University of IsfahanGeography and Environmental Planning2008-536229420190220Locating Top Ten Areas of Nuclear Power Stations in IranLocating Top Ten Areas of Nuclear Power Stations in Iran1182307910.22108/gep.2018.98253.0FAAli AsgharJafariMA in Industrial Engineering, Islamic Azad University, Najaf AbadFatemehNematollahiPh.D. Candidate of Geomorphology, Faculty of Geography and Planning, University of IsfahanMohammad HossainRameshtProfessor of Geomorphology, Faculty of Geography and Planning, University of IsfahanJournal Article20160407Diversity of power generation in each country can be considered a form of passive defense policy. Although there are enough fossil energy resources in Iran, due to several reasons, diversifying energy production centers has always been considered as a strategic policy and if we consider the occurrence of natural events and unpredictable disasters and the promotion of the diversity of scientific and technical professions to this collection, validity of such a strategy will be more clear. Locating such plants has attracted attention of land logisticians and due to environmental issues and security matters, it demands more attention and accuracy. This article, which is based on Christaller and Lush’s theory, underlying the three main factors of environmental considerations, security, and access to the main power supply network and applying geographical information system, first attempts to determine the appropriate locations based on these three features, then, applying a provision of access to the beach and the sea depth in the form of TOPSIS priority ranking, it priorities ten points in Iran, as the candidate for building plants. The results of this study show that the distribution of certain areas of Iran has the advantage of such election and from the total of 10 points two regions in the north coasts, two regions in the domestic land, one region in the coast of Oman and five regions in Persian Gulf have the priority of being selected as locations for establishing nuclear power plants in Iran.Diversity of power generation in each country can be considered a form of passive defense policy. Although there are enough fossil energy resources in Iran, due to several reasons, diversifying energy production centers has always been considered as a strategic policy and if we consider the occurrence of natural events and unpredictable disasters and the promotion of the diversity of scientific and technical professions to this collection, validity of such a strategy will be more clear. Locating such plants has attracted attention of land logisticians and due to environmental issues and security matters, it demands more attention and accuracy. This article, which is based on Christaller and Lush’s theory, underlying the three main factors of environmental considerations, security, and access to the main power supply network and applying geographical information system, first attempts to determine the appropriate locations based on these three features, then, applying a provision of access to the beach and the sea depth in the form of TOPSIS priority ranking, it priorities ten points in Iran, as the candidate for building plants. The results of this study show that the distribution of certain areas of Iran has the advantage of such election and from the total of 10 points two regions in the north coasts, two regions in the domestic land, one region in the coast of Oman and five regions in Persian Gulf have the priority of being selected as locations for establishing nuclear power plants in Iran.https://gep.ui.ac.ir/article_23079_d15f6498b02dc526c07062ba524ab7ab.pdfUniversity of IsfahanGeography and Environmental Planning2008-536229420190220Optimal Locating of the New Towns in Qazvin Province based on Climatic ParametersOptimal Locating of the New Towns in Qazvin Province based on Climatic Parameters19342314010.22108/gep.2018.98275.0FAFatemehShahryarTourism Research Center, Najafabad Branch, Islamic Azad University, Najafabad, IranAmirGandomkarAssistant Professor, Tourism Research Center, Najafabad Branch, Islamic Azad University, Najafabad, IranRahimHashempourAssistant Professor, Imam Khomeini International University, Qazvin, IranJournal Article20160513Due to the increasing population and urban development, locating suitable locations according to climatic parameters for constructing new towns is the concern of today's world. Locating is an activity in order to select a suitable location for a particular application by assessing and analyzing the spatial and non-spatial seating properties of a land. Hence, locating suitable areas according to climatic parameters for constructing new towns in Qazvin province is the main goal of the present study. The method of this study is to determine the importance and weight of climatic parameters using fuzzy-AHP and data from two questionnaires Delphi and pairwise comparison method. The susceptible areas in terms of climate conditions were identified in a case study in Qazvin province. Finally the results show that, according to climate conditions for creating new cities, 9.6 percent area of the province were located in the highly desirable region, 31.3 percent in favorable region, 40.7 percent in moderate region, 12.3 percent in undesirable region, and 9.1 percent in the complete undesirable region, respectivelyDue to the increasing population and urban development, locating suitable locations according to climatic parameters for constructing new towns is the concern of today's world. Locating is an activity in order to select a suitable location for a particular application by assessing and analyzing the spatial and non-spatial seating properties of a land. Hence, locating suitable areas according to climatic parameters for constructing new towns in Qazvin province is the main goal of the present study. The method of this study is to determine the importance and weight of climatic parameters using fuzzy-AHP and data from two questionnaires Delphi and pairwise comparison method. The susceptible areas in terms of climate conditions were identified in a case study in Qazvin province. Finally the results show that, according to climate conditions for creating new cities, 9.6 percent area of the province were located in the highly desirable region, 31.3 percent in favorable region, 40.7 percent in moderate region, 12.3 percent in undesirable region, and 9.1 percent in the complete undesirable region, respectivelyhttps://gep.ui.ac.ir/article_23140_03700478fa0806dacdb0be1b07a52bad.pdfUniversity of IsfahanGeography and Environmental Planning2008-536229420190220Comparing Three Main Methods of Artificial Intelligence in Flood Estimation in Yalphan CatchmentComparing Three Main Methods of Artificial Intelligence in Flood Estimation in Yalphan Catchment35502316810.22108/gep.2018.98036.0FAHamidNouriAssistant Professor, Faculty of Natural Resources and Environment, Malayer University, Malayer, IranAlirezaIldoromiAssistant Professor, Faculty of Natural Resources and Environment, Malayer University, Malayer, IranMahdiSepehriMA Student, Faculty of Natural Resources and Environment Malayer University, Malayer, IranMahdiArtimaniMA Student, Faculty of Natural Resources and Environment, University of Lorestan, Khoramabad, IranJournal Article20150609Estimation of discharge as one of the major issues in water resource management and flood control has a key role in the success of water construction design and efficiency of Bio-Mechanical proceeding in catchments. In this research, discharge Peak of Yalphan River has been simulated using three main methods of artificial intelligence (MLP neural network model, subtractive clustering and ANFIS model, and the combination of neural network and genetic algorithm). For this purpose, 8 parameters have been prepared as input data (2001-2012) including precipitation in the event day, precipitations during 5 days before the event day, base flow in the event day and CN map. Peak of flow has been considered as output data of models. RSME, MAE and NSE indicators has been used to assess the artificial intelligence models. Output data of neural network model have been imported to the combined model of neural network and genetic algorithm. Also, output data of subtractive clustering model have been imported to ANFIS model. Finally three models have been assessed using the mentioned indicators. The results showed that the combined model of neural network and genetic algorithm is better than the other models in Yalphan Catchment.Estimation of discharge as one of the major issues in water resource management and flood control has a key role in the success of water construction design and efficiency of Bio-Mechanical proceeding in catchments. In this research, discharge Peak of Yalphan River has been simulated using three main methods of artificial intelligence (MLP neural network model, subtractive clustering and ANFIS model, and the combination of neural network and genetic algorithm). For this purpose, 8 parameters have been prepared as input data (2001-2012) including precipitation in the event day, precipitations during 5 days before the event day, base flow in the event day and CN map. Peak of flow has been considered as output data of models. RSME, MAE and NSE indicators has been used to assess the artificial intelligence models. Output data of neural network model have been imported to the combined model of neural network and genetic algorithm. Also, output data of subtractive clustering model have been imported to ANFIS model. Finally three models have been assessed using the mentioned indicators. The results showed that the combined model of neural network and genetic algorithm is better than the other models in Yalphan Catchment.https://gep.ui.ac.ir/article_23168_20c9d9e3b116308df1f83ba31b6d8a19.pdfUniversity of IsfahanGeography and Environmental Planning2008-536229420190220A Survey of Landslides in Central Zagros using Entropy Model
Case Study (Aradal-Naghan Region)A Survey of Landslides in Central Zagros using Entropy Model
Case Study (Aradal-Naghan Region)51682355110.22108/gep.2019.100417.0FASomayehSadat Shahzeidi1 Assistant Prof. of Physical Geography (Geo morphology), University of Guilan, , Rasht, IranMojganGhanbari2 Mojgan Ghanbari, graduate of geographyJournal Article20161117Today, cities around the world are exposed to natural hazards for many reasons. These risks come with many injuries that require immediate and preventive actions. The occurrence of landslides and hazards has made it necessary to identify and prioritize these sensitive areas. Ardal-Naghan region is located in the southwest of Chaharmahal-Bakhtiari province. The method of this research is descriptive-analytic. In the descriptive section, using the documentary studies and in the analytical section, identifying the effective parameters in the zoning of geomorphic hazards and integrating it with spatial analysis in the GIS of the vulnerable zones in the study area were determined. In this study, firstly, effective factors in hazard zonation were identified. After examining satellite images, geological maps and field studies, effective factors were studied using entropy model. The aim of this research is to determine the zoning of landslide hazard in Ardal-Naghan region using the entropy model in landslide occurrence by identifying effective factors such as slope, direction, distance from fault, distance from the waterway, elevation, geology and so on. According to the entropy model, the results show that 23 percent of landslides are in low-risk area, 25 percent are in moderate risk, and 52 percent of landslides are in high-risk area. This shows that in landslide zoning, the regional entropy model possesses the accuracy and validity.Today, cities around the world are exposed to natural hazards for many reasons. These risks come with many injuries that require immediate and preventive actions. The occurrence of landslides and hazards has made it necessary to identify and prioritize these sensitive areas. Ardal-Naghan region is located in the southwest of Chaharmahal-Bakhtiari province. The method of this research is descriptive-analytic. In the descriptive section, using the documentary studies and in the analytical section, identifying the effective parameters in the zoning of geomorphic hazards and integrating it with spatial analysis in the GIS of the vulnerable zones in the study area were determined. In this study, firstly, effective factors in hazard zonation were identified. After examining satellite images, geological maps and field studies, effective factors were studied using entropy model. The aim of this research is to determine the zoning of landslide hazard in Ardal-Naghan region using the entropy model in landslide occurrence by identifying effective factors such as slope, direction, distance from fault, distance from the waterway, elevation, geology and so on. According to the entropy model, the results show that 23 percent of landslides are in low-risk area, 25 percent are in moderate risk, and 52 percent of landslides are in high-risk area. This shows that in landslide zoning, the regional entropy model possesses the accuracy and validity.https://gep.ui.ac.ir/article_23551_912ce8802786fac0cc7f8a04252758af.pdfUniversity of IsfahanGeography and Environmental Planning2008-536229420190409The Physical Development of Mashhad Metropolis and Change in the Morphology of River SystemsThe Physical Development of Mashhad Metropolis and Change in the Morphology of River Systems69882352310.22108/gep.2018.105486.1071FAEzatallahGhanavatiAssistant Professor, Dean of the Faculty of Geography, Kharazmi University, Tehran, IranSeyed RezaHosseinzadehAssistant Professor, Faculty and Geography Department , Ferdowsi University Mashhad, Mashhad, IranAmirKaramAssistant Professor, Head of Geomorphology Department, Kharazmi University of Tehran, IranMitraFarokhzadPhD Candidate, Department of Social Sciences, Farhangian University of Mashhad, IranJournal Article20170721In terms of geographical location, Mashhad metropolis has spread all over a wide alluvial plain. Locating between the Kopeh Dagh and the Hezar Masjed sedimentary heights and the Binalood igneous heights has led to the creation of specific morphology for the Mashhad alluvial plain. In the northern part of the city, the Kashafrood River drains all the rivers of Mashhad plain. And the Binalood heights drainage rivers run through the city of Mashhad and drain into the Kashafrood River. The city's physical development over the years has led to a change in the morphology of the city's rivers and in some ways, high-rise buildings are built on the abandoned river-beds and the probability of occurrence of geomorphological hazards has increased. In this research, the location of Mashhad and its physical growth, which led to the destruction and change of river's morphology, has been studied by using 1353, 1359, and 1390 satellite images and the old maps of Mashhad and geological and topographic maps in different periods. The purpose of this research is to investigate the comparative situation of rivers with urban built canals and the resulting risks. In this regard, it has been found that many urban canals are designed without regard to the natural morphology of the rivers and also regardless of the flow capacity of the water. The natural type of the river-beds has been sedimentary deposits including shale, clay and sand and rock along with the forms between the rifting of the rivers, but the canals have thick concrete walls and direct paths.In terms of geographical location, Mashhad metropolis has spread all over a wide alluvial plain. Locating between the Kopeh Dagh and the Hezar Masjed sedimentary heights and the Binalood igneous heights has led to the creation of specific morphology for the Mashhad alluvial plain. In the northern part of the city, the Kashafrood River drains all the rivers of Mashhad plain. And the Binalood heights drainage rivers run through the city of Mashhad and drain into the Kashafrood River. The city's physical development over the years has led to a change in the morphology of the city's rivers and in some ways, high-rise buildings are built on the abandoned river-beds and the probability of occurrence of geomorphological hazards has increased. In this research, the location of Mashhad and its physical growth, which led to the destruction and change of river's morphology, has been studied by using 1353, 1359, and 1390 satellite images and the old maps of Mashhad and geological and topographic maps in different periods. The purpose of this research is to investigate the comparative situation of rivers with urban built canals and the resulting risks. In this regard, it has been found that many urban canals are designed without regard to the natural morphology of the rivers and also regardless of the flow capacity of the water. The natural type of the river-beds has been sedimentary deposits including shale, clay and sand and rock along with the forms between the rifting of the rivers, but the canals have thick concrete walls and direct paths.https://gep.ui.ac.ir/article_23523_a848ed49ebc40cc22affecd6e9a00e60.pdfUniversity of IsfahanGeography and Environmental Planning2008-536229420190220A Capability Assessment of the SDSM Model to Simulate Mean Temperature of Urmia CityA Capability Assessment of the SDSM Model to Simulate Mean Temperature of Urmia City891082351410.22108/gep.2019.98143.0FAHosseinAsakerhProfessor of Climatology, Department of Geography, University of Zanjan, Zanjan, Iran0000-0001-7699-0547HassanShadmanPhD Candidate of Climatology, Department of Geography, University of Zanjan, Zanjan, IranJournal Article20151106Climate modeling is one of the fundamental methods of simplifying the complexity of the climate that can increase our understanding of the system’s behavior. Climate simulating through using the outputs of general circulation models in order to be aware of the characteristics of the climate, will be required in the coming years. The achievements of general circulation models cannot be used directly in regional and smaller-scale climate simulations. A common way to solve this problem is by statistically downscaling the output of general circulation models. SDSM is one of the most practical models in the mentioned fields. In this study, attempts are made to assess the ability of the SDSM in downscaling and simulating the temperature data of Urmia since the beginning of 1961 until the end of 2010 using National Emergency Communications Plan’s re-analyzed data and the outputs of HadCM3 under A2 and B2 scenarios. To assess the adequacy of the models obtained and the SDSM’s ability to simulate, some statistical tests such as the Chow test, the standard error, Wilmot index compatibility and also monthly and annual diagrammed data have been used. The results of this study show that the greater the time period is, the more preferable and closer to reality the simulated mean temperature will be. However the SDSM model’s function is inadequate in simulating the maximums and minimums. Therefore the achievements of this model are suitable only to obtain a general understanding of the characteristics of future climate and they cannot be used in precise projects.Climate modeling is one of the fundamental methods of simplifying the complexity of the climate that can increase our understanding of the system’s behavior. Climate simulating through using the outputs of general circulation models in order to be aware of the characteristics of the climate, will be required in the coming years. The achievements of general circulation models cannot be used directly in regional and smaller-scale climate simulations. A common way to solve this problem is by statistically downscaling the output of general circulation models. SDSM is one of the most practical models in the mentioned fields. In this study, attempts are made to assess the ability of the SDSM in downscaling and simulating the temperature data of Urmia since the beginning of 1961 until the end of 2010 using National Emergency Communications Plan’s re-analyzed data and the outputs of HadCM3 under A2 and B2 scenarios. To assess the adequacy of the models obtained and the SDSM’s ability to simulate, some statistical tests such as the Chow test, the standard error, Wilmot index compatibility and also monthly and annual diagrammed data have been used. The results of this study show that the greater the time period is, the more preferable and closer to reality the simulated mean temperature will be. However the SDSM model’s function is inadequate in simulating the maximums and minimums. Therefore the achievements of this model are suitable only to obtain a general understanding of the characteristics of future climate and they cannot be used in precise projects.https://gep.ui.ac.ir/article_23514_07d316956146326263ae887c16bfd825.pdfUniversity of IsfahanGeography and Environmental Planning2008-536229420190220Evaluation of Tabriz Sprawl Growth using Satellite Images and Probability Development ModelingEvaluation of Tabriz Sprawl Growth using Satellite Images and Probability Development Modeling1091242348710.22108/gep.2019.97447.0FAAkbarRahimiAssistant professor in Department of Landscape Engineering, agricultural Faculty, University of Tabriz, Tabriz, IranJournal Article20130310Urbanization is one of the main consequences of the Industrial Revolution, which has transformed the process of urbanization and expanded immigration to cities. One of the main results of the urbanization development in recent decades is land use change in cities and urban size growth, which has caused urban sprawl growth to be one of the most important challenges of spatial planning and has resulted in social and environmental damages. In recent years, planners, economists, ecologists and urban managers have used a variety of models to assess changes in user behavior and to examine the outcomes of these changes in the future, and these models are being developed day by day. The purpose of this research is to evaluate the past development of Tabriz and predict these changes in the future. The research method is descriptive-analytical, which is applied to the evaluation and modeling of a specific area using satellite imagery and other data and factors influencing past development and the future of the city. The LTM model, which combines the capabilities of artificial neural networks and geographic information systems, has been used in this research. At first, the data were prepared as raster and then in Acsi format. After evaluating the past changes in neural networks, the results were prepared as raster maps. By selecting the learning pattern and network structure and the results of the urban development process, a possible development of the city of Tabriz for 2024 was prepared. The results of the evaluation a 10-year period (2006-2016) indicated the development of the periphery and sprawl of the city in Tabriz, which most of the surrounding Lands of the city have become urban structure, and with the continuation of this trend for the future development, most of the agricultural land and the periphery will change. The results of the possible development of the city in 2024 indicated that more than 3600 hectares of peripheral lands will be allocated to urban development, which will complicate Tabriz's urban problems and challenges, and continuing of the development of Urban Sprawl, not only increases environmental problems, but also increases the cost of development and management.Urbanization is one of the main consequences of the Industrial Revolution, which has transformed the process of urbanization and expanded immigration to cities. One of the main results of the urbanization development in recent decades is land use change in cities and urban size growth, which has caused urban sprawl growth to be one of the most important challenges of spatial planning and has resulted in social and environmental damages. In recent years, planners, economists, ecologists and urban managers have used a variety of models to assess changes in user behavior and to examine the outcomes of these changes in the future, and these models are being developed day by day. The purpose of this research is to evaluate the past development of Tabriz and predict these changes in the future. The research method is descriptive-analytical, which is applied to the evaluation and modeling of a specific area using satellite imagery and other data and factors influencing past development and the future of the city. The LTM model, which combines the capabilities of artificial neural networks and geographic information systems, has been used in this research. At first, the data were prepared as raster and then in Acsi format. After evaluating the past changes in neural networks, the results were prepared as raster maps. By selecting the learning pattern and network structure and the results of the urban development process, a possible development of the city of Tabriz for 2024 was prepared. The results of the evaluation a 10-year period (2006-2016) indicated the development of the periphery and sprawl of the city in Tabriz, which most of the surrounding Lands of the city have become urban structure, and with the continuation of this trend for the future development, most of the agricultural land and the periphery will change. The results of the possible development of the city in 2024 indicated that more than 3600 hectares of peripheral lands will be allocated to urban development, which will complicate Tabriz's urban problems and challenges, and continuing of the development of Urban Sprawl, not only increases environmental problems, but also increases the cost of development and management.https://gep.ui.ac.ir/article_23487_7fc91c46b330ceac4ab3804be3dbb15a.pdfUniversity of IsfahanGeography and Environmental Planning2008-536229420190408Application of Multilayer Perceptron Neural Network Method in Land Use Change Modeling in the East of Mzandaran ProvinceApplication of Multilayer Perceptron Neural Network Method in Land Use Change Modeling in the East of Mzandaran Province1251442351810.22108/gep.2019.97390.0FASharifJoorabian Shooshtari1 Department of Environment, Faculty of Natural Resources, Tarbiat Modares University, Tehran, IranAbbasEsmaili-Sari2 Department of Environment, Faculty of Natural Resources, Tarbiat Modares University, Tehran, IranSeyed MohsenHosseini3 Department of Forestry, Faculty of Natural Resources, Tarbiat Modares University, Tehran, IranMehdiGholamalifard4 Department of Environment, Faculty of Natural Resources, Tarbiat Modares University, Tehran, IranJournal Article20121226This study was performed with objective of predicting land cover change in the east of Mazandaran Province (Neka and Behshahr counties), using Artificial Neural Network in the GIS environment. Landsat imagery belonging to the years 1987 and 2001 was used for change detection. Then, using Multilayer Perceptron neural network transition potentials was implemented for 7 sub-models and finally, land cover change modeling for 2006 with 1987-2001 calibration period and by Markov Chain and hard prediction was run. The accuracy of the assessment model was determined by using the Null Successes, Hits, False Alarms, and Misses. Finally, land cover change prediction was done for 2015. The result showed that during 1987–2001, respectively, 1964 and 1197 ha from forest and orchard were reduced, and 1182 and 1978 ha agriculture and residential were added. The results showed high accuracy (67-89%) in all the sub-models. Total error prediction model was 9.98%. Furthermore, the prediction results showed that forest areas will be reduced and residential, agriculture and orchard will be increased in 2015 compared with 2006.This study was performed with objective of predicting land cover change in the east of Mazandaran Province (Neka and Behshahr counties), using Artificial Neural Network in the GIS environment. Landsat imagery belonging to the years 1987 and 2001 was used for change detection. Then, using Multilayer Perceptron neural network transition potentials was implemented for 7 sub-models and finally, land cover change modeling for 2006 with 1987-2001 calibration period and by Markov Chain and hard prediction was run. The accuracy of the assessment model was determined by using the Null Successes, Hits, False Alarms, and Misses. Finally, land cover change prediction was done for 2015. The result showed that during 1987–2001, respectively, 1964 and 1197 ha from forest and orchard were reduced, and 1182 and 1978 ha agriculture and residential were added. The results showed high accuracy (67-89%) in all the sub-models. Total error prediction model was 9.98%. Furthermore, the prediction results showed that forest areas will be reduced and residential, agriculture and orchard will be increased in 2015 compared with 2006.https://gep.ui.ac.ir/article_23518_329c9578a8b1e18c875476dd9c493647.pdfUniversity of IsfahanGeography and Environmental Planning2008-536229420190220Spatial Analysis and Capability Assessment of Tourism Susceptible Zones in Fasa CountySpatial Analysis and Capability Assessment of Tourism Susceptible Zones in Fasa County1451682363310.22108/gep.2019.115384.1116FASayed HojjatMousaviAssistant Professor, Department of Geography and Ecotourism, Faculty of Natural Resources and Geosciences, University of Kashan, Kashan, I.R. IranNajmehNazariMSc Student of Ecotourism, Department of Geography and Ecotourism, Faculty of Natural Resources and Geosciences, University of Kashan, Kashan, IranYonesGholamiAssistant Professor of Geography and Ecotourism Department, Faculty of Natural Resources and Geosciences, University of Kashan, Kashan, Iran.Journal Article20190130Tourism has a close relationship with the environmental capabilities, therefore, the feasibility assessment of tourism susceptible zones can help identify capacity, refine development plans, and preserve the environment and sustainable development. Thus, the purpose of this research is to evaluate the potential of tourism development and zoning in Fasa County through spatial analysis of tourism attractions. This process is based on the following steps: (1) spatial analysis of historical, cultural, religious, scientific, rural and natural attractions based on the density of tourist resources, (2) the zoning of mountain sport tourism, and (3) the zoning of agricultural tourism. In this regard, initially, tourism susceptible zones were presented by identifying various types of attractions, determining the spatial location, categorizing and density of them in an area, and then separating the areas with maximum densities. In order to zoning the sport tourism, the roughness factor in the form of slope more than 25% and elevations above 1700 m were used. The zonation of agricultural tourism was based on the vegetation areas with a Normalized Difference Vegetation Index more than 0.05. The results showed that an area with 2606.69 km2 (62.11%) of the whole Fasa County is suitable for various types of tourism, which among them, sport, natural, sports-natural, historical-cultural-rural and historical-cultural-rural-natural zones have the highest extent with area of 1479.95, 267.05, 225.82, 132.89 and 129.35 km2 (35.26, 6.36, 5.38, 3.17 and 3.08 percent), respectively. In conclusion, the results of the study show the spatial graphic representation of Fasa County in the form of susceptible zones of various tourism, which, on the one hand, can provide a comprehensive guide for tourists and tour leaders, and on the one hand, can be a scientific document for managers and planners for constructive decisions and implementation of developmental policies.Tourism has a close relationship with the environmental capabilities, therefore, the feasibility assessment of tourism susceptible zones can help identify capacity, refine development plans, and preserve the environment and sustainable development. Thus, the purpose of this research is to evaluate the potential of tourism development and zoning in Fasa County through spatial analysis of tourism attractions. This process is based on the following steps: (1) spatial analysis of historical, cultural, religious, scientific, rural and natural attractions based on the density of tourist resources, (2) the zoning of mountain sport tourism, and (3) the zoning of agricultural tourism. In this regard, initially, tourism susceptible zones were presented by identifying various types of attractions, determining the spatial location, categorizing and density of them in an area, and then separating the areas with maximum densities. In order to zoning the sport tourism, the roughness factor in the form of slope more than 25% and elevations above 1700 m were used. The zonation of agricultural tourism was based on the vegetation areas with a Normalized Difference Vegetation Index more than 0.05. The results showed that an area with 2606.69 km2 (62.11%) of the whole Fasa County is suitable for various types of tourism, which among them, sport, natural, sports-natural, historical-cultural-rural and historical-cultural-rural-natural zones have the highest extent with area of 1479.95, 267.05, 225.82, 132.89 and 129.35 km2 (35.26, 6.36, 5.38, 3.17 and 3.08 percent), respectively. In conclusion, the results of the study show the spatial graphic representation of Fasa County in the form of susceptible zones of various tourism, which, on the one hand, can provide a comprehensive guide for tourists and tour leaders, and on the one hand, can be a scientific document for managers and planners for constructive decisions and implementation of developmental policies.https://gep.ui.ac.ir/article_23633_0cb261b306ffcfc7718c4863999c7e34.pdf