Morteza Heidarimozaffar; Morteza Shahavand
Abstract
Introduction Iran is mostly located in arid and semi-arid regions, and groundwater is its only water resource. The present study introduces a method based on spatial zoning evaluation which takes advantage ofFuzzy Logic and Geospatial Information System to design possible sites for an underground dam, ...
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Introduction Iran is mostly located in arid and semi-arid regions, and groundwater is its only water resource. The present study introduces a method based on spatial zoning evaluation which takes advantage ofFuzzy Logic and Geospatial Information System to design possible sites for an underground dam, and ranks them according to their suitability. The usability of this method for the construction of an underground dam in Kabodarahang Plain in the north of Hamedan Provincewas evaluated in the present study. Materials & Methods Groundwater use is considered to be a solution of water scarcity in arid and semi-arid regions. Lack of sufficient financial resources and adequate technology as well as specific physical conditions make it difficult to provide clean water in arid areas of most developing countries. Over the past few years, underground dams has been considered as a way to overcome water scarcity in arid and semi-arid regions. The present study seeks to identify suitable locations for the construction of an underground dam in Kabodarahangplain in north of Hamadan province using fuzzy logic in GIS environment. As one of the case study areas of Qareh Chai River,KabodarahangPlain isthe largest plain of Hamedan province with an area of 3448 square kilometers and an average height of about 1789 meters above the sea level.It is located between 48°14ˊ 51 ̋ to 49° 5ˊ 11 ̋ eastern longitude and 34° 50ˊ 6 ̋ to36°14ˊ 31 ̋ Northern latitude. To reach the goal of the present study, effective parameters in the constructionof underground dam, such as land slope, positionof wells, springs and aqueducts, rivers channels, positionof faults, location of villages and cities, position of paths and the thickness of alluvium were collected from the study area. Based onthe possibility of performing different spatial analyses in geographic information system environment, zoning ofKaboodarahang plain was evaluated from the point of view of an underground dam construction usingfuzzy logic and GIS tools in the present study. Results & Discussion Similar to membership in classical series,“And” operatorin Fuzzy Logic is used when two or more different criteria can help in solving an issue. This operator extracts the minimum membership level of pixel units in a specified positionand use it in the final map.Fuzzy multiplication operator multiplies membership level of pixel units in specified positionsof different factors and use the result in the final map. This operator is used when mapsof different criteria have a subtractive effect on each other.Fuzzy gamma operator is the general form of algebraic multiplication of fuzzy multiplication and addition operators to the power of gamma. It is used when increasing and decreasing effects are present in the relations between different criteria. Following the preparation of layers in Arc Map software, Euclidean distance operator and interpolation based on triangulation method were used to convert parameters to raster layers. Based on the background research and standards used, the criteria maps were combined using fuzzy operators. Using Fuzzy membership operator, an area of 3342 hectares, using fuzzy multiplier operator an area of2393 hectare (around one percent of the study area) and using the fuzzy gamma operator, an area of 35574 hectares (10.32% of the study area) was selected as having a very good potential for underground dam construction.Slope Map is also one of the most important criteria in determining areas appropriate for underground dam construction. It is suggested to use a larger-scale topographic map to improve the accuracy and increase the possibility of errors. Intelligent algorithms can also be used to determine the threshold level for standardization of the criteria. Since different organizationswork in the field of data collection, it is also suggested to providea suitable mechanism to assess the potential of other plains through consultation and coordination with other relevant organizations. It is recommended to use other parameters and factors affecting the selection of suitable areas for the construction of underground dams, such as soil type or physical and chemical properties of soil in future studies. Conclusion Zoning maps prepared by fuzzy logic in GIS environment can be used to determine the appropriate location forthe constructionof underground dams. Fuzzy operators provide special conditions which make them more reliablecompared to traditional methods.Appropriate areas for construction of underground dam were identified in GIS environment. A decision making model can also be produced based on the input parameters.It is suggested to enter general information of the area to perform the initial investigation of potential areas and then add field study information to complete the model.
Qassem Safari; Mohammad Reza Malek
Abstract
Extended Abstract
Introduction
Earthquake is one of the most frequent natural hazardsannually leading to numerous human and economic losses. Both in the planning stage and after the earthquake occurrence in the relief phase,findingappropriate sites for temporary housing is considered to be one ...
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Extended Abstract
Introduction
Earthquake is one of the most frequent natural hazardsannually leading to numerous human and economic losses. Both in the planning stage and after the earthquake occurrence in the relief phase,findingappropriate sites for temporary housing is considered to be one of the most important issues in reduction of damages caused by earthquake. Temporary housing, especially in a crisis situation is always accompanied by elements of uncertainty. Hence, definitive and classical approaches normally do not lead to acceptable results without involving elements of uncertainty. Although using methods based on fuzzy logic and fuzzy set theory are conventional and appropriate for uncertainty modeling, these methods also have their own disadvantages. For an instance, they require a certain and definitive membership function for each parameter. Moreover,fuzzy theory cannot describe verbal variables related to doubt and hesitation.
Temporary housing is always accompanied byuncertainty.Thus, fuzzy theory cannot lead to reliable results in this regard. However, in case sufficient information is not obtained using fuzzy theory, intuitionistic fuzzy logic isconsidered to be an appropriate solution for this problem and uncertaintymodeling. Despite various applications of intuitionistic fuzzy logic in uncertainty modeling, few researches have focused on this method.
Materials & Methods
Designing a qualitative model based on human knowledge requires a rule-based inference system, which is called an Expert System. This system consists of several parts. In the knowledge-based part, data and a set of rules, which are based on expert knowledgearesavedin the form of logical sentences. The input of this system is a set of numbers fuzzified in the inference engine by a set of fuzzy rules. Then,defuzzification is performed to map the fuzzy set and reach a certain point. In other words, the outputs must be readable and easy for the users.
The present study takes advantage of fuzzy and intuitionistic fuzzy approaches todetermine optimal sites for temporary housing. Furthermore, determinant factors of danger and safety followinganearthquakeare used to identify safe places for sheltering in such situations. The present study has applied layers of faults, hospitals, emergency and medical centers, fire stations, parks and green spaces, and roads as determinant factors. New spatial layers were produced for each ofthe aforementioned layers using distance and other similar functions. Then, trapezoidal functionwas used to determine membership and non-membership function of each layer in both fuzzy and intuitionistic fuzzy methods. Membership functions obtained from these methods are different in that they assign different membership values to the pixels surrounding the layer. Following the definition of membership and non-membership functions for each layer in both methods, temporary accommodation maps were obtained using the classical fuzzy as well as intuitionistic fuzzy methods.
Results and Discussion
The results obtained from these two methods were not identical. The main reason for this difference is that they treat data uncertainty differently. Furthermore, the results of membership and non-membership functions inintuitionistic fuzzy are not complementary. This provides us with a powerful tool for interpretation and, of course, decision making about the study area. As the first case, membership and non-membership degreesequal zero and one implying that the membership degree equals one and the non-membership degree equalszero. This occurs when the method identifies the area as quite appropriate for temporary housing after the earthquake. In this case,results are determinative, and data can be used in the area. In the second case, membership and non-membership degreesare low, which occurs in areas lacking enough information. It implies that more information is neededin such areas for decision making. The third condition takes place when both membership and non-membership degrees equal 0.5. In such a case,it can be conclude that either the stated variable belongs to the area with a membership degree of 0.5, or the variable doesn’t belong to the area with a non-membership degree of 0.5. In the fourth condition, the membership degree is high and the non-membership degree is low. In this case, the results can be trusted and used in decision-making. The fifth condition is in contrast with the fourth case. It occurs when the non-membership degree is high and membership degree is low. Under this condition, it can be concluded that the results are not reliable.
Conclusion
The proposed method and model were implemented in the second district of Tehran. According to the results, it can be concluded that the proposed approachperforms better than theclassical fuzzy approach, especially in the presence ofuncertainvariablesand lack of adequate data.
Ali Dastranj; Maryam Jafari Aghdam
Abstract
Extended Abstract Introduction After United States of America, China and Turkey,Iran has the highest karst percentage, and karst formations cover more than 11%of our country. The volume of water stored in these areas can supply the water demand of many cities and villages. Characteristics of karst aquifers’feeding ...
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Extended Abstract Introduction After United States of America, China and Turkey,Iran has the highest karst percentage, and karst formations cover more than 11%of our country. The volume of water stored in these areas can supply the water demand of many cities and villages. Characteristics of karst aquifers’feeding area determine the type of feed, flow andvulnerability of the aquifer tocontamination.Therefore, identification of feeding areas in karst aquifers plays a key role in understanding their hydrodynamic and hydrochemical characteristics, along with management and optimal scientific exploitation of them. Given the critical impact of karst water resources on human life and limited number of researcheson karst, any fundamental, applied, and developmental research performed with the aim of modelingkarst landforms and investigating the potential of karst water resources in these areas seems necessary. In order to assess andevaluatethe potential of karst water resources from a qualitativeand quantitative perspective, understand pollution, and vulnerability and also assessrisks facing aquifers,the present study models feeding areas of Dalahoowasaquifer using KARSTLOP model. Methodology The present applied-developmental study is based on library research, field observation, and evaluation methods and seeks to prepare the map of karst water resourcesfeeding Dalahookarst aquifer. Fuzzy logic and gamma operator model were used to produce a zoning map for surface karst development. And finally, a map was produced for the feeding areas of Dalahoowaskarst aquifer using KARSTLOP model. Result Using Natural Breaks method, the zoning map of Dalahoo’ssurface karst development divides the study area are into four classes: areas without karst formations (0-0.224), karst formations with low development (0.224-0.558), karst formations with moderate development (0.588-0.777) and developed karstformations(0.777-0.982).The final map of Dalahoo’sfeeding areas indicates that Bistoon karst aquifer has anannual charge rate of 37 to 81 percent. Discussion and conclusion Systematic study of karst aquifer’s water tables is very important, especially for drinking and agricultural purposes. The final mapof feeding areas, as well as the layers obtained from KARSTLOP method can be used as inputs for modeling groundwater. They may also be used to address practical issues of karst in relation to water management, including water supply, spatial distribution of watersheds, transboundary management of water, and initial assessment of groundwater vulnerability. Results obtained from zoning of feeding areas are consistent with the results obtained from zoning of surface karst development. High feeding values as well as spatial distribution of the aquifer’s feeding zones indicate that the aquifer has a high potential to store groundwater resources.This potentialityshould be properly managed to makeharvestingand protecting groundwaterpossible.
Payam Jafari; Somayeh Sadat Shahzeidi
Abstract
Extended abstract
Introduction
Today, cities in different parts of the worldare exposed to damages from natural hazards for various reasons. These hazards which are associated with lots of financial damages, fatalities and injuries, are in need for urgent preventive measures. Based on the United Nation ...
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Extended abstract
Introduction
Today, cities in different parts of the worldare exposed to damages from natural hazards for various reasons. These hazards which are associated with lots of financial damages, fatalities and injuries, are in need for urgent preventive measures. Based on the United Nation International Strategic Plan for disaster reduction (UNISDR), all hazards have two natural and human activities origins.The province of Gilanis one of the northern coastal provinces, whose center is the city of Rasht. The objective of the present research is, analyzing and zoning geomorphic hazards in the province of Gilan. The method of this research is descriptive – analytical, and empirical. In the descriptive section, by using documentary studies and also in the analytical section, by identifying the effective parameters in the zonation of geomorphic hazards and integratingthem with the spatial analyses in GIS, vulnerable zones were identified in the study area.
In this research, the factors effective in the zonation of hazards were identified first. Then, in order to measure the significance of each of these factors, a questionnaire was prepared to carry out this important task by the method of ANP and by collecting the opinions of the relevant experts on each of the identified factors. After obtaining the opinions and using the fuzzy logic method, evaluation of each of the criteria and determination of their importance coefficients were done and based on its results, spatial evaluation was carried out using ARC GIS and high risks zones were identified.Results have shown that the use of fuzzy logic along with spatial analysis of GIS has been able to be used as an efficient tool in zoning geomorphic hazards and to prove the capability of the analytical model of research well.
Materials & Methods
The performing method of this research is descriptive-analytical, which is compiled using documentary studies of required information and dat. In this study, it was attempted to investigate the geomorphic hazards in the province of Gilan. At first, the study area was identified. In the next stage, information layers such as slope, topography, vegetation, the elevation map of land use and… were prepared using 1: 50000 topographic maps, 1:100000 and 1: 250000 geological maps, and Digital Elevation Model (DEM), and finally, the provided effective information layers by the experts’ opinion and the obtained field and documentary studies were investigated in the form of network analysis model. Network Analysis Process (ANP) is one of the techniques for decision-making. When several indicators are considered for evaluation, the evaluation task becomes complicated, and when the criteria are of different genders, the work will become more complicated, and the evaluation and comparison go out of the analytical state which the mind is capable of performing), and a strong tool for practical analysis is needed. Therefore, the network analysis process is capable of doing this (Shadfar et al., 2007: 66). The network analysis process is one of the multi-criteria decision-making techniques. This model has been designed based on the hierarchical analysis process and replaces ‘network’ with ‘hierarchy’. The main assumption in AHP is based on the independent function of the hierarchical upper groups from all of its lower parts and from the criteria of each level and class (Chang et al., 2005: 22 and De Seun, 2004: 636).Saatyhas proposed the use of the hierarchical analysis model (AHP) to solve problems with independent and dependent criteria and solutions, and has established and presented the network analysis model (Lee and Kim, 2001: 374). Thus, the ANP method was presented as an extension of AHP.
As the AHP provides a framework for hierarchical structures with one-way relationships, the ANP also provides the possibility of complex internal relationships between different levels of decision and criteria. The ANP feedback approach has replaced the network structure with hierarchical structure, suggesting that the relations between different levels of decision-making can’t simply be imagined as up-down, dominant-recessive or direct-indirect.In general, the ANP model consists of a hierarchy of control, clusters, elements, interrelationships between clusters and elements (Sarkis, 2002; 23; Oraet et al., 2006: 247). The geomorphic hazards of Gilan province were evaluated and zoned in 6 stages (Saaty, 1392).
1- First step:At first, given the field and library studies as well as the experts of the issue, the research-related elements were defined from 4 clusters with 11 elements. The relations between the variables and clusters were determined using correlation analysis.
2- Second step: the pairwise comparison matrix and the relative weight estimation: the determination of relative weightin ANP is similar to AHP, In other words, the relative weight of the criteria and the sub-criteria can be determined throughpairwisecomparison.Pairwise comparisons of the elements in each level are done similar to the AHP method because of its relative significance to the criterion of control.
3- Third step:the formation of primary super matrix. The ANP elements interact with each other. These elements can be the decision-making unit, criteria, sub-criteria, the obtained results, options, and anything else. The relative weight of each matrix is calculated based on the pairwise comparison similar to the AHP method. The resulting weights are entered in the super matrix, which indicate the mutual relationbetween the elements of the system.
4- Fourth step: the formation of a weight super matrix: super matrix columns consist of several special vectors that the sum of each vectoris equal to 1. Therefore, it is possible that the sum of each column of primary super matrixto be more than 1. In order to factorize the column elements proportional to the relative weight, and that the sum of the column be equal to 1, each column of the matrix is standardized. As a result, a new matrix is obtained, the sum of each column of which will be equal to 1. The new matrix is called the weight matrix. (FarajiShabbarbar et al., 2011: 56).
5- Fifth step:the calculation of the general weight vector: in the next step, the weight super matrix reaches to a power limit so that the matrix elements are converged and its row values are equal. The general weight vector is determined based on the matrix obtained.
6- Sixth step:the calculation of the final weight of the criteria: finally, the weight of each of the effective criteria is obtained. After determining the structure of the model and determining the weight super-matrices and the limit, the weight of each of the effective indices is obtained. After weighting the natural criteria effective in the zonation of the effective indices, using fuzzy logic technique in this stage, the maps of geomorphic hazards mapping of Gilan province are plotted
Results & Discussion
After determining the relationship between the effective criteria in geomorphic hazards, the experts’ opinions, the matrix of pairwise comparison, and the relative weight estimation, the formation of primary super matrix, the formation of weight super matrix, the calculation of the general weight vector, the calculation of the final weight of the criteria was carried out, using the mathematical operations in the ArcGissoftware. Then, using fuzzy logic technique, maps of geomorphic hazards zonation in Gilan province were drawn. Given the combination of all layers and the application of the coefficients obtained from the network analysis model, the final map of geomorphic hazard zonation was plottedand three vulnerable zones were obtained. 1- First zone - Northeast of the province: This is a zonewith high risks due to its location on the way of floods and geological features.
2-Second zone: south of the province: located in the vicinity of Roodbar and Rudsar, and to some extent Amlash, is considered as a part of high risky zones of the province. Closeness to the faultand relatively high slope are among the characteristics of this zone.
3-Third zone: center of the province: in the vicinity of the city of Bandar-e Anzali, Somesara is considered as high risk zones of the province. Flooding, high erosion, and slope movements to some extent are among the features of this zone.
Conclusion
Investigating the situation and the value of vulnerable human environments against various types of geomorphological hazards seems to be very important and essential. Natural hazards, especially geomorphic hazards, have already had and have lots of financial and losses and fatalities. On this basis, natural hazards were considered as one of the basic studies in order to be able to control and reduce natural hazards. Thus, the most risky zones of Gilan province were integrated into critical centers such as mines in the province. In order to model and predict the relative risk of geomorphic hazards in the present research, an ANP network analysis model was used. For each of the different values and ranges, a weight and score were obtained, for which the fuzzy sum of these scores and the integration of each layer in the obtained weight, determined the relative risk of the occurrence of geomorphic hazards. The results showed that three vulnerable zones in the northeast, south of the province I the vicinity of the cities of Roodbar and Rudsar, and to some extent,Amlash, and the center of the province in the vicinity of the cities of Bandar-Anzali, and Somesara, are risky and hazardous areas which are affected by the risks of flood and Geological features, proximity to faults and relatively high slopes, flooding, high erosion and, to some extent, movements of the slopes. The application of fuzzy logic along with spatial analysis of GIS has been able to be used as an effective tool forgeomorphic hazards zoning. In the end, it is necessary to note that the location of some of the zones at low levels of vulnerability and risk does not represent their idealsituation and determines only the place of the aforementioned zone in relation to other zones.
bahare hajizade vadeghani; jahanbakhsh balist; saeed karimi
Abstract
Extended Abstract Introduction Paying attention to sustainable urban physical development in urban development programs indicates the importance of this issue in strengthening the cultural, social and physical aspects of the city. Developers in developing countries have deeply realized that infrastructure ...
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Extended Abstract Introduction Paying attention to sustainable urban physical development in urban development programs indicates the importance of this issue in strengthening the cultural, social and physical aspects of the city. Developers in developing countries have deeply realized that infrastructure services and facilities have also played a major role in improving the development of urban and rural areas in these countries, and emphasizes this. Finding out that improving the access of urban and rural communities to basic services is an important tool in accelerating regional development, and accepts that location-based services, in addition to impacting costs in Efficiency and utilization and their quality are also effective. A lot of research has been done in the field of location, including the study of Sin et al. (2002) aimed at evaluating urban land use structures with an eye to sustainable development. Simpleiara et al. (2004) examined the dynamics and modeling of urban expansion with the help of GIS in the city of Manglor, India, and predicted the type of future expansion of the city. Vanakata Subways (2007) completed the article entitled "Analysis of Places for Urban Development using GIS" (Chang, 2008) using GIS and Land Multi-Fuzzy Decision-Making Model Has identified susceptible people for the establishment of an urban forest in Harlingen. The importance and necessity of this research in the lack of methods are suitable models for locating human settlements. In decision-making for the development of human settlements, all the criteria and parameters required and involved in structured and structured models should be considered in the form of up-to-date models. The purpose of the research is to develop a suitable model for determining the appropriate sites for the development of human settlements. In this research, we have been asked to answer the following question. Is the city of Kashan capable of urban development and, if so, what is its potential and in what districts? Materials and methods The city of Kashan with an area of 20,000 square kilometers (2100 hectares) and a population of 500,000, facing the mountains on one side with its back to the desert on the other side, is located in the central region of Iran. The geographical coordinates of Kashan with an altitude of 945 meters above the sea level are 51 degrees and 27 minutes East longitude and 33 degrees and 59 minutes North latitude. In this research, at first, data were collected and the criteria were defined and weighted by FANP. Then, using the Arc Gis software, the criterion map was created and standardized. To create the final map, the layers were combined and overlaid by the weighted linear combination method and Gamma function in fuzzy logic. Finally, the attraction map of Kashan City for urban development was created and analyzed. The GIS-based linear weighting method (WLC) includes the following steps: 1. Defining a set of evaluation criteria and options 2. Standardize the mapping layer of each level 3. Define the weight for each criterion: meaning that a relative weight is assigned directly to each criterion map. 4. Generating the layers of standardized layer with weight: This means that we multiply the standardized layers of the weight in the respective weights. 5. Add the final score to each option using the "Gamma" for the layout of the standard weighted map. 6. Sorting options based on ratings (the best option is the option with the highest score). Result and discussion To determine the weight and prioritization of the FUZZY ANP software criteria, the purpose of the research which is suitable for urban development, is at the highest level of decision-making, and at the next level, the criteria Includes (environmental, socioeconomic and physical), and at the last level are the following criteria which are mentioned in the article 13 at the beginning of the article, and according to experts, regarding the recognition of the region the weight loss study is carried out for each of the following criteria. After weighting and performing calculations in the software, the final weight is obtained. In urban development, the highest weights are taken to the slope index and the lowest weight is considered as the index of slope (Table 2). After fuzzying and multiplying the weights by the fuzzy layers, the GAMA operator with three suffixes (0.9, 0.5, 0.1), is applied to the fuzzy layers which is shown in Fig. 7. The 0.9 gamma fuzzy operator shows the most compatible among the urban areas of Kashan with appropriate lands for urban development. Therefore, a 0.9 gamma is referred to as the final layer of appropriate land for urban use. The second coexistence method is, using the WLC linear gravity combination. In this section, all cabinet layers were classified instead of fuzzy layers, and their class values were determined. Then, in the RASTER CALCULATOR, the classified layers were multiplied by the weight of the FANP, and finally, the total layers were plotted, as shown in Fig. 8. Conclusion Based on the results of this research and the previous studies, the optimal result is the time taken by the 0.5 gamma operator, in which case its function is a combination of two operators Sam and Product. According to the final map obtained from the WLC method, urban development is more possible in the southwestern part of the city of Kashan. In the fuzzy method, the results indicate that the current location of Kashan city and its southern regions have good potential. The results of the linear weight combination method are similar to the fuzzy combination method of the current location of Kashan and its southern and southwestern regions. About 15% of the total area of the city of Kashan is suitable for urban development. Therefore, according to the obtained results, the aforementioned model including two methods and the use of the decision-making techniques, can be used as an appropriate model for studying the power of other similar regions (central regions of Iran). The development of the cities of Kashan and Qasr is more oriented towards the south and southwest.
Samad Shadfar
Abstract
One of the types of environmental hazards that causes the destruction of agricultural lands, rangelands and Infrastructure in many parts of the country is gully erosion. In this research, fuzzy logic operators were used with the aim of determining the different hazard zones,obtaining the area of each ...
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One of the types of environmental hazards that causes the destruction of agricultural lands, rangelands and Infrastructure in many parts of the country is gully erosion. In this research, fuzzy logic operators were used with the aim of determining the different hazard zones,obtaining the area of each one of them, and presenting the map of the gully erosion hazard in Troud watershed. In order to achieve this goal, satellite imagery, interpretation of 1:20000 scale aerial photos, 1:50000 scale topographic maps, 1:100000 scale geological maps, field studies and ArcGIS software have been used as the main research tools. To do this, at first, some of the effective variables which had more important roles in the formation and development of gully erosion, as well as the areas with gully erosion, were identified. In the next stage, the effective factor classes were weighted and the gully erosion map was prepared using fuzzy operators including fuzzy algebraic sum, fuzzy multiplication, fuzzy gamma 0.5 and fuzzy gamma 0.8 in the GIS environment.The results indicate that in the fuzzy algebraic summation method, 100% of the gully areas are located in very highclass, in the fuzzy algebraic multiplication, 83.29% of the gully areas are located in low class, in 0.8 fuzzy gamma method,60.93% of the gullies are located in low class and about 17 %are located in high and very high classesbut, in 0.5 fuzzy gamma method, around 1.5% of the gully areas are located in low class and about 62% are located in high and very high classes.
Marzieh Khanahmadi; Mahdi Arabi; Alireza Vafaienejad; Hani Rezaiean
Volume 23, Issue 89 , May 2014, , Pages 88-98
Abstract
Constructing new urban facilities needs a precise investigation on the right method of establishing such facilities in different areas of the city. Selecting an optimal place based on different and sometimes controversial characteristics is the first fundamental issue in correct allocation of urban facilities. ...
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Constructing new urban facilities needs a precise investigation on the right method of establishing such facilities in different areas of the city. Selecting an optimal place based on different and sometimes controversial characteristics is the first fundamental issue in correct allocation of urban facilities. This is especially important if crucial issues like human life are also considered. Thus due to the importance of endangered human lives, optimal selection of fire stations is considered to be crucial. Considering the uncertainty about information sufficiency and comprehensiveness of inferences drawn by tools like spatial information system, fuzzy model is used in combination with analytic hierarchy process. In the beginning step of the study, influential factors in locating fire stations were determined and standard maps were produced and prepared. During the study, a survey performed on the experts opinions indicated that these criteria do not have the same influence in locating stations. Thus, these criteria should be assigned different weights based on their importance and influence. Analytic hierarchy process (AHP) and Export choice software were used to weight these criteria. After collecting expert opinions and in order to avoid possible non-expert opinions, adaptability of the judgments were calculated. After verifying CR values, these weights were used in subsequent steps. In the next step, fuzzy logic was used to rate these layers. Prepared layers were transformed into fuzzy logics using different membership functions which were selected according to experts’ opinion. Finally, AHP and weighted linear combination (WLC) were used to integrate fuzzy criteria with fuzzy membership functions and calculated weights, and in this way appropriate zones for building fire stations were identified and determined. Simply relying on the map results cannot have the necessary efficiency in locating an optimal place for the fire stations. Therefore, standard functional radius of available stations were determined using network analysis in GIS environment. Then, places with a high score for building stations and those covering whole area in a standard time were selected. This research seeks to display the efficiency of applying integrative logic for ranking layers using AHP in GIS environment. The integrated model benefits from high capabilities and it can be applied for different goals (selecting the optimal place for a site) and in different spatial situations.
