildings, the number of the floors, the population density, pedestrian width , the availability of open space and distance from river were identified and evaluated, so that for each of the indicators or factors, one layer of map with shp format was produced and then in an analytical hierarchy process and weighting to the variables, layers overlaying operation using available analytical functions was implemented in Arc Gis software. Finally the vulnerability map of the Sarab city was prepared. According to the results of AHP model, it is concluded that Sarab in terms of vulnerability has no appropriate status against earthquake risk so that the whole Sarab city is vulnerable to earthquake, but some of its neighborhoods due to low quality of buildings and vulnerability of streets network and inaccessibility to open areas and excessive compression are more vulnerable. Deteriorated urban area is one of the most vulnerable parts of the Sarab city during the occurrence of the earthquake. Therefore, to reduce the health and wealth damages which can cause by the earthquake in the city.  

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Environmental hazards are considered as one of the main obstacles for achieving sustainable human settlements development (particularly in rural areas). Today, with a new look at crisis management, using all managerial, organizational and planning accomplishments before the crisis, is an essential and rational concern. Rural settlements of the country along with cities always are threatened by a variety of environmental hazards, but what makes these spaces different from the cities is the high-intensity of vulnerability due to its physical decay texture. In this regard, one of the key elements in confronting the possible crisis that must be taken into account is the crisis management bases in which all prevention, preparedness and response measures, including disaster relief, temporary accommodation for the injured, etc. is provided and minimizes the consequences of potential crisis. Being located in the Kahrizak fault zone and the placement of hazardous industries in this region, is the main reason for selecting Kahrizak district as a study area in this research.    To achieve goals of constructing crisis management bases which indeed is the tactic ability of crisis management system (CMS), it is required to set the site selection criteria and standards for constructing them in such a way that provide more operational activities and develop the level of their impacts. In this regard, in the first step, the final criteria for site selection of crisis management base were selected after reviewing previous studies. Then, after surveying the experts and also the localization of criteria on the basis of area condition, seventeen final criteria were determined. For quantitative criteria, data were collected through organizations and reference centers and for a single qualitative criterion (cultural convergence), the questionnaire instrument used in gathering data. After collecting data using library and field methods, a combination of two models: fuzzy logic and hierarchical analysis process (AHP) applied for optimal location of crisis management base.    To determine the impact level of each criterion in the site selection process in two above-mentioned models, the standards for each of the seventeen criteria was determined with the help of combination method. The standards of some of the criteria determined using the standards in related organizations and some other standards proposed by experts and also through the localization by the researcher. Afterward, initially fuzzy standardized common scale maps produced from all information layers in a raster format. Then selected criteria by experts in the format of AHP model were compared with each other through pairwise comparison method. As a result of this comparison, the weight of criteria was determined which indicates the preference degree of each criterion over the others. At last, all standardized (fuzzified) layers multiplied in each of the final weight resulting from Analytical Hierarchy Model and in total converted into weighted fuzzy layers. In the next step, following the process of fuzzy model, fuzzy addition and multiplication operators were applied on output layers. Finally, to modify the layer resulting from fuzzy addition and multiplication, the Gamma operator was used. As such, after producing layers of different fuzzy gammas, essential assessment was conducted for selecting appropriate and ideal gamma. In order to do this, produced layers of each fuzzy gammas were compared with the study area for optimal location and the establishment of crisis management base. Since the gamma 0.9 had the most conformity to suitable zone in the layers of study area, it was selected as the appropriate gamma. However, to ensure the selected location, field study was conducted.     According to the research findings, the following conclusions were obtained: Site selection criteria for rural crisis management base not only has an environmental essence (built and natural), but socio –economic criteria are important as well Effective criteria for site selection of rural crisis management base, affected by regional and local requirements are not the same. Localization of criteria is a necessity that should be considered in site selection. Standards based on site selection criteria depending on the type of services, goals and location at multiple spatial levels (regional, local, urban and rural) is different: in the other words one size does not fit all Site selection is not only based on the location within overlaying information layers by using the models, but the final choice is done after field evaluation and visit.

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The best path to development is the primary focus on the potentials and threats of the environment and accordingly efficient use of the land. In this regard, it has a closely relation between agricultural and rural development and natural resources. The type of land use is a main factor in soil erosion and sediment production in the watersheds. In this research, it has been studied and evaluated the soil erosion in the Aleshtar plain catchment with aim of developing agricultural exploitation.

This study is based on PSIAC model. The PSIAC method has been designed based on the estimating of sediment potential with 9 important effective factors contains surface of the earth, soil type, weather conditions, runoff conditions,  topography,  land cover, Land use, current erosion condition, slope of river erosion and sediment transportation in the soil erosion. In the process of this research using geographical information system (GIS), the mentioned data analyzed, integrated, and finally layers of information were prepared. Followed by extraction of units, erosion zoning of the studied area has been implemented.

The total area of the studied area is 80305 hectares and is located in the northern parts of Lorestan province (southwest of Iran) and geomorphologic features are  almost mountainous and 39.65% of their area are mountains and hills. The maximum altitude is 3600 meters; the minimum is 1500 meters. and the average height of 2116 meters. Its climate type (based on De Marten method) is Mediterranean climatic pattern exists and  the average annual rainfall is 506 mm. The Aleshtar City is the only urban center in the area but there are 208 villages. The economy of the settlements is based on agriculture (farming, gardening and animal husbandry).

     Based on the findings of this research, 37.92% of the total land area of the basin is eroded (classes I, II, III). The land consists mainly of low slope and plain basin and is suitable for plantation (I). In this zone, 98 rural settlements (47.11%) are located. Relatively deep soils and flat are the features of these lands so the rate of erosion is low (II). 84 rural settlements (40.38%) are classified in this class. Shallow soils, these lands need to have conservation measures and can be managed under the operation of arable, rangeland, forest and resorts (III). 1 rural settlement (0.48%) is located in this class of erosion. 62.09% of the total basin land is located in the classes IV and V. A total of 25 rural settlements (12%) are located in this class. These lands under certain conditions can be planted; because erosion in the land is relatively high and the limitations in comparison with class III is more. Therefore they need more protection operations for exploitation. Also in these lands that are located in the high topography of the basin; erosion is extreme (Class V), which makes arable exploitation impossible.

    Generally the land use in Aleshtar basin is faced to erosion limitation, so the control of the soil erosion and soil conservation and water resources management are essential. However, the locations of the most rural settlements were based on low to moderate erosion zones which indicates that the ancient has had a traditional preparatory thinking.

    As a general recommendation, it can be said that in any location, including rural and urban settlements, along with the development of agricultural activities, attention to the erosion and zoning is essential.

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The term "Game GIS” implies to real spatially enabled games in which a special part of the world is virtually simulated, represented and managed. In fact, game GIS is an integrated system consists of video games and geographical information systems, aimed to simulate and representing spatially enabled environment. The achieved result of implementing a game GIS service can be exploited before a crisis for wise designing of a city and diminution of the aftermath casualties. As the decision making process plays the key role to reduce the losses, the need arises for using the models as much as close to the reality. By this, it is possible to use the virtual world in in the form of a game rather than experiencing the real world with real wounded and killed persons in. This enables us to recognize and manage a test environment for promoting the managing the real environment of a city during and before a natural hazard disaster like an earthquake. The game GIS may be counted as a service for sharing and dissemination of spatial information as well as online GIS to have a visual and synoptic management of the earth plant facing various disasters. The current research is aimed to design and implement a software architecture for an earthquake game in Tabriz city (Iran).

The study area is district 10 of Tabriz located within a fault zone. According to field surveys, 82.1 percent of buildings in the study area may be vulnerable against earthquake in terms of the quality of building construction.

Methodology of the research to design, program and implement the game GIS service are undertaken as the following processes: data collection, database creation and software production.

The collected data includes master plan maps of the district 10, building quality, number of floors, building façade materials, age of building, street network (adopted from the master plan of Tabriz) and population of each parcel.  Also, some regions are assumed as hospital, relief-rescue center and treasury money.

To design the software, 2D environment of MapControl and for implementing the game into the 2D environment, ArcEngine of ArcGIS have been exploited. The mentioned engine gives us possibility to use of analysis and modelling capabilities as much as closer to the ground reality which are compatible with available geometry of the terrain (Amirian, 2013, 17-19). The MapControl is a framework in which the map and game area are displayed. Symbology is used to show the persons as well as equipments. Briefly, the stages undertaken during the current research can be explained as the following:

• Data collection based on available sources via field surveying.
• Data processing and creating a database from street networks and building owned the age, materials, floors fields.
• Calculation of vulnerability rate for each building separately as well as the amount of deconstruction damage per Richter.
• Drawing the street and alley network to prepare network analysis dataset.
• Preparing special network analysis database and evaluation in various situations.
• Using the gained layers and implementation of the scenario.

After that, the conceptual architecture of the software has been designed based on the scenario.

The game GIS services has been designed with 6 different classes offer numerous functionalities responsible for displaying program commands and different views of the game. Finally, the service is designed and implemented in a real schema for crisis management application. The resulted game is played in 4 stages. In the first stage, the player starts with a 5 Richter magnitude earthquake and ends while the player gets to 8 Richter. The designed software simulates the destruction rate of buildings based on the influential factors, wounded transfer routing and rescue operation. The game player gains credit according to his quickness and agility. The player would go to the next stage with one Richter magnitude higher, if gains enough credits during each stage. The result of the current research as a Game GIS service, can be used in earthquake simulation happens in various magnitudes for management of decreasing the effects of earthquake, quick reaction, maneuver and education. Considering the achieved results, designing and performing the game GIS service over the web based on open source technologies rather than being desktop and commercial service, can be suggested as a new research frontier for the future researchers.

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Most of the large cities in developing countries have faced with the problem of informal settlements. The formation and growth of these settlements for reasons such as rapid and outside the customs building construction are the threatening issue for their communities. Informal settlements are areas that often shaped and expanded in major and middle cities of the Iran’s cities including the city of Parsabad. During the last decades, the rapid growth of urbanization and the lack of appropriate planning for low-income families housing leads to the formation of the urban informal settlements in most cities of the Iran. In most cases, these settlements have a structural and demographic dense texture. The structural texture of these settlements is often fine aggregate, impermeable, and unstable. In times of crisis, the possibilities of human and material losses to them are high.

Environmental hazards such as earthquakes are a serious threat to these settlements. However, these hazards in most developing countries, due to the unavailability and lack of preventive actions, end to the crisis. We cannot prevent earthquakes. But we can reduce the losses and damages caused by the earthquakes. Remove of the disaster is impossible, but it is possible to reduce the damage caused by the disaster. One of the most important ways to reduce the risk of earthquakes is preparation to deal with earthquakes. Preparation means having previous programs and plans.

     Iran is one of the countries where earthquakes always happen. Because Iran located in the world's earthquake belt, each year on average about 1,000 earthquakes happening in Iran. Ardebil and Pars-Abad city, located in an area that the possibility of earthquakes shakings in these areas, is more. The Zire Nahre Torab Neighborhood is one of the Parsabad city’s informal settlements that located in the northwest of the city. Regarding the possibility of an earthquake in the city of Pars Abad, identification and assessment the vulnerability of the neighborhood during an earthquake, is essential. Therefore, identifying and assessing the vulnerability, especially in the poor neighborhoods to offer strategies for dealing with the injuries, is essential. The aim of this study is assessing vulnerability of the informal settlements during an earthquake by using spatial data and GIS. This study, have been prepared in fifth main parts including: introduction and background, methodology and presentation of case study, theoretical framework, analysis and conclusions.  

This research in terms of the nature is practical and is descriptive and in terms of the method is analytical. Three methods including library, documentary and survey have been used for data collection. In the first phase, data and base maps were extracted from documents and reports of projects such as city comprehensive and detailed plans. Also, in this phase of the study data were updated. In the second phase, the problem, questions and research objectives were defined. In the third phase, the 3 criteria and 12 sub-criteria based on research literature and according to available data were selected. In the fourth phase, after preparation of databases related to each of the criteria in GIS, input layers were prepared for each of them. In the fifth step, the method of network analysis process (ANP) was used to determine the significance of criteria. In the sixth phase, the weighted overlay index (WOI) was used for combining output layers.

The results of this study show that more than 80% of neighborhood buildings are vulnerable against the risk of a possible earthquake. Also, research findings suggest that physical characteristics such as building structure, quality and age of the buildings will have the greatest role in determining the neighborhood buildings vulnerability level. Doing activities such as resisting buildings, improving roads, locating facilities in appropriate places, training and informing citizens to prevent a crisis caused by the possible earthquakes, is essential. Other recommendations are listed in below:

1. Identifying vulnerable buildings
2. The use of GIS in the management of settlements
3. Preparations cities, to deal with urban hazards
4. Empowering citizens to deal with environmental hazards
5. Action to reduce earthquake risk
6. Civil engineering Renovation of buildings
7. New practices in the urban construction
8. Equip cities with facilities and relief supplies.
9. The use of specialists in urban planning.
10. Conducting workshops on urban resilience.

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One of the geomorphologic issues that many human activities affect is the landslides. Natural factors and human activities on the other hand, these events are triggered. Landslide one of the most active hazards are natural processes that lead to erosion and changes in the landscape. Iran is a predominantly mountainous topography, seismic activity and high landslide, diverse climatic and geological conditions of natural conditions for a wide range of slip is important. Located in second place in the sector of industry, population of 1695094 people, proximity to major faults of Tabriz and occurrence Landslides of different city of Tabriz, the city has become one of the most dangerous cities in the environmental hazards, especially landslide. In these circumstances and completed a comprehensive review and a detailed zoning of land for landslide susceptibility seems absolutely necessary. The purpose of the present paper, the occurrence of landslide susceptibility assessment and mapping potential occurrence of landslides in the city of Tabriz in this range.

     This research of the type applied- development research and of the research method is descriptive - analytic. In this study, using a variety of sources including satellite imagery, aerial photography, global positioning system (GPS) and field studies landslide occurred in the study area were identified and these data were analyzed using the software ILWIS and use of library studies and expert opinions should identify the criteria and sub-criteria and range were classified. Then, using fuzzy TOPSIS model, the importance of the criteria and sub-criteria specified in pixel units and finally combining fuzzy-TOPSIS model and overlapping functions in ARC / GIS final map was extracted.

Geomorphologic and lithology conditions of the city with its mountainous location where the trigger landslides. The final results indicate that over 30% of the areas of the city of Tabriz are medium to high risk that this areas of land in the north and northeast is sparse. The accuracy of the final map and the map of the distribution of faults and the accuracy of the study proved to be that hazardous zones roughly corresponding to the final map lapses occurred. So we can conclude that the method and the model presented in this paper is an effective method for landslide hazard zonation within the cities.

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In Iran, there is a general risk of runoff and flood, and since this country has a dry to semi-arid climate, its predominant rainfall is not evenly distributed in terms of time and place. Routine runoff at the earth's surface can lead to risks such as groundwater abatement, social issues such as population migration, erosion and loss of soil fertility, sedimentation in reservoirs and water quality in rivers. Also, damage to the agricultural sector, subsidence, the destruction of residential buildings and the reconciliation of the urban, rural and nomadic order are all examples of controversy about the risks that runoff and flooding are due to. The severity of these hazards in the Afje watershed is due to the geographical location, the specific climate, geology and pond factors, and a large volume of flooding every year causes the destruction of residential areas, agricultural lands and many financial and financial losses.                            
In this research, data collection was carried out through library and field resources. The main tools of this research were topographic map of 1: 25000 which was used by GIS software for the separation of layers and determining the boundaries of the basin; Land use maps and user data and hydrologic groups of the study area were also used to estimate runoff height using curve number method and Arc-CN Runoff instrument. Then Arc-CN Runoff tool was used to prepare layers and curve number map (CN). Finally, the runoff height of the studied basin was prepared in the GIS software.
Soil Hydrology Group: According to the studies, in terms of breadth and extent, the Hydrologic Groups C has the largest area with relatively high runoff potential. By matching the map of Hydrologic Soil Groups and the mineralogical units of the basin it can be stated that the green mass tuff and thick conglomerates are in the hydrologic group D, and the thick layers of green tuff, marl and sandstone in the hydrologic group C and the rocky layer of limestone in The hydrological group B is located.
Land use: The hydrological status of the land and types of uses in the Afje watershed basin are as follows. Most of the catchment area is covered by medium-sized meadows, which comprises 53.77% of the basin area and is located in the hydrological group C with relatively high potential of runoff production. The rock outcrops are in the next rank, which is in the hydrological group D.
Runoff curve number (CN): Land use maps and soil hydrologic groups were combined and extracted for each curve number range (CN) and CN map was prepared. The Afjeh basin has a curtain number of 66 to 100. The highest value of the curve number is 100, which is related to the outflow of the Afjeh watershed basin, which is practically inert, so all precipitation becomes runoff. The Afjeh basin has a curtain number of 66 to 100. The highest value of the curve number is 100, which is related to the outflow of the Afjeh watershed basin, which is practically Impervious, so all precipitation becomes a runoff. In fact, the curve number 100 in stone is 5.59 square kilometers from the area of the Afjeh watershed. But gardens and Agricultural land have the lowest CN (curve numbers 66 to 77) in the Afjeh basin, and include 4.53 square kilometers of basin area. Therefore, the lower parts have a lower CN than the upstream of basin.               
The runoff height in the four seasons was calculated based on the daily precipitation values occurring at mentioned times.
Based on the average daily rainfall of spring with a value of 10.79 mm and runoff classification, in a small part of the gardens in catchment area due to high permeability of the soil, 2.54 mm of precipitation has become runoff, although it is due to stone due to The Impervious of the surface, 10.66 mm of precipitation, turned into runoff.
According to the studies carried out and according to the potential maps of runoff production in the Afje watershed, in the garden with the value of the curve number 66 and daily precipitation (for example, in the winter with a rainfall of 4.04 mm), the runoff height is 0.76 mm And the peak of discharge of 0.47 cubic meters per second And has the lowest runoff potential. In winter, the upstream sediments of the basin with curve number 100, runoff height of 3.81 mm and peak of discharge of 2.65 cubic meters per second and almost all rainfall becomes runoff. Therefore, the shortage of water resources, the presence of dry and semi-arid climates in the country and the achievement of sustainable development leads to the optimal use of water resources.
 
keywords: hazard, Arc- CN Runoff, GIS, high runoff, catchment Afjeh
 

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     Environment, development and sustainability are the three significant issues of worldwide concern. Environmental vulnerability and assessment of natural and anthropogenic activities impacts represent a comprehensive evaluation approach. The main purpose of this study is to present a comprehensive and novel framework in order to environmental vulnerability assessment using by spatial data and techniques. The method of this research is analytical-descriptive. The basic premise is that the finding of this study can be applied in the local planning system and policy making process of environmental conservation particularly to cope with rapid environmental change. The environmental vulnerability is defined and governed by four factors: hydro-meteorology signatures, environmental attributes, human activities and natural hazard. Based on data availability and vulnerability status of different areas, there is no general rule for selecting how many variables are required to assess the environmental vulnerability. In this study, 18 variables were taken into account and organized into four aforementioned groups.  The process of environmental vulnerability index is proposed to integrate AHP approach, remote sensing indices and GIS techniques. The environmental vulnerability showed distinct spatial distribution in the study area. Furthermore, the distribution of heavy and very heavy vulnerability patterns mainly occur in low and medium lands where the human activities have been developing rapidly and is the nearest region to Urmia lake in the west region.

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Developing urbanization and changing hydrological conditions of natural streams increases the flooding risk. This study tries to do flood hazard zoning in the Ilam city and determine the critical area of the urban regions against flooding by using AHP method and GIS environment. For this purpose, the parameters of the curve number, height, distance from the river, geology, land use, population, slope, soil, building density, worn texture buildings and accumulated flow as effective parameters in flooding hazard in Ilam city selected and of these parameters weighted by using Expert Choice software. The result of the Expert Choice software is transferred to the environment of GIS software and flood hazard map of study area prepared. Results of the study and flood hazard map show that areas with very low-risk, low risk, intermediate-risk, high-risk and very high-risk form the 0.8%, 8.5%, 49.6%, 32.54% and 8.56% of the of Ilam city area, respectively. Also, the central area of the city has the highest risk and the probability of occurrence of the flood due to the high density of population and residential areas in this area and its proximity to the seasonal rivers and old part of the city. Therefore, by examining the results of Expert Choice software, it is possible to identify the most effective factors in the occurrence of flood risk and prioritize them to address management solutions to eliminate or mitigate the effects of these factors.

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ite selection for Temporary Earthquake Shelter Compounds, Using Analytic Hierarchy Process and Weighted Linear Combination based on GIS; Case Study: Shahrood
 
Abstract
Natural disasters are unpredictable and unavoidable and their occurrence in human settlements has led to catastrophes in many cases. Therefore, it is necessary to prepare prior the occurrence of these events. A prompt response can be a solution to this goal. As long as assurance is provided to the affected population that there is no lack of assistance and facilities, their ability to return to pre-disaster conditions and recovery will be increased. Selecting the right accommodation according to the needs of people after natural disasters, as well as planning to meet the needs of the victims, not only reduces risks and expedites recovery operations during reconstruction, but also strengthens the protection structures and advances the safety aspects of communities prior to any kind of incident. Increasing concerns arising from high occurrence of natural disasters, especially earthquakes, and witnessing the unpleasant consequences, will emphasize the need for proper habitation conditions and facility provision. Iran is a country that is prone to disasters. In fact, no country in the world is immune to natural disasters. In this research, urban areas of Shahrood located in Semnan Province, have been studied with regard to seismic potential and proximity to the southeastern part of Alborz Mountain and Shahrood’s faults as a sample for selecting appropriate post-earthquake shelters. The overall purpose of this research is to propose a decision making process for efficient and safe spatial planning in the wake of crises. In the first step, the structural vulnerability of buildings in terms of foundation quality and their vulnerability measures is estimated at 24% of the city, which is equivalent to 12778 buildings prone to destruction, even facing a mild earthquake. After analyzing the possible damage to the city, according to the average household size of 3.43 people in Shahrood, 43829 people are estimated to be homeless. The amount of space needed to accommodate these people, with an estimated per capita of 30-45 square meters per person, was estimated at 132 to 198 hectares, which could be used in a few distinct and scattered spaces. After determining the area needed for settlement, the criteria influencing the location of temporary shelters were identified based on scientific literature and analysis of previous experiences. According to these studies, the criteria for influencing this concept are classified into nine groups including access, location, cultural, economic, compatible and incompatible neighbors, infrastructure conditions, land quality as well as space area. The subsets of these nine criteria can be categorized into two groups: constraint factors and classification possibilities. Factors such as distances from faults, high voltage electric power lines, vulnerable zones, gas stations and chemical storage facilities are known to cause limitations. The concept of the facility in this research, in addition to proximity to residential areas, main roads and storage depots, includes access to compatible applications, medical centers, security centers, fire departments and outdoor spaces; hence it is necessary to accommodate people at the minimal distance from these facilities. Parameters such as area, surface water, infrastructures and available energy sources are some of the criteria that need to be measured in terms of their quality in proposed options and decisions are to be made on the basis of their existence and accuracy. Since each parameter has a different effect on the location of temporary accommodation therefore, the list of priorities is sorted accordingly. In this article, a methodology for locating shelter after an earthquake has been recommended by using hierarchical analysis, weighted linear combination and GIS. In this multi-criteria decision-making process, the weighting process was performed on each parameter by paired questionnaires that were provided to 40 experts, and analyzed according to the principle of hierarchy (AHP) and arranged in Expert Choice software. Then, all of the data layers in GIS software were combined with WLC method according to the criteria and standardization. The Geographic Information System (GIS) has been used as one of the most useful tools in allocation and land use planning. To analyze the data in the software, after converting the data into the Raster structure and classifying the layers in appropriate categories and in accordance with the functional radius, a conclusion was made in the Arc GIS environment. The output, obtained by overlapping the collected items, is a list of land plots suitable for post-disaster shelters, sorted according to the aforementioned priorities.
 
Keywords: site selection, temporary sheltering, AHP, WLC, GIS
 
 

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Landslide susceptibility mapping is  essential for  land use  planning and decision-making especially in  the mountainous areas. The main objective of this  study is to produce landslide susceptibility maps (LSM) at Dalahoo basin, Iran  using two statistical models such as an  index of entropy and Logistic Regression and to compare the  obtained results. At the  first stage, landslide locations identified by Natural Resources Department of Kermanshah Province is used to prepare of LSM map. Of the 29 lanslides identified, 21 (≈ 70%) locations were used for the landslide susceptibility maps, while the remaining 8 (≈ 30%) cases were used for the model validation. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, distance to faults, distance to rivers, distance to roads, land use, and  lithology  were extracted from the spatial database. Using these factors,  landslide susceptibility and weights of each factor were analyzed by index of entropy and Logistic Regression models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and  the areas under the curve (AUC) were calculated. The verification results showed that the index of entropy model (AUC = 86.08%) performed slightly better than conditional probability (AUC = 80. 13%) model. The produced susceptibility maps can be useful for general land use  planning in the Dalahoo basin, Iran.

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Identifying spatial patterns in vulnerability involves a comprehensive look at vulnerable points. And provides analytical power to the authorities. Therefore, it is necessary to recognize patterns of vulnerability so as to minimize the amount of damage to them in the event of a crisis. The city of Tehran, as the political and administrative center of the country, is faced with a variety of risks due to demographic burden and physical development. In this research, we tried to analyze the spatial distribution pattern of urban vulnerability to natural hazards in social and physical dimensions in Tehran's 7th region. The method of this descriptive-analytic study and the model used for trigonometric fuzzy logic. The results indicate that: According to the z score, the positive values are 1.96 up, which form the clusters of hot spots in the southeastern region of the arena; It is a sign of more vulnerability in these areas. Also, negative values of 1.96 and less, which are statistically significant and blue, have formed cold spots, And it is interpreted that low vulnerability zones are clustered in space and are mainly located in the northwest. Therefore, the lower the color range in the red and blue areas was less statistically significant  to the point where this positive net worth is 1.65 that in this situation, the spatial behavior of the vulnerability is considered to be non-significant in terms of hot or cold clusters with high and low values and spatial autocorrelation that the map is also displayed in yellow.
 

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Flood susceptibility mapping using frequency ratio and weight of evidence technique: a case study of Kermanshah Province
 
abstract
Flood is considered as one of the most destructive natural disasters worldwide, because of claiming a large number of lives and incurring extensive damage to the property, disrupting social fabric, paralyzing transportation systems, and threatening natural ecosystems. Flood is one of the most devastating natural disasters causing massive damages to natural and man-made features Flood is a major threet to human life (injure or death of man and animal life), properties (agricultural area, yield production, building and homes) and infrastructures (bridges, roads, railways, urban infrastructures). The damage thet can occur due to such disaster leads to huge economic loss and bring pathogens into urban environments thet causes microbial development and diseases Therefore, the assessment and regionalization of flood disaster risks are becoming increasingly important and urgent. Although it is a very difficult task to prevent floods, we can predict and compensate for the disaster. To predict the probability of a flood, an essential step is to map flood susceptibility.
The methodology of the current research is includes the following steps:
Flood inventory mapping;
Determination of flood-conditioning factors;
Modeling flood susceptibility and its validations.
 Et first , 146 flood locations were identified in the study area. Of these, 102 (70%) points were randomly selected as training data and the remaining 44 points (30%) cases were used for the validation purposes. In the next step 1 flood-conditioning factors were prepared including geology, landuse , distance from river , soil , slope angle, plan curvature, topographic wetness index, Drainage density elevation, rainfall. Then, the probability of the flood occurring for each class of parameters was calculated. Et the end, the obtained weights for each class in the Geographical Information System (GIS) were applied to the corresponding layer and flood risk map of th studied region was prepared. Subsequently, the receiver operating characteristic (ROC) curves were drawn for produced flood susceptibility maps.
To determine the level of correlation between flood locations and conditioning factors, the FR
method was used. The results of spatial relationship between the flood location and the conditioning factors using FR model is shown in Table 2. In general, the FR value of 1 indicates
an average correlation between flood locations and effective factors. If the FR value would be larger than 1, there is a high correlation, and a lower correlation equals to the FR value lower than 1.
The analysis of FR for the relationship between flood location and lithology units indicates thet Cenozoic group has the highest FR value. In the case of land-use, it can be seen thet the residential areas and agriculture land-use have values. One of the most important factors affecting the flood is distance from the river. The results showed thet the class of >500 m FR was the most effective one. The analysis of FR for the relationship between flood location and slope angle indicate thet class 0-6. 1 has the highest FR value. In the case of slope aspect, flood event is most abundant on flet and East facing slopes According to the analysis of FR for the relationship between flood location and plan curvature, flet shape has the highest FR value., A flet shape retains surface run-off for a longer period especially during heavy rainfall . Flood locations are concentrated in areas with a TWI >6. 8 drainage density > 4. 6 km/km2 and altitude classes of 1200 m. In the soil layer, the tallest weight is from the earth with a small transformation of gravel. Finally, the maximum weight is the maximum rainfall.
In this study, all parameters of WofE model were calculated for each conditioning factor. In the lithology unit, the Cenozoic class has the highest flood susceptibility. Among the different land-use types, agriculture categories had the highest values . The distance from the river from 0 to 1000 m indicated positive influence in flooding, while the areas more than 1000 m or far from the river represented the negative correlation with flood occurrence. In the soil layer, clayey soil and tuberous soil had the highest weight. The analysis of WofE for the relationship between flood occurrence and slope angle indicated thet slope angle from 0 to 6. 21 had positive influences in flooding. In the case of slope aspect and plan curvature, flet area had a strong positive correlation with flood occurrence. Effectiveness increases wit increasing TWI classes. The results of drainage density indicate thet areas with higher drainage densities are more susceptible to flood occurrence. By increasing the height of the flooding reduced sensitivity classes. byn flooding rainfall and flood events increased with increasing rainfall.
 
The prediction accuracy and quality of the development model were examined using the area under the curve (AUC). Specifically, the receiver operating characteristic (ROC) curve was used to examine the basis of the assessment is true and false positive rates . So the results showed thet based on the area under the curve, the FR and WofE models show similar results and can be used as a simple tool for verifying the map prepared for flood sensitivity and reducing its future risks.
Floods are the most damaging catastrophic phenomena in the worldwide. Therefore, flood susceptibility mapping is necessary for integrated watershed management in order to have sustainable development. In this study, flood susceptibility zones have been identified using FR and WofE methods. Et first step, a flood inventory map containing 146 flood locations was prepared in the kermanshah Province using documentary sources of Iranian Water Resources Department and field surveys. Then, eleven data layers (lithology, landuse, distance from rivers, soil texture, slope angle, slope aspect, plan curvature, topographic wetness index, drainage density, and altitude) were derived from the spatial database. Using the mentioned conditioning factors, flood susceptibility maps were produced from map index calculated using FR and WofE models, and the results were plotted in ArcGIS. Finally, the AUC-ROC curves using validation dataset were prepared for the two models to test their accuracy. For this reason, of 146 identified flood locations, 102 (70%) cases were used as training data and the remaining 44(30%) was used for validation. The validation of results indicated thet the FR and WofE models had almost similar and reasonable results in the study area. Based on the overall assessments, the proposed approaches in this study were concluded as objective and applicable. The scientific information derived from the present study can assist governments, planners, and engineers to perform proper actions in order to prevent and mitigate the flood occurrence in the future.
 
Key words: Flood susceptibility mapping, validation, method of frequency, weight of evidence, GIS- Kermanshah
 
 

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Determining Effective Factors on Forest Fire Using the Compound of Multivariate Adaptive Regression Spline and Genetic Algorithm, a Case Study: Golestan, Iran   
Pahlavani, P., Assistant professor at School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran
Raei, A., PhD Candidate of GIS at School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran
Bigdeli, B., Assistant professor at School of Civil Engineering, Shahrood University of Technology
 
Keywords: Forest Fire, Multivariate adaptive regression spline, Multiple linear regression, Logistic regression, Genetic Algorithm.
 

1. Introduction

Nowadays, Determining the effective factors on fire is so important, because the plenty areas of forests around the world are destroyed annually by fire and recurrence of that in the long term can irreparably damage to the earth and its inhabitants. It helps us to identify most dangerous locations and times in forest fire. Hence, we can prevent many of driving factors of forest fire by law enforcement, efficient forest management policies and more supervision. In the current study, we identified the effective factors on the fire in Golestan forest through integration of three different methods including multiple linear regression, logistic regression and multivariate adaptive regression spline with Genetic Algorithm.

2. Study Area

Golestan Province is in the North of Iran and 18% of it is covered by forests. Golestan Province is a touristic province and several roads pass through its forests and according to statistical records, most of the occurred fires were in proximity of these roads. Our study area is located in 36°53′-37°25′N and 55°5′- 55°50′E and its area is about 3719.5 km2. We selected this area, because includes the most of fires have been occurred in Golestan Province in recent years.

3. Materials and Methods

A big fire was occurred on 12 December, 2010 in our study area and we used it as the dependent variable. The actual burnt area and some other data, such as Digital Elevation Model (DEM), the roads network, the rivers, the land uses, and soil types in the area were provided from Golestan Province Department of Natural Resources. Also, geographic coordination of the synoptic weather stations near the area and their data, including maximum, minimum, and mean temperature; total rainfall, as well as maximum wind speed and azimuth in December 2010 were obtained from National Meteorological Organization of Iran.
The land use and soil layers were in scale of 1:100000 and the roads and the rivers layers were in 1:5000 and all of them were provided in 2006. The region DEM is generated from topographic maps of Iran National Cartographic Center in scale of 1:25000 with positional resolution of 30m and we produced the slope and the aspect layers from it in ArcGIS software with the same resolution. The roads and the rivers were in vector format, hence, we used the Euclidean Distance analysis to generate rasters that each cell of them shows the distance from the nearest road or river.
At first we had 5 weather stations, which is very few for GWR. In this regard, we generated 1000 random points in the area and interpolated data to these points using Ordinary Kriging method with exponential semivariogram model in 30m resolution in ArcGIS software.
The multiple linear regression (MLR) model is the generalization of simple linear regression that is modeling the linear relation between one dependent variable and some independent variables. The general formula of MLR is seen below:
                                                                                                                                    (1)
The unknown coefficients are obtained using least squares adjustment as follows:
                                                                                                                                                      (2)
The logistic regression (LR) model is a nonlinear model for determination of the relation between a binary dependent variable and some independent variables. If we use the values of 0 and 1 for non-fire and fire points respectively, then the probability that a point be a fire point is obtained by Eq. (3):
                                                                                            (3)
If the number of parameters is insignificant compared to the observations, then we use the unconditional maximum likelihood estimation shown by Eq. (4) to compute the unknown coefficients of this model.
                                                                                                                                (4)
The multivariate adaptive regression spline (MARS) model is a flexible non-parametric model that requires no assumption about the relation between the dependent and independent variables. Hence it has a high ability in determination of complex nonlinear relations among the variables. The general formula of MARS is seen below:
                                                                                                             (5)
 is the m’th basic function that is obtained by Eq. (6):
                                                                                                  (6)
These basic functions are chosen in such a way that leads to minimum RMSE of model.
We use the genetic algorithem (GA) with the fitness function of the normalized RMSE to select the optimum combination of effective factors on forest fire.
 

4. Results and Discussion

In this paper we study the dependence of the forest fire to 14 factors shown in table 1, in the study area. Our results are shown in figures 1 to 3.
 
Table 1. The studied factors in the present research

Factor	Num.	Factor	Num.	Factor	Num.
Aspect	11	Maximum Wind Speed (m/s)	6	Maximum Temperature (℃)	1
Slope	12	Soil Type	7	Minimum Temperature (℃)	2
Elevation (m)	13	Land Use	8	Mean Temperature (℃)	3
Distance from The Residential Zones (m)	14	Distance from The Roads (m)	9	Total Rainfall (mm)	4
		Distance from The Rivers (m)	10	Maximum Wind Azimuth	5

 
 
  
Figure 1. (a) The best and the mean values of fitness, (b) The last best individuals, (c) The average distance between individuals, (d) The fitness of each individual in the last generation using MLR
 
Figure 2. (a) The best and the mean values of fitness, (b) The last best individuals, (c) The average distance between individuals, (d) The fitness of each individual in the last generation using LR
 

Figure 3. (a) The best and the mean values of fitness, (b) The last best individuals, (c) The average distance between individuals, (d) The fitness of each individual in the last generation using MARS

5. Conclusion

This research shows that both of the biophysical and anthropogenic factors have significant effects on forest fire in our study area. Just two factors were identified as impressive factors in all three cases including the minimum temperature and the maximum speed of wind. This study concluded to the NRMSE=0.4291 and R2=0.9862 for the multiple linear regression, NRMSE=0.9416 and R2=0.9912 for the logistic regression and NRMSE=0.1757 and R2=0.9886 for the multivariate adaptive regression spline and totally the multivariate adaptive regression spline method showed a better performance in comparison to the other two methods.
 

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Study the Effects of Covid-19 on Air Pollutants by Using Sentinel-5 Satellite Images (Case Study: Metropolises of Tehran, Isfahan, and Mashhad)

Zeinab shogrkhodaei, PHD. Student of Climatology, Faculty of Literature and Humanities, Department of Geography, Razi University
Amanollah Fathnia*, Assistant Professor of Climatology, Faculty of Literature and Humanities, Department of Geography, Razi University
Vahid Razavi Termeh, PHD. Student of GIS, Faculty of Geodesy and Geomantic, K. N. Toosi University.

Introduction
One of the challenges facing the international community right now is Covid-19. This pandemic has caused a comprehensive change in behavior contrary to the usual routine, which can lead to changes in people's lifestyles (Briz-Redón et al., 2021). The prevalence of this disease has not only affected the economy and health, but also the environment (Sohrabi et al., 2020). Among the effects of Covid-19 on the environment are the effects on beaches, noise, surface and groundwater, municipal solid waste, and air quality (Zambrano-Monserrate et al., 2020). The restrictions applied during the Covid-19 era were accompanied by a reduction in greenhouse gas emissions by transport and industry, which affected air quality (Rybarczyk and Zalakeviciute, 2020). Air is a vital element for the survival of all living things, but human activities have caused the release of many harmful pollutants into the atmosphere and endangered human health (Ghorani-Azam et al., 2016). Among the causes of death, air pollution is the fourth leading cause of death in the world after tobacco (WHO, 2020a). Sulfur dioxide, nitrogen oxide, carbon monoxide, and ozone are some of the pollutants that cause short-term or long-term exposure to heart and lung disease (Briz-Redón et al., 2021). Human activities are one of the main sources of air pollutants, so their concentration is expected to decrease during the Covid-19 period (Ghahremanloo et al., 2021).
Materials and methods
In this study, the required data were the average monthly pollutants of sulfur dioxide, nitrogen dioxide, carbon monoxide and ozone before (20 February 2019 to 20 February 2020) and after (20 February 2020 to 20 February 2021) the prevalence of Covid-19 virus. For this purpose, Sentinel-5P satellite images were used to prepare the required data set. The case study included three metropolises of Tehran, Mashhad, and Isfahan. Google Earth Engine was used to access Sentinel-5P satellite images. The final output of the images for each pollutant was interpolated for better display and exposure in GIS software using the kriging method. Then, a T-test was used to compare the differences between the concentrations of contaminants before and after the outbreak of the Covid-19 virus and to evaluate the mean correlation. Based on this test, values that were p-value <0.05 were considered significant. This was considered as a change in the concentration of the contaminant before and after the Covid-19 virus (decreasing or increasing). Those pollutants with a p-value <0.05 were considered unchanged.
Results and Discussion
Analysis of the T-test showed that for pollutants such as sulfur dioxide, nitrogen dioxide, and carbon monoxide in all three metropolises, there was no significant change in their concentration before and after the outbreak of the Covid-19 virus. However, significant changes were observed for ozone pollutants. Also, its concentration trend in all three metropolises has been a decreasing trend. The main sources of emissions of nitrogen dioxide, carbon monoxide, sulfur dioxide, and ozone are related to human activities, including transportation and industry (Ghahremanloo et al., 2021; Cárcel-Carras et al., 2021). Pollutants such as carbon monoxide, nitrogen dioxide and sulfur dioxide are the primary pollutants; It means that they are emitted directly from sources, while ozone is a secondary pollutant and depends on complex and nonlinear atmospheric chemistry (Bekbulat et al., 2021). Given that the concentration of ozone surface decreases significantly with increasing concentration of nitrogen dioxide. When nitric oxide (NO) emissions are high enough, the NO released into the atmosphere converts a large portion of ozone to nitrogen dioxide (Hashim et al., 2021). In addition, in all three cities, when the concentration of nitrogen dioxide increased, we saw a decrease in the amount of ozone concentration. In addition, during the Covid-19 era, many industries that produced primary pollutants, including carbon monoxide, nitrogen dioxide, and sulfur dioxide, were not on the closure list or were telecommuted. Despite the decline in the performance of some activities, important sectors such as manufacturing plants, industrial and mining centers, agriculture, and public transportation have continued to operate even during severe restrictions. The mean difference between the concentrations of nitrogen dioxide before and after the outbreak of Covid-19 was positive. However, this average difference is small. However, the concentration of nitrogen dioxide is slightly increased, especially in cold seasons; Therefore, it can be said that ozone concentration has decreased.

Keywords: Covid-19, Air Pollutants, Remote Sensing, Sentinel-5.


















 

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Comparison of Results of GIS-Based Multicriteria Decision Analysis and Remote Sensing Indicators in Kahir River Basin, Iran.

Alireza Khosravi¹, Mehdi Azhdary Moghaddam^2*, Seyed Arman Hashemi Monfared³,
 Hamid Nazaripour⁴

1. M.Sc. Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
2. Professor, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
3. Associate professor, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
4.Assistant professor, Department of Physical Geography, University of Sistan and Baluchestan, Zahedan, Iran.


Abstract
Flood risk maps and Flood zoning techniques are useful tools to manage this hazard in the catchment and mitigation of flood impacts. In South Baluchestan and Kahir Basin, due to the existence of winter and summer precipitation regimes, the occurrence of flash floods is inevitable due to the establishment of rural communities and settlements in flood-prone areas, the flooding has caused many damages to the region's vulnerable population. In order to zone flood risk and prepare flood risk maps, climatic data, hydrological, land cover, and topography of the basin were prepared from reliable sources and according to scientific studies, 12 variables affecting flood risk in the form of five main components (Hydrology, vegetation, land cover, climate, and topography) were prepared. According to the regional conditions of the basin, using the opinions of experts based on scientific methods, the weight of each variable and component was determined by Analytical Hierarchy Process(AHP). Using two methods of fuzzy overlay, Weighted Overlay, and the Geographical Information System facilities, a map of variables and components was prepared after reclassification and fuzzy membership function with appropriate operators. The results showed that the fuzzy overlay method concerning its dominant logic has a better distinction of flood-prone areas and can help determine flood hazard micro-zonation in the drainage basins like the Kahir basin. By comparing the results from the real data of the January 2020 flood obtained from satellite images. Due to poor infrastructure and high economic, the risk of flooding may be more harmful and widespread in the future.

Keywords: Flood, Fuzzy logic, Weighted overlay, Southern Baluchestan, GIS.