University of Isfahan Geography and Environmental Planning 2008-5362 31 3 2020 09 22 Assessment of Opportunities and Future Capabilities of Sports Tourism Based on Spatial Planning Approach (Case Study: Lorestan Province) Assessment of Opportunities and Future Capabilities of Sports Tourism Based on Spatial Planning Approach (Case Study: Lorestan Province) 1 20 25158 10.22108/gep.2020.125139.1357 FA Hedayat Darvishi PhD, Department of Human Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran Siyamack Sharafi Assistant Professor, Department of Geography, Faculty of Literature and Human Sciences, Lorestan University, Khorramabad, Iran Maryam Beyranvandzadeh Researcher of Academic Center for Education, Culture, and Research (ACECR), Lorestan Branch, Lorestan, Iran Journal Article 2020 09 28 1. Introduction Tourism is one of the largest and most profitable industries in the world and is used as a development strategy in many countries. The tourism industry is the main source of income and employment in many countries. It also contributes to the growth of non-governmental industries and infrastructure development. Given the importance of the tourism industry in the economic development of countries, it is necessary to identify different types of this industry and pay special attention to the more important types. Sports tourism is one of the growing and popular types of the tourism industry, which has emerged from the link between tourism and sports. Sports tourism is a formal or informal journey that people make for entertainment like watching sports matches. This type of tourism has become one of the important business and economic strategies for income, employment, and infrastructure development in many counties. Statistical data show that the countries with good sports tourism conditions contribute to a large part of their economy by this type of tourism. However, sports tourism can have implications for tourist areas that may benefit from or incur the costs of this development. One of the ways to develop sports tourism is to recognize and use the factors affecting its development. Tourist attractions such as high mountains, snow-covered areas, waterfalls, large rivers, etc. are among the potentials that can be used to develop sports tourism. The purpose of this study is to identify the potentials of sports tourism and ways to develop them in the study area. 2. Methodology The present research was an applied study. It was conducted based on documentary-survey sources (researcher-made questionnaires). Using the available resources in the field of study, the most important components and criteria affecting the future opportunities and capabilities of sports tourism in Lorestan province were explored. In this regard, due to the diversity of contributing factors and to determine the consensus of thematic and local experts on each of the factors and the importance of each, the criteria have been reduced based on their importance. In this regard, the factors affecting sports tourism were identified by the experts by the Delphi questionnaire, and the data were analyzed using Mick Mac software. 3. Discussion The findings showed that out of a total of 22 factors, 3 factors were in the cluster of dependent variables, 2 variables were in the intermediate cluster, 5 variables were in the cluster of independent variables, and 12 variables were in the cluster of key variables. This shows the diversity of key drivers in creating opportunities commensurate with tourism potentials. In other words, from the total of mentioned variables, 50% of the drivers are strategic (key) drivers. Of the total effective factors in creating opportunities commensurate with the capabilities of sports tourism, 54.5% were in the cluster of tourism opportunities, and 45.4% in the cluster of sports tourism potentials. Moreover, 54.5% of the factors mentioned in the terms of ‘capability assessment’ and ‘opportunistic proportionality’ were key variables, 22.7% were independent, 13.6% were dependent, and 9.09% were in the cluster of neutral variables. In terms of ‘opportunity’, the factors of ‘tourism identification and extra-regional, national and international networking’, ‘information and advertising outside the region’, ‘opportunity making appropriate with the capability of sports-oriented tourism’, ‘investing in sports tourism in present and future’, ‘tourism development policies and strategies’, ‘tourism business model and structure’ were key factors. The factor of ‘branding (symbolization) and fame of sports tourism and nature tourism’ and ‘accompanying tourists by providing free incentives and facilities’ except for the dependent factor, the factors of ‘institution and organization of sports tourism’, ‘bedding of cheap air transit and network price’ and ‘national and international agencies’ were considered as independent factors. The allocation of advertising funds is considered as a neutral or intermediate factor. In terms of ‘capability’, the factors of ‘tourism stabilization’, ‘attractiveness for out-of-province tourists with the priority of neighboring tourists’, ‘change of aid from agriculture to tourism’, ‘the impact of beneficiaries in the development of sports tourism’, ‘inexpensive tourism’, ‘combined tourism (sports, natural tourism, ecotourism, geo-tourism)’ were of the key factors. ‘Local and indigenous cultural-social reception of tourism’ was a dependent factor, and ‘existing capacity of tourism structure’ and ‘governmental-dependent institutional skillful requirements’ were independent factors. 4. Conclusion Sports tourism is an emerging capability that has favorable spatial outcomes at sectoral, territorial, and organizational levels. This capability will have an objective-spatial reflection as a potential advantage when it creates an opportunity appropriate for this capability. In this regard, identifying the effective factors in the spatial development of sports tourism capabilities and future opportunities are essential. Therefore, 22 effective factors and drivers in utilizing the capabilities were identified and analyzed. In this regard, among the variables ‘opportunity’ and ‘capability’, the most influential factors in the current and future situation of sports tourism were the variable ‘opportunity’ with 54.5% and the variable ‘capability’ with 45.4%. This indicates that despite the sports tourism capabilities in the Lorestan Province, the variable ‘opportunity’ has a key role in future planning and achieving the desired spatial organization of sports tourism. The findings of the present study fill a gap in the research background, which can be considered in sports tourism. Major clustering of the effective factors in opportunities and the capabilities of sports tourism indicates that key drivers with 54% were significant. Independent variables with 23%, dependent with 14%, and intermediate variables with 9% were of the other contributing factors. Distribution analysis and the distribution of drivers by key, independent, dependent, and neutral factors indicates that the key factors that should be considered by planners and policymakers in formulating and designing spatial development scenarios for sports tourism are equally distributed in both variables of ‘opportunity’ and ‘capability’. This issue (the equal diversity of the key drivers) is also a new finding that can be considered in future planning related to sports tourism. Besides, among the key factors and drivers in the opportunity variable, ‘attractiveness factors for out-of-province tourists with the priority of neighboring tourists’ and in the capability variable of ‘tourism identity and extra-regional, national and international networking’ have the most impact. Keywords: Spatial Planning, Capability, Sports Tourism. References - Adami, M., & Panahi, H. (2016). Evaluating of Sports Tourism Development in East Azerbaijan Province. Journal of Applied Research in Sport Management, 4(4), 55-64. - Akbari, M., & Moradpoor, A. (2014). Tourism in Chabahar, an Opportunity for Sustainable Development (With Emphasis on Geotourism). Journal of Social Issues & Humanities, 2, 41-46. - Balali, M., Moein Fard, M. R., Hamedi Niya, M. R., & Amir Ahmadi, A. (2012). Investigating the Capacities of Sports Tourism in Khorasan Razavi Province. Journal of Arid Regions Geographic studies, 9(3), 87-100. - Brichi, L., Savari, F., Jalilvand, J., & Mehdipour, A. (2015). Identifying the Capabilities of Sports Tourism in Khuzestan Province. The First National Conference on New Achievements in Physical Education and Sports, International University of Chabahar. - Cho, K. M. (2001). Developing Taekwondo as a Tourist Commodity. International Journal of Applied Sports Sciences, 13(2), 53-62. - Country Planning and Budget Organization. (2016). Spatial Planning Zoning. Unpublished Report. - Darabi, M., Azizian Kohan, N., & Ghaffari, SH. (2015). Explaining the Strategy of Sports Tourism in Ardabil Province. 9th International Conference on Physical Education and Sports Sciences, Tehran. - Darabi, M., Keshtidar, M., Alizaiy_Yousef_Abadi, O., Heydari, R., & Nazari_Torshizi, A. (2020). Scenario Planning of the Future of Sports Tourism Industry in Mashhad. Annals of Applied Sport Science, 8(4), 1-13. - Deery, M., Jago, L., & Fredline, L. (2004). Sports Tourism or Event Tourism: Are They One and the Same?. Journal of Sport and Tourism, 9(3), 235-245. - Fallahi, A., Hassani, E., & Karoubi, M. (2015). Study of Natural Attractions Affecting the Development of Sports Tourism in Kurdistan Province. Journal of Sport Management Studies, 5(17), 159-174. - Farahani, A., Eslami, S., & Porsoltan Zarandi, H. (2017). Ranking the Employment Share of Sports Tourism Industry Factors in Development. Applied Research in Sport Management, 6(2), 107-113. - Fekrizad, N., & Vossoughi, L. (2017). Prioritization of Appropriate Areas for Developing Ecotourism in Talesh County, Using GIS & AHP. Journal of Spatial Planning, 6(4), 101-124. - Foroozanfar, M. H., Najafipour, A. A., Mohammad Abadi, M., & Rezaie, R. A. (2015). Presenting Sports Tourism Strategies, Challenges, and Guidelines in IRAN, International Journal of Research in Organizational Behavior and Human Resource Management, 3(1), 24-34. - Ghanbari, I. (2015). Identifying the Capabilities of Sports Tourism in Qazvin Province. Master Thesis, Supervisor: Ghodratollah Bagheri Ragheb, University of Tehran. - Giampiccoli, A., Lee, S. S., & Nauright, J. (2015). Destination South Africa: Comparing Global Sports Mega-Events and Recurring Localized Sports Events in South Africa for Tourism and Economic Development. Journal of Current Issues in Tourism, 18(3), 229-248. - Gibson, H. J., Lamont, M., Kennelly, M., & Buning, R. J. (2018). Introduction to the Special Issue Active Sports Tourism. Journal of Sport and Tourism, 22(2), 83-91. - Hamidi, M., Razavi, S. M. H., Amirnejhad, S., Shafieh Zadeh, SH., & Fazli Darzi, A. (2010). Explaining the Strategy of Sports Tourism in the Country (Iran). Journal of Sport Management and Motor Behavior, 6(12), 51-68. - Hasani, A., Rahimzadeh, M. (2019). Tehran Tourism industry foresight. Journal of Urban Tourism, 6(1), 135-148. - Higgins-Desbiolles, F. (2006). More than an ‘Industry’: The Forgotten Power of Tourism as a Social Force. Journal of Tourism Management, 27(6), 1192-1208. - Hinch, T., & Higham, J. (2005). Sport, Tourism, and Authenticity. European Sport Management Quarterly, 5(3), 243-256. - Khosravimehr, H., Ghadiri Masom, M., & Rezvani, M. R. (2017). Providing Sports Tourism Development Strategies (Case study: Minoodasht Township). Applied Research in Sport Management, 5(3), 105-115. - Kiani Salami, S., & Yehaneh Dastgherdi, P. (2016). Identifying Effective Factors and Prioritizing Sports Tourism Activities (Case Study: Chaharmahaland Bakhtiary Province). Journal of Tourism and Development, 5(2), 116-135. - Kim, N. S., & Chalip, L. (2004). Why Travel to the FIFA World Cup? Effects of Motives, Background, Interest, and Constraints. Tourism Management, 25(6), 695-707. - Lorestan Management and Planning Organization. (2020). Lorestan Province Spatial Planning Document. Unpublished Report. - Mapjabil, J., Marzuki, M., Kumalah, M. J., Tangavello, L., & Abidin, M. K. Z. (2017). Sport as a Tourism Attraction in Malaysia: Potential and Prospects. Geografia-Malaysian Journal of Society and Space, 11(12),23-31. - Masaeli, M., Farsani, N. T., & Mortazavi, M. (2020). A Study on Tourist Demand for Pahlevani and Zoorkhanei Rituals as Ancient Iranian Sport. Journal of Sport and Tourism, 24(1), 19-29. - Masoumi Janafard, I., Tabrizi, N., Ramezanzadeh, M. (2019). Feasibility of Developing Sports Tourism in Ardabil (Case Study: Alvares Ski Resort). MJSp , 22 (4), 28-54. - Meshkini, A., & Heidari, T. (2011). Evaluation of Tourism Development in Zanjan City Using SWOT Model (Case Study: Zanjan Rud Region). Journal of Geographic Space, 35, 64-37. - Miranda, J., & Andueza, J. (2005). The Role of Sport in the Tourism Destinations Chosen by Tourists Visiting Spain. Journal of Sport and Tourism, 10(2), 143-145. - Negahdari, F., & Nourani, T. (2015). Prioritizing the Effective Factors of the Development of Sports Tourism in Hormozgan Province Based on the Pistol Model. The First Conference on Accounting, Economics, and Innovation in Management, Bandar Abbas. - Sharafi, S. (2019). Basic Studies of Khorramabad-Poldakhtar Tourism Road. Cultural Heritage, Tourism and Handicrafts Organization of Lorestan Province, 1-405. - Shojaei, V., Tejari, F., Solaymani Tapeh Sari, B., & Dousti, M. (2012). Strategic Planning of Sports Tourism in Mazandaran Province. Journal of Geographic Space, 12(39), 173-194. - Taleghani, G. R., & Ghafary, A. (2014). Providing a Management Model for the Development of Sports Tourism. Procedia–Social and Behavioral Sciences, 120, 289-298. - Yarahmadi, D., & Sharafi, S. (2017). An Investigation of the Capacities and Attractions of Shiraz Valley Geotourism as a Future Geopark in Lorestan Province. Geographical Journal of Tourism Space, 6(21), 19-40. - Zeitounli, A., & Zeitounli, S. (2012). Identification of the Strengths, Weaknesses, Opportunities, and Threats Involved in Sports Tourism in Golestan. Quarterly Journal of Research in Sport Management, 1(3), 87-104. 1. Introduction Tourism is one of the largest and most profitable industries in the world and is used as a development strategy in many countries. The tourism industry is the main source of income and employment in many countries. It also contributes to the growth of non-governmental industries and infrastructure development. Given the importance of the tourism industry in the economic development of countries, it is necessary to identify different types of this industry and pay special attention to the more important types. Sports tourism is one of the growing and popular types of the tourism industry, which has emerged from the link between tourism and sports. Sports tourism is a formal or informal journey that people make for entertainment like watching sports matches. This type of tourism has become one of the important business and economic strategies for income, employment, and infrastructure development in many counties. Statistical data show that the countries with good sports tourism conditions contribute to a large part of their economy by this type of tourism. However, sports tourism can have implications for tourist areas that may benefit from or incur the costs of this development. One of the ways to develop sports tourism is to recognize and use the factors affecting its development. Tourist attractions such as high mountains, snow-covered areas, waterfalls, large rivers, etc. are among the potentials that can be used to develop sports tourism. The purpose of this study is to identify the potentials of sports tourism and ways to develop them in the study area. 2. Methodology The present research was an applied study. It was conducted based on documentary-survey sources (researcher-made questionnaires). Using the available resources in the field of study, the most important components and criteria affecting the future opportunities and capabilities of sports tourism in Lorestan province were explored. In this regard, due to the diversity of contributing factors and to determine the consensus of thematic and local experts on each of the factors and the importance of each, the criteria have been reduced based on their importance. In this regard, the factors affecting sports tourism were identified by the experts by the Delphi questionnaire, and the data were analyzed using Mick Mac software. 3. Discussion The findings showed that out of a total of 22 factors, 3 factors were in the cluster of dependent variables, 2 variables were in the intermediate cluster, 5 variables were in the cluster of independent variables, and 12 variables were in the cluster of key variables. This shows the diversity of key drivers in creating opportunities commensurate with tourism potentials. In other words, from the total of mentioned variables, 50% of the drivers are strategic (key) drivers. Of the total effective factors in creating opportunities commensurate with the capabilities of sports tourism, 54.5% were in the cluster of tourism opportunities, and 45.4% in the cluster of sports tourism potentials. Moreover, 54.5% of the factors mentioned in the terms of ‘capability assessment’ and ‘opportunistic proportionality’ were key variables, 22.7% were independent, 13.6% were dependent, and 9.09% were in the cluster of neutral variables. In terms of ‘opportunity’, the factors of ‘tourism identification and extra-regional, national and international networking’, ‘information and advertising outside the region’, ‘opportunity making appropriate with the capability of sports-oriented tourism’, ‘investing in sports tourism in present and future’, ‘tourism development policies and strategies’, ‘tourism business model and structure’ were key factors. The factor of ‘branding (symbolization) and fame of sports tourism and nature tourism’ and ‘accompanying tourists by providing free incentives and facilities’ except for the dependent factor, the factors of ‘institution and organization of sports tourism’, ‘bedding of cheap air transit and network price’ and ‘national and international agencies’ were considered as independent factors. The allocation of advertising funds is considered as a neutral or intermediate factor. In terms of ‘capability’, the factors of ‘tourism stabilization’, ‘attractiveness for out-of-province tourists with the priority of neighboring tourists’, ‘change of aid from agriculture to tourism’, ‘the impact of beneficiaries in the development of sports tourism’, ‘inexpensive tourism’, ‘combined tourism (sports, natural tourism, ecotourism, geo-tourism)’ were of the key factors. ‘Local and indigenous cultural-social reception of tourism’ was a dependent factor, and ‘existing capacity of tourism structure’ and ‘governmental-dependent institutional skillful requirements’ were independent factors. 4. Conclusion Sports tourism is an emerging capability that has favorable spatial outcomes at sectoral, territorial, and organizational levels. This capability will have an objective-spatial reflection as a potential advantage when it creates an opportunity appropriate for this capability. In this regard, identifying the effective factors in the spatial development of sports tourism capabilities and future opportunities are essential. Therefore, 22 effective factors and drivers in utilizing the capabilities were identified and analyzed. In this regard, among the variables ‘opportunity’ and ‘capability’, the most influential factors in the current and future situation of sports tourism were the variable ‘opportunity’ with 54.5% and the variable ‘capability’ with 45.4%. This indicates that despite the sports tourism capabilities in the Lorestan Province, the variable ‘opportunity’ has a key role in future planning and achieving the desired spatial organization of sports tourism. The findings of the present study fill a gap in the research background, which can be considered in sports tourism. Major clustering of the effective factors in opportunities and the capabilities of sports tourism indicates that key drivers with 54% were significant. Independent variables with 23%, dependent with 14%, and intermediate variables with 9% were of the other contributing factors. Distribution analysis and the distribution of drivers by key, independent, dependent, and neutral factors indicates that the key factors that should be considered by planners and policymakers in formulating and designing spatial development scenarios for sports tourism are equally distributed in both variables of ‘opportunity’ and ‘capability’. This issue (the equal diversity of the key drivers) is also a new finding that can be considered in future planning related to sports tourism. Besides, among the key factors and drivers in the opportunity variable, ‘attractiveness factors for out-of-province tourists with the priority of neighboring tourists’ and in the capability variable of ‘tourism identity and extra-regional, national and international networking’ have the most impact. Keywords: Spatial Planning, Capability, Sports Tourism. References - Adami, M., & Panahi, H. (2016). Evaluating of Sports Tourism Development in East Azerbaijan Province. Journal of Applied Research in Sport Management, 4(4), 55-64. - Akbari, M., & Moradpoor, A. (2014). Tourism in Chabahar, an Opportunity for Sustainable Development (With Emphasis on Geotourism). Journal of Social Issues & Humanities, 2, 41-46. - Balali, M., Moein Fard, M. R., Hamedi Niya, M. R., & Amir Ahmadi, A. (2012). Investigating the Capacities of Sports Tourism in Khorasan Razavi Province. Journal of Arid Regions Geographic studies, 9(3), 87-100. - Brichi, L., Savari, F., Jalilvand, J., & Mehdipour, A. (2015). Identifying the Capabilities of Sports Tourism in Khuzestan Province. The First National Conference on New Achievements in Physical Education and Sports, International University of Chabahar. - Cho, K. M. (2001). Developing Taekwondo as a Tourist Commodity. International Journal of Applied Sports Sciences, 13(2), 53-62. - Country Planning and Budget Organization. (2016). Spatial Planning Zoning. Unpublished Report. - Darabi, M., Azizian Kohan, N., & Ghaffari, SH. (2015). Explaining the Strategy of Sports Tourism in Ardabil Province. 9th International Conference on Physical Education and Sports Sciences, Tehran. - Darabi, M., Keshtidar, M., Alizaiy_Yousef_Abadi, O., Heydari, R., & Nazari_Torshizi, A. (2020). Scenario Planning of the Future of Sports Tourism Industry in Mashhad. Annals of Applied Sport Science, 8(4), 1-13. - Deery, M., Jago, L., & Fredline, L. (2004). Sports Tourism or Event Tourism: Are They One and the Same?. Journal of Sport and Tourism, 9(3), 235-245. - Fallahi, A., Hassani, E., & Karoubi, M. (2015). Study of Natural Attractions Affecting the Development of Sports Tourism in Kurdistan Province. Journal of Sport Management Studies, 5(17), 159-174. - Farahani, A., Eslami, S., & Porsoltan Zarandi, H. (2017). Ranking the Employment Share of Sports Tourism Industry Factors in Development. Applied Research in Sport Management, 6(2), 107-113. - Fekrizad, N., & Vossoughi, L. (2017). Prioritization of Appropriate Areas for Developing Ecotourism in Talesh County, Using GIS & AHP. Journal of Spatial Planning, 6(4), 101-124. - Foroozanfar, M. H., Najafipour, A. A., Mohammad Abadi, M., & Rezaie, R. A. (2015). Presenting Sports Tourism Strategies, Challenges, and Guidelines in IRAN, International Journal of Research in Organizational Behavior and Human Resource Management, 3(1), 24-34. - Ghanbari, I. (2015). Identifying the Capabilities of Sports Tourism in Qazvin Province. Master Thesis, Supervisor: Ghodratollah Bagheri Ragheb, University of Tehran. - Giampiccoli, A., Lee, S. S., & Nauright, J. (2015). Destination South Africa: Comparing Global Sports Mega-Events and Recurring Localized Sports Events in South Africa for Tourism and Economic Development. Journal of Current Issues in Tourism, 18(3), 229-248. - Gibson, H. J., Lamont, M., Kennelly, M., & Buning, R. J. (2018). Introduction to the Special Issue Active Sports Tourism. Journal of Sport and Tourism, 22(2), 83-91. - Hamidi, M., Razavi, S. M. H., Amirnejhad, S., Shafieh Zadeh, SH., & Fazli Darzi, A. (2010). Explaining the Strategy of Sports Tourism in the Country (Iran). Journal of Sport Management and Motor Behavior, 6(12), 51-68. - Hasani, A., Rahimzadeh, M. (2019). Tehran Tourism industry foresight. Journal of Urban Tourism, 6(1), 135-148. - Higgins-Desbiolles, F. (2006). More than an ‘Industry’: The Forgotten Power of Tourism as a Social Force. Journal of Tourism Management, 27(6), 1192-1208. - Hinch, T., & Higham, J. (2005). Sport, Tourism, and Authenticity. European Sport Management Quarterly, 5(3), 243-256. - Khosravimehr, H., Ghadiri Masom, M., & Rezvani, M. R. (2017). Providing Sports Tourism Development Strategies (Case study: Minoodasht Township). Applied Research in Sport Management, 5(3), 105-115. - Kiani Salami, S., & Yehaneh Dastgherdi, P. (2016). Identifying Effective Factors and Prioritizing Sports Tourism Activities (Case Study: Chaharmahaland Bakhtiary Province). Journal of Tourism and Development, 5(2), 116-135. - Kim, N. S., & Chalip, L. (2004). Why Travel to the FIFA World Cup? Effects of Motives, Background, Interest, and Constraints. Tourism Management, 25(6), 695-707. - Lorestan Management and Planning Organization. (2020). Lorestan Province Spatial Planning Document. Unpublished Report. - Mapjabil, J., Marzuki, M., Kumalah, M. J., Tangavello, L., & Abidin, M. K. Z. (2017). Sport as a Tourism Attraction in Malaysia: Potential and Prospects. Geografia-Malaysian Journal of Society and Space, 11(12),23-31. - Masaeli, M., Farsani, N. T., & Mortazavi, M. (2020). A Study on Tourist Demand for Pahlevani and Zoorkhanei Rituals as Ancient Iranian Sport. Journal of Sport and Tourism, 24(1), 19-29. - Masoumi Janafard, I., Tabrizi, N., Ramezanzadeh, M. (2019). Feasibility of Developing Sports Tourism in Ardabil (Case Study: Alvares Ski Resort). MJSp , 22 (4), 28-54. - Meshkini, A., & Heidari, T. (2011). Evaluation of Tourism Development in Zanjan City Using SWOT Model (Case Study: Zanjan Rud Region). Journal of Geographic Space, 35, 64-37. - Miranda, J., & Andueza, J. (2005). The Role of Sport in the Tourism Destinations Chosen by Tourists Visiting Spain. Journal of Sport and Tourism, 10(2), 143-145. - Negahdari, F., & Nourani, T. (2015). Prioritizing the Effective Factors of the Development of Sports Tourism in Hormozgan Province Based on the Pistol Model. The First Conference on Accounting, Economics, and Innovation in Management, Bandar Abbas. - Sharafi, S. (2019). Basic Studies of Khorramabad-Poldakhtar Tourism Road. Cultural Heritage, Tourism and Handicrafts Organization of Lorestan Province, 1-405. - Shojaei, V., Tejari, F., Solaymani Tapeh Sari, B., & Dousti, M. (2012). Strategic Planning of Sports Tourism in Mazandaran Province. Journal of Geographic Space, 12(39), 173-194. - Taleghani, G. R., & Ghafary, A. (2014). Providing a Management Model for the Development of Sports Tourism. Procedia–Social and Behavioral Sciences, 120, 289-298. - Yarahmadi, D., & Sharafi, S. (2017). An Investigation of the Capacities and Attractions of Shiraz Valley Geotourism as a Future Geopark in Lorestan Province. Geographical Journal of Tourism Space, 6(21), 19-40. - Zeitounli, A., & Zeitounli, S. (2012). Identification of the Strengths, Weaknesses, Opportunities, and Threats Involved in Sports Tourism in Golestan. Quarterly Journal of Research in Sport Management, 1(3), 87-104.

https://gep.ui.ac.ir/article_25158_379e932fb51b1be60e51bb869a341e7d.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 31 3 2020 09 22 Monitoring the Desertification Trend in the Areas Surrounding Lake Urmia (2000-2018) Monitoring the Desertification Trend in the Areas Surrounding Lake Urmia (2000-2018) 21 40 25167 10.22108/gep.2020.121458.1264 FA Fatemeh Khodaei Geshlag PhD Candidate in Geomorphology, University of Tabriz, Tabriz, Iran Shahram Roostaei Professor of Geomorphology, University of Tabriz, Tabriz, Iran (*Corresponding Author Email: roostaei@tabrizu.ac.ir) Davod Mokhtari Professor of Geomorphology University of Tabriz, Tabriz, Iran Journal Article 2020 02 04 Extended Abstract Introduction According to the First World Conference on Deserts and Desertification, desertification refers to the destruction and degradation of natural ecosystems in arid, semi-arid, and sub-humid arid regions, which results in lower biomass production and the emergence of soil erosion (Ekhtesasi et al., 2011). Desertification results from natural factors such as climate variables and anthropogenic activities (Binal et al, 2018; Claado et al, 2002) and its impact on ecological processes is enormous and complex. Therefore, counteracting desertification is necessary to maintain long-term soil fertility in arid areas of the world. The present study aimed at evaluating desertification trends in the areas surrounding Lake Urmia in the period from 2000 to 2018. The main objectives of this study were 1) identification of the most suitable spectral index pair of desertification in the study area during the study period, taking into account the statistical relations; 2) mapping the desertification risk for the study period and the assessment of desertification trend in the study area by using the spectral biophysical indices such as normalized difference vegetation index (NDVI), surface albedo, Tasseled cap along with three components of brightness, Wetness, and greenness, and 3) identifying the most important factor that caused desertification in the study area by using the logistic regression model. Methodology In the present study, first, three frames of Landsat 5 TM sensor and seven frames of Sentinel 2 images were downloaded and analyzed by ENVI5.3 and QGIS software for July 2000 and 2018. In the next step, spectral indices of desertification, including the normalized difference vegetation index (NDVI), surface albedo, Tasseled Cap (including three components of brightness coefficient, Wetness, and greenness) were extracted for the study period. Thereafter, using the statistical relations and the determination coefficient, the most suitable spectral index pair of desertification in the study area was identified. After the identification of suitable spectral index pairs, the selected spectral index pair was normalized and the desertification mapping was performed for the years 2000 and 2018 taking into account the obtained gradient by using the linear regression relation. Finally, by applying the statistical change detection method, changes in the class's risk were investigated and using the Logistic Regression model, the most effective factor in the occurrence of desertification was identified. Discussion The normalized difference vegetation index (NDVI), wetness, and greenness were considered as the independent variables and surface albedo and brightness coefficient as dependent variables. The pairs of NDVI-Albedo spectral indicators have a positive correlation, but two spectral index pairs of humidity-brightness coefficient and brightness coefficient-greenness due to having a negative correlation were selected as the desertification index pairs and then normalized in the next step through the relevant relations. After mapping the desertification risk according to the index pairs of brightness coefficient-greenness and humidity-brightness, the combined map of desertification was obtained using line slope from the normalized relationship of the selected index pair and overlay function for the years 2000 and 2018 in 5 classes of non-desertification, weak, moderate, severe, and relatively severe desertification risks. To verify the results, using the classification algorithm, the Maximum Likelihood Algorithm and the Error Matrix were obtained, and the algorithm, with the accuracy of 91.96 and the kappa coefficient of 0.95 for 2000, and accuracy of 91.25 and a kappa coefficient of 0.89 for 2018 indicated a good correlation between the obtained results and the real-world data. Conclusion The results of this study were as follows: A) The two spectral index pairs of humidity-brightness coefficient and brightness coefficient-greenness were selected as the most suitable desertification indices in the study area, and therefore, the desertification risk maps were obtained through using this spectral index pair, B) The classification algorithm showed the highest degree of similarity with the accuracy of 91.96 and the kappa coefficient of 0.95 for the maps of 2000, and accuracy of 91.25 and a kappa coefficient of 0.89 for the maps of 2018, which indicated a good correlation between the obtained results and the real-world data, C) According to the results of statistical change detection analysis method, the areas of severe, relatively severe, and moderate desertification risk classes were increasing from 2000 to 2018, D) The desertification risk maps of 2000 and 2018 showed that the lands on the eastern coast, and especially on the southeast of the Lake Urmia, and the areas at the marginal edge of Tabriz Plain, overlooking the Lake Urmia were more sensitive to the desertification risk, and showed more severe degradation, compared to those on the west coast of Lake Urmia, F) Indicators such as underground water electric conductivity, chlorine index of underground water, Sodium adsorption ratio, drought index, Percentage of vegetation, had a high impact on the occurrence of desertification. Keywords: Desertification Monitoring, Lake Urmia, ENVI 5.3, Logistic Regression, Maximum Likelihood Algorithm. References: - Binal A., Christian, P. S., & Dhinwa, A. (2018). Long-term Monitoring and Assessment of Desertification Processes Using Medium and High Resolution Satellite Data. Journal of Applied Geography, 97, 10-24. - Boali, A. H., Jafari, R., & Bashari, H. (2016). Boali, A. H., Jafari, R., & Bashari, H. (2017). Analyzing the Effect of Groundwater Quality on Desertification using Bayesian Belief Networks in Segzi Desertification Hotspot. JWSS-Isfahan University of Technology, 21(3), 205-218. - Collado, A. D., Chuvieco, E., & Camarasa, A. (2002). Satellite Remote Sensing Analysis to Monitor Desertification Processes in the Crop-rangeland Boundary of Argentina. Journal of Arid Environments, 52(1), 121-133. - Cui, G., Lee, W. K., Kwak, D. A., Choi, S., Park, T., & Lee, J. (2011). Desertification Monitoring by LANDSAT TM Satellite Imagery. Journal of Forest Science and Technology, 7(3), 110-116. - Davri, S., Rashki, A. R., Akbari, M., Talebanfard, A.A. (2018). Monitoring of Spatio-Temporal Indices on Desertification in Arid Regions of South of Khorasan Razavi Province. Journal of RS & GIS for Natural Resources, (9)2, 17-30. - Ekhtesasi, M. R., & Sepehr, A. (2011). Methods and Models of Desertification Assessment and Mapping. Yazd: Yazd University Press. - Foody, G. M. (2002). Status of Land Cover Classification Accuracy Assessment. Journal of Remote Sensing of Environment, (80)1, 185-201. - Hasheminasab, S. & Jafari, R. (2018). Evaluation of Land Use Changes to Desertification Monitoring Using Remote Sensing Techniques. Journal of Spatial Analysis Environmental Hazard, (5)3, 67-82. - Jedari Eyvazi, J. (1982). Geomorphological Characters of Kabudan Desert. Journal of Research of geography, University of Tehran, 18, 1-27. - Kundu, A., Patel, N. R., Saha, S. K., & Dutta, D. (2014). Monitoring the Extent of Desertification Processes in Western Rajasthan (India) Using Geo-Information Science. Journal of Arab Geoscience, (8)8, 5727-5737. - Lamqadem, A. A., Hafid, S., & Biswajeet, P. (2018). Quantitative Assessment of Desertification in an Arid, Oasis Using Remote Sensing Data and Spectral. Journal of Remote Sensing, 10, 1-18. - Liangliang, J., Guli, J., Anming, B., Alishir, K., Hao, G., Guoxiong, Z., & Philippe De, M. (2019). Monitoring the Long-Term Desertification Process and Assessing the Relative Roles of Its Drivers in Central Asia. Ecological Indicators, 104(1), 195-208. - Masoudi, M., Parviz, J., & Biswajeet, P. (2018). A New Approach for Land Degradation and Desertiﬁcation Assessment Using Geospatial Techniques. Natural Hazards and Earth System Sciences, 18, 1133–1140. - Rahimi, Hossein (2012), Spatial-Spatial Modeling of Land Cover Changes by Combining Markov Chain Analysis, Artificial Neural Networks, and Automated Cells (Case Study: Eastern Part of Tabriz Plain). PhD Thesis, Faculty of Planning and Environmental Sciences, University of Tabriz. - Soltanian, M., & Halabian A. H. (2018). Application of Remote Sensing in the Environmental Science (Method of satellite Processing in ENVI). Isfahan: University of Isfahan Press. - Tavosi, T., Shojae, F., Akbari, E., & Asgari, E. (2016). Assessment of Land Use Change and Analysis Process Climate Desertification Wetland of Gavkhyny. Geographical Space Journal, (16)56, 79-94. - Xu, D., Kang, X., Qiu, D., Zhuang, D., & Pan, J. (2009). Quantitative Assessment of Desertification Using Landsat Data on a Regional Scale- A Case Study in the Ordos Plateau, China. Journal of Sensors, (9)3, 1738-1753. Extended Abstract Introduction According to the First World Conference on Deserts and Desertification, desertification refers to the destruction and degradation of natural ecosystems in arid, semi-arid, and sub-humid arid regions, which results in lower biomass production and the emergence of soil erosion (Ekhtesasi et al., 2011). Desertification results from natural factors such as climate variables and anthropogenic activities (Binal et al, 2018; Claado et al, 2002) and its impact on ecological processes is enormous and complex. Therefore, counteracting desertification is necessary to maintain long-term soil fertility in arid areas of the world. The present study aimed at evaluating desertification trends in the areas surrounding Lake Urmia in the period from 2000 to 2018. The main objectives of this study were 1) identification of the most suitable spectral index pair of desertification in the study area during the study period, taking into account the statistical relations; 2) mapping the desertification risk for the study period and the assessment of desertification trend in the study area by using the spectral biophysical indices such as normalized difference vegetation index (NDVI), surface albedo, Tasseled cap along with three components of brightness, Wetness, and greenness, and 3) identifying the most important factor that caused desertification in the study area by using the logistic regression model. Methodology In the present study, first, three frames of Landsat 5 TM sensor and seven frames of Sentinel 2 images were downloaded and analyzed by ENVI5.3 and QGIS software for July 2000 and 2018. In the next step, spectral indices of desertification, including the normalized difference vegetation index (NDVI), surface albedo, Tasseled Cap (including three components of brightness coefficient, Wetness, and greenness) were extracted for the study period. Thereafter, using the statistical relations and the determination coefficient, the most suitable spectral index pair of desertification in the study area was identified. After the identification of suitable spectral index pairs, the selected spectral index pair was normalized and the desertification mapping was performed for the years 2000 and 2018 taking into account the obtained gradient by using the linear regression relation. Finally, by applying the statistical change detection method, changes in the class's risk were investigated and using the Logistic Regression model, the most effective factor in the occurrence of desertification was identified. Discussion The normalized difference vegetation index (NDVI), wetness, and greenness were considered as the independent variables and surface albedo and brightness coefficient as dependent variables. The pairs of NDVI-Albedo spectral indicators have a positive correlation, but two spectral index pairs of humidity-brightness coefficient and brightness coefficient-greenness due to having a negative correlation were selected as the desertification index pairs and then normalized in the next step through the relevant relations. After mapping the desertification risk according to the index pairs of brightness coefficient-greenness and humidity-brightness, the combined map of desertification was obtained using line slope from the normalized relationship of the selected index pair and overlay function for the years 2000 and 2018 in 5 classes of non-desertification, weak, moderate, severe, and relatively severe desertification risks. To verify the results, using the classification algorithm, the Maximum Likelihood Algorithm and the Error Matrix were obtained, and the algorithm, with the accuracy of 91.96 and the kappa coefficient of 0.95 for 2000, and accuracy of 91.25 and a kappa coefficient of 0.89 for 2018 indicated a good correlation between the obtained results and the real-world data. Conclusion The results of this study were as follows: A) The two spectral index pairs of humidity-brightness coefficient and brightness coefficient-greenness were selected as the most suitable desertification indices in the study area, and therefore, the desertification risk maps were obtained through using this spectral index pair, B) The classification algorithm showed the highest degree of similarity with the accuracy of 91.96 and the kappa coefficient of 0.95 for the maps of 2000, and accuracy of 91.25 and a kappa coefficient of 0.89 for the maps of 2018, which indicated a good correlation between the obtained results and the real-world data, C) According to the results of statistical change detection analysis method, the areas of severe, relatively severe, and moderate desertification risk classes were increasing from 2000 to 2018, D) The desertification risk maps of 2000 and 2018 showed that the lands on the eastern coast, and especially on the southeast of the Lake Urmia, and the areas at the marginal edge of Tabriz Plain, overlooking the Lake Urmia were more sensitive to the desertification risk, and showed more severe degradation, compared to those on the west coast of Lake Urmia, F) Indicators such as underground water electric conductivity, chlorine index of underground water, Sodium adsorption ratio, drought index, Percentage of vegetation, had a high impact on the occurrence of desertification. Keywords: Desertification Monitoring, Lake Urmia, ENVI 5.3, Logistic Regression, Maximum Likelihood Algorithm. References: - Binal A., Christian, P. S., & Dhinwa, A. (2018). Long-term Monitoring and Assessment of Desertification Processes Using Medium and High Resolution Satellite Data. Journal of Applied Geography, 97, 10-24. - Boali, A. H., Jafari, R., & Bashari, H. (2016). Boali, A. H., Jafari, R., & Bashari, H. (2017). Analyzing the Effect of Groundwater Quality on Desertification using Bayesian Belief Networks in Segzi Desertification Hotspot. JWSS-Isfahan University of Technology, 21(3), 205-218. - Collado, A. D., Chuvieco, E., & Camarasa, A. (2002). Satellite Remote Sensing Analysis to Monitor Desertification Processes in the Crop-rangeland Boundary of Argentina. Journal of Arid Environments, 52(1), 121-133. - Cui, G., Lee, W. K., Kwak, D. A., Choi, S., Park, T., & Lee, J. (2011). Desertification Monitoring by LANDSAT TM Satellite Imagery. Journal of Forest Science and Technology, 7(3), 110-116. - Davri, S., Rashki, A. R., Akbari, M., Talebanfard, A.A. (2018). Monitoring of Spatio-Temporal Indices on Desertification in Arid Regions of South of Khorasan Razavi Province. Journal of RS & GIS for Natural Resources, (9)2, 17-30. - Ekhtesasi, M. R., & Sepehr, A. (2011). Methods and Models of Desertification Assessment and Mapping. Yazd: Yazd University Press. - Foody, G. M. (2002). Status of Land Cover Classification Accuracy Assessment. Journal of Remote Sensing of Environment, (80)1, 185-201. - Hasheminasab, S. & Jafari, R. (2018). Evaluation of Land Use Changes to Desertification Monitoring Using Remote Sensing Techniques. Journal of Spatial Analysis Environmental Hazard, (5)3, 67-82. - Jedari Eyvazi, J. (1982). Geomorphological Characters of Kabudan Desert. Journal of Research of geography, University of Tehran, 18, 1-27. - Kundu, A., Patel, N. R., Saha, S. K., & Dutta, D. (2014). Monitoring the Extent of Desertification Processes in Western Rajasthan (India) Using Geo-Information Science. Journal of Arab Geoscience, (8)8, 5727-5737. - Lamqadem, A. A., Hafid, S., & Biswajeet, P. (2018). Quantitative Assessment of Desertification in an Arid, Oasis Using Remote Sensing Data and Spectral. Journal of Remote Sensing, 10, 1-18. - Liangliang, J., Guli, J., Anming, B., Alishir, K., Hao, G., Guoxiong, Z., & Philippe De, M. (2019). Monitoring the Long-Term Desertification Process and Assessing the Relative Roles of Its Drivers in Central Asia. Ecological Indicators, 104(1), 195-208. - Masoudi, M., Parviz, J., & Biswajeet, P. (2018). A New Approach for Land Degradation and Desertiﬁcation Assessment Using Geospatial Techniques. Natural Hazards and Earth System Sciences, 18, 1133–1140. - Rahimi, Hossein (2012), Spatial-Spatial Modeling of Land Cover Changes by Combining Markov Chain Analysis, Artificial Neural Networks, and Automated Cells (Case Study: Eastern Part of Tabriz Plain). PhD Thesis, Faculty of Planning and Environmental Sciences, University of Tabriz. - Soltanian, M., & Halabian A. H. (2018). Application of Remote Sensing in the Environmental Science (Method of satellite Processing in ENVI). Isfahan: University of Isfahan Press. - Tavosi, T., Shojae, F., Akbari, E., & Asgari, E. (2016). Assessment of Land Use Change and Analysis Process Climate Desertification Wetland of Gavkhyny. Geographical Space Journal, (16)56, 79-94. - Xu, D., Kang, X., Qiu, D., Zhuang, D., & Pan, J. (2009). Quantitative Assessment of Desertification Using Landsat Data on a Regional Scale- A Case Study in the Ordos Plateau, China. Journal of Sensors, (9)3, 1738-1753.

https://gep.ui.ac.ir/article_25167_14debc57fb2d92b1a8c869b5c5169b03.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 31 3 2020 09 22 The Feasibility of the Environmental Strategy of Zero Carbon City in Shahrekord The Feasibility of the Environmental Strategy of Zero Carbon City in Shahrekord 41 60 25063 10.22108/gep.2020.122584.1291 FA Mostafa Mohammadi Associate Professor of Geography and Urban Planning, Faculty of Literature and Humanities, Shahid Chamran University of Ahvaz, Ahvaz, Iran Sohrab Ghaedi Assistant Professor of Geography and Urban Planning, Faculty of Literature and Humanities, Shahid Chamran University of Ahvaz, Ahvaz, Iran Neda Peyvand MA in Geography and Urban Planning, Faculty of Literature and Humanities, Shahid Chamran University of Ahvaz, Ahvaz, Iran. Journal Article 2020 04 17 Extended abstract 1- Introduction: One of the most important environmental issues is global climate change caused by the accumulation of greenhouse gases. In today's technological society, with the expansion of industrial activities, the increase in population growth, and urbanization, and the need for greater utilization of limited natural resources, pollution is increasing, especially in developing countries that do not have high technology to reduce air pollution and emission of pollutants. One of the most important of these pollutants is the role of greenhouse gas pollution. Greenhouse gases, including vapor, carbon dioxide, methane, nitrogen dioxide, monoxide, and ozone, which are natural emissions, are important for survival and only when their concentrations exceed the permissible limit. But it is human activity that has increased the levels of many of these gases. Iran is one of the first greenhouse-gas producing countries to change its temperature pattern, reduce water resources, increase seas, degrade coastal areas, destroy crops and food, destroy forests, alternate and intensify droughts. Greenhouse gases are naturally occurring in the atmosphere, but human activities and pollution caused by these activities increase the amount of gases abruptly. One of the new strategies for urban environmental sustainability and pollution control is the zero-carbon city, which is necessary for the sustainable development and development of each city. 2- Methodology: The present study is of theoretical, practical, and descriptive-analytical research methodology. The main objective of the study is to investigate the feasibility of the environmental strategy of the Zero-carbon city in Shahrekord. In this research, after the extraction of the indices, the Anp-Dematil combination method is the most important criterion and the environmental indicator of the Zero-carbon city in Shahrekord. Then, IPCC software was used to measure the ecological footprint in Shahrekord and was used for mapping the carbon dioxide dispersion map from the spatial satellite GIS Arc applications. 3– Discussion: The results of the present study indicate that the relative weights of indicators in Shahrekord have an environmental creativity index of 0.298, and urban design with a weight of 0.229 is among the most important and most stable index. The energy index with a weight of 0.107 is considered the most unstable index. The environmental index was recognized in this city. Also, to determine the ecological footprint of Shahrekord's carbon dioxide emissions per year (2018), 4.51 tons of carbon dioxide emissions are used. This amount is higher than the world scale, which is 4.47 tons and is lower compared to the Iranian scale, which is 6.76 tons per year. 4– Conclusion: The IPCC results showed that the energy index had the highest carbon dioxide production, increasing over a five-year period from 380983 tons in 2013 to 497237 tons in 2018 years, with transport reaching 119561 tons in 2013 to 275363 tons in 2018. Industry ranks third, from 24,292 tons in the year 2013 to 43,409 tons in 2018, and lastly from 5799 tons in 2013 to 12,136 tons in 2018. The crop has been the agricultural index which has declined from 36542 tons in 2013 to 25284 tons in 2018. Finally, using the national and international carbon dioxide emissions figures from the 2015 International Energy Agency report, we can say that Shahrekord's carbon dioxide emissions per capita in 2014 is 4.51 tons compared to the world scale of 4.47 tons. It is higher and lower than the Iranian scale of 6.76 tons per year. The results showed that the carbon footprint in Shahrekord is above the global average and lower than the Iranian average. Besides, the ecological footprint of carbon in Shahrekord is above the global average and below the Iranian average. The use of environmental strategies such as increasing urban green space and replacing renewable energy sources with fossil fuels in the city can be inadequate to reach the low carbon city in Shahrekord. Keywords: Environmental Zero Carbon City, Ecological Footprints, IPCC, Shahrekord. References: - Assefa, G., & Frostell, B. (2007). Social Sustainability and Social Acceptance in Technology Assessment: A Case Study of Energy Technologies. Technology in Society, 29(1): 63–78. - Baynes, T. M., & Wiedmann, T. (2012). General Approaches for Assessing Urban Environmental Sustainability. Current Opinion in Environmental Sustainability, 4(4): 458-464. - Brandon, P. S., & Patrizia, L. (2005). Evaluating Sustainable Development in the Built Environment. Oxford: Blackwell. - Chavez, A., & Ramaswami, A. (2013). Articulating a Trans-Boundary Infrastructure Supply Chain Greenhouse Gas Emission Footprint for Cities: Mathematical Relationships and Policy Relevance. Energy Policy, 54, 376-384. - Chu, X., Deng, X., Jin, G., Wang, Z., & Li, Z. (2017). Ecological Security Assessment Based on Ecological Footprint Approach in Beijing-Tianjin-Hebei Region, China. Physics and Chemistry of the Earth, Parts A/B/C, 101, 43-51. - Eckel, A. (2007). The Reality of Carbon Neutrality. Energetics, 21(2): 35-36. - Fong, W. K., Matsumoto, H., Ho, C. S., & Lun, Y. F. (2008). Energy Consumption and Carbon Dioxide Emission Considerations in the Urban Planning Process in Malaysia. The Journal of the Malaysia Institute of Planners, 6(1). - Grubb, E., & Ellis, C. (2007). Meeting the Carbon Challenge: The Role of Commercial Real Estate Owners. Chicago: Users and Managers. - Heinonen, J., & Junnila, S. (2011). A Carbon Consumption Comparison of Rural and Urban Lifestyles. Sustainability, 3(8): 1234-1249. - Hussain, M., Malik, R. N., & Taylor, A. (2017). Carbon Footprint as an Environmental Sustainability Indicator for the Particleboard Produced in Pakistan. Environmental Research, 155, 385-393. - IEA., World Energy Outlook. (2008). Fact Sheet. Paris: International Energy Agency. - Kennedy, S., & Sgouridis, S. (2011). Rigorous Classification and Carbon Accounting Principles for Low and Zero Carbon Cities. Energy Policy, 39(9): 5259-5268. - Li, X., Tian, M., Wang, H., Wang, H., & Yu, J. (2014). Development of an Ecological Security Evaluation Method Based on the Ecological Footprint and Application to a Typical Steppe Region in China. Ecological Indicators, 39, 153-159. - Mac, D., & Gordon, J. (2005). Environment: Evolution of a Concept-International Institute for Applied Systems Analysis. (IIASA). Page1. - Neira, M., Prüss-Ustün, A., & Mudu, P. (2018). Reduce Air Pollution to Beat NCDs: From Recognition to Action. Lancet (London, England), 392(10154), 1178. - Orosa, J. A. (Ed.). (2011). Indoor and Outdoor Air Pollution. Cambridge: BoD–Books on Demand. - Pandey, D., Agrawal, M. & Pandey, J. S. (2011). Carbon Footprint: Current Methods of Estimation. Environmental Monitoring and Assessment, 178 (1-4): 135-160. - Pandey, D., Agrawal, M., & Pandey, J. S. (2011). Carbon Footprint: Current Methods of Estimation. Environmental Monitoring and Assessment, 178(1-4), 135-160. - Steijger, L. A., Buswell, R. A., Smedley, V. A., Firth, S. K., & Rowley, P. (2013). Establishing the Zero-Carbon Performance of Compact Urban Dwellings. Journal of Building Performance Simulation, 6(4), 319-334. - Straatman, B., Boyd, B., Mangalagiu, D., Rathje, P., Madsen, C., Madsen, B., & Rasmussen, S. (2015). The Carbon City Index (CCI): A Consumption Based, Regional Input-Output Analysis of Carbon Emissions. (n.p). - Su, M. R., Chen, B., Xing, T., Chen, C., & Yang, Z. F. (2012). Development of Low-Carbon City in China: Where Will It Go?. Procedia Environmental Sciences, 13, 1143-1148. - Tjan, W., Tan, R. R., & Foo, D. C. (2010). A Graphical Representation of Carbon Footprint Reduction for Chemical Processes. Journal of Cleaner Production, 18(9), 848-856. - Walker, G., Karvonen, A., & Guy, S. (2015). Zero Carbon Homes and Zero Carbon Living: Sociomaterial Interdependencies in Carbon Governance. Transactions of the Institute of British Geographers, 40(4), 494-506. - Wiedmann, T., Minx, J. (2008). A Definition of 'Carbon Footprint'. In: Pertsova, C. C. (2008). Ecological Economics Research Trends. Chapter 1, 1-11. - Williams, I., Kemp, S., Coello, J., Turner, D. A., & Wright, L. A. (2012). A Beginner’s Guide to Carbon Foot Printing, Carbon Management, 3, 55–67. - World Bank and Institute for Health Metrics and Evaluation. (2016). The Cost of Air Pollution: Strengthening the Economic Case for Action. Washington DC: World Bank. License: Creative Commons Attribution CC BY 3.0 IGO. - Zhao, Y., Onat, N. C., Kucukvar, M., & Tatari, O. (2016). Carbon and Energy Footprints of Electric Delivery Trucks: A Hybrid Multi-Regional Input-Output Life Cycle Assessment. Transportation Research Part D: Transport and Environment, 47, 195-207. - Liu, Z. H., Yu, J. H., & Zhang, D. (2011). Study on Low-Carbon Building Ecological City Construction in Harmonious Beibu Gulf Culture. Procedia Environmental Sciences, 10, 1881-1886. Extended abstract 1- Introduction: One of the most important environmental issues is global climate change caused by the accumulation of greenhouse gases. In today's technological society, with the expansion of industrial activities, the increase in population growth, and urbanization, and the need for greater utilization of limited natural resources, pollution is increasing, especially in developing countries that do not have high technology to reduce air pollution and emission of pollutants. One of the most important of these pollutants is the role of greenhouse gas pollution. Greenhouse gases, including vapor, carbon dioxide, methane, nitrogen dioxide, monoxide, and ozone, which are natural emissions, are important for survival and only when their concentrations exceed the permissible limit. But it is human activity that has increased the levels of many of these gases. Iran is one of the first greenhouse-gas producing countries to change its temperature pattern, reduce water resources, increase seas, degrade coastal areas, destroy crops and food, destroy forests, alternate and intensify droughts. Greenhouse gases are naturally occurring in the atmosphere, but human activities and pollution caused by these activities increase the amount of gases abruptly. One of the new strategies for urban environmental sustainability and pollution control is the zero-carbon city, which is necessary for the sustainable development and development of each city. 2- Methodology: The present study is of theoretical, practical, and descriptive-analytical research methodology. The main objective of the study is to investigate the feasibility of the environmental strategy of the Zero-carbon city in Shahrekord. In this research, after the extraction of the indices, the Anp-Dematil combination method is the most important criterion and the environmental indicator of the Zero-carbon city in Shahrekord. Then, IPCC software was used to measure the ecological footprint in Shahrekord and was used for mapping the carbon dioxide dispersion map from the spatial satellite GIS Arc applications. 3– Discussion: The results of the present study indicate that the relative weights of indicators in Shahrekord have an environmental creativity index of 0.298, and urban design with a weight of 0.229 is among the most important and most stable index. The energy index with a weight of 0.107 is considered the most unstable index. The environmental index was recognized in this city. Also, to determine the ecological footprint of Shahrekord's carbon dioxide emissions per year (2018), 4.51 tons of carbon dioxide emissions are used. This amount is higher than the world scale, which is 4.47 tons and is lower compared to the Iranian scale, which is 6.76 tons per year. 4– Conclusion: The IPCC results showed that the energy index had the highest carbon dioxide production, increasing over a five-year period from 380983 tons in 2013 to 497237 tons in 2018 years, with transport reaching 119561 tons in 2013 to 275363 tons in 2018. Industry ranks third, from 24,292 tons in the year 2013 to 43,409 tons in 2018, and lastly from 5799 tons in 2013 to 12,136 tons in 2018. The crop has been the agricultural index which has declined from 36542 tons in 2013 to 25284 tons in 2018. Finally, using the national and international carbon dioxide emissions figures from the 2015 International Energy Agency report, we can say that Shahrekord's carbon dioxide emissions per capita in 2014 is 4.51 tons compared to the world scale of 4.47 tons. It is higher and lower than the Iranian scale of 6.76 tons per year. The results showed that the carbon footprint in Shahrekord is above the global average and lower than the Iranian average. Besides, the ecological footprint of carbon in Shahrekord is above the global average and below the Iranian average. The use of environmental strategies such as increasing urban green space and replacing renewable energy sources with fossil fuels in the city can be inadequate to reach the low carbon city in Shahrekord. Keywords: Environmental Zero Carbon City, Ecological Footprints, IPCC, Shahrekord. References: - Assefa, G., & Frostell, B. (2007). Social Sustainability and Social Acceptance in Technology Assessment: A Case Study of Energy Technologies. Technology in Society, 29(1): 63–78. - Baynes, T. M., & Wiedmann, T. (2012). General Approaches for Assessing Urban Environmental Sustainability. Current Opinion in Environmental Sustainability, 4(4): 458-464. - Brandon, P. S., & Patrizia, L. (2005). Evaluating Sustainable Development in the Built Environment. Oxford: Blackwell. - Chavez, A., & Ramaswami, A. (2013). Articulating a Trans-Boundary Infrastructure Supply Chain Greenhouse Gas Emission Footprint for Cities: Mathematical Relationships and Policy Relevance. Energy Policy, 54, 376-384. - Chu, X., Deng, X., Jin, G., Wang, Z., & Li, Z. (2017). Ecological Security Assessment Based on Ecological Footprint Approach in Beijing-Tianjin-Hebei Region, China. Physics and Chemistry of the Earth, Parts A/B/C, 101, 43-51. - Eckel, A. (2007). The Reality of Carbon Neutrality. Energetics, 21(2): 35-36. - Fong, W. K., Matsumoto, H., Ho, C. S., & Lun, Y. F. (2008). Energy Consumption and Carbon Dioxide Emission Considerations in the Urban Planning Process in Malaysia. The Journal of the Malaysia Institute of Planners, 6(1). - Grubb, E., & Ellis, C. (2007). Meeting the Carbon Challenge: The Role of Commercial Real Estate Owners. Chicago: Users and Managers. - Heinonen, J., & Junnila, S. (2011). A Carbon Consumption Comparison of Rural and Urban Lifestyles. Sustainability, 3(8): 1234-1249. - Hussain, M., Malik, R. N., & Taylor, A. (2017). Carbon Footprint as an Environmental Sustainability Indicator for the Particleboard Produced in Pakistan. Environmental Research, 155, 385-393. - IEA., World Energy Outlook. (2008). Fact Sheet. Paris: International Energy Agency. - Kennedy, S., & Sgouridis, S. (2011). Rigorous Classification and Carbon Accounting Principles for Low and Zero Carbon Cities. Energy Policy, 39(9): 5259-5268. - Li, X., Tian, M., Wang, H., Wang, H., & Yu, J. (2014). Development of an Ecological Security Evaluation Method Based on the Ecological Footprint and Application to a Typical Steppe Region in China. Ecological Indicators, 39, 153-159. - Mac, D., & Gordon, J. (2005). Environment: Evolution of a Concept-International Institute for Applied Systems Analysis. (IIASA). Page1. - Neira, M., Prüss-Ustün, A., & Mudu, P. (2018). Reduce Air Pollution to Beat NCDs: From Recognition to Action. Lancet (London, England), 392(10154), 1178. - Orosa, J. A. (Ed.). (2011). Indoor and Outdoor Air Pollution. Cambridge: BoD–Books on Demand. - Pandey, D., Agrawal, M. & Pandey, J. S. (2011). Carbon Footprint: Current Methods of Estimation. Environmental Monitoring and Assessment, 178 (1-4): 135-160. - Pandey, D., Agrawal, M., & Pandey, J. S. (2011). Carbon Footprint: Current Methods of Estimation. Environmental Monitoring and Assessment, 178(1-4), 135-160. - Steijger, L. A., Buswell, R. A., Smedley, V. A., Firth, S. K., & Rowley, P. (2013). Establishing the Zero-Carbon Performance of Compact Urban Dwellings. Journal of Building Performance Simulation, 6(4), 319-334. - Straatman, B., Boyd, B., Mangalagiu, D., Rathje, P., Madsen, C., Madsen, B., & Rasmussen, S. (2015). The Carbon City Index (CCI): A Consumption Based, Regional Input-Output Analysis of Carbon Emissions. (n.p). - Su, M. R., Chen, B., Xing, T., Chen, C., & Yang, Z. F. (2012). Development of Low-Carbon City in China: Where Will It Go?. Procedia Environmental Sciences, 13, 1143-1148. - Tjan, W., Tan, R. R., & Foo, D. C. (2010). A Graphical Representation of Carbon Footprint Reduction for Chemical Processes. Journal of Cleaner Production, 18(9), 848-856. - Walker, G., Karvonen, A., & Guy, S. (2015). Zero Carbon Homes and Zero Carbon Living: Sociomaterial Interdependencies in Carbon Governance. Transactions of the Institute of British Geographers, 40(4), 494-506. - Wiedmann, T., Minx, J. (2008). A Definition of 'Carbon Footprint'. In: Pertsova, C. C. (2008). Ecological Economics Research Trends. Chapter 1, 1-11. - Williams, I., Kemp, S., Coello, J., Turner, D. A., & Wright, L. A. (2012). A Beginner’s Guide to Carbon Foot Printing, Carbon Management, 3, 55–67. - World Bank and Institute for Health Metrics and Evaluation. (2016). The Cost of Air Pollution: Strengthening the Economic Case for Action. Washington DC: World Bank. License: Creative Commons Attribution CC BY 3.0 IGO. - Zhao, Y., Onat, N. C., Kucukvar, M., & Tatari, O. (2016). Carbon and Energy Footprints of Electric Delivery Trucks: A Hybrid Multi-Regional Input-Output Life Cycle Assessment. Transportation Research Part D: Transport and Environment, 47, 195-207. - Liu, Z. H., Yu, J. H., & Zhang, D. (2011). Study on Low-Carbon Building Ecological City Construction in Harmonious Beibu Gulf Culture. Procedia Environmental Sciences, 10, 1881-1886.

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University of Isfahan Geography and Environmental Planning 2008-5362 31 3 2020 09 22 Investigating the Relationship between Socio-Economic Poverty and Physical-Functional Deprivation in Isfahan Investigating the Relationship between Socio-Economic Poverty and Physical-Functional Deprivation in Isfahan 61 78 24947 10.22108/gep.2020.118816.1194 FA Homayoon Nooraie Assistant Professor in Urban and Regional Planning, College of Architecture and Urban Planning, Art University of Isfahan, Isfahan, Iran. Faezeh Shafi M.A.; Faculty of Architecture & Urban Planning, Daneshpajoohan Pishro Higher Education Institute, Isfahan, Iran Journal Article 2019 08 22 1) The forms and effects of urbanization are becoming more and more complex and widespread. In fact, the cities have a higher capacity for housing, prosperity and access to better living opportunities for people. However, urban poverty in the world is spreading rapidly and at a high rate, and despite different views on poverty and global and national programs to combat it, this problem remains a major threat and it confronts cities with effects of inefficiency (Asian Bank, 2014: 11). This issue is especially more important in developing countries (including Iran) and statistics show an increasing trend of inter-class distance and consequently the extent of relative poverty. Due to the mentioned necessity, a large number of thinkers in various fields of social sciences, geography, etc. have addressed the issue of poverty in various dimensions and this issue, along with the importance discussion of justice, has become one of the key issues of the era. Multidimensional poverty today also refers to the fact that poverty is more than inadequate income or deprivation of material resources, as well as the inability to access education, primary health care, clean drinking water or influence political processes and other important factors for the people (UNDP, 2009). Also, in addition to the importance of identifying poor people in various social, economic, etc., understanding the relationship between areas of poverty is also worth serious attention. Because determining how the relationship between different areas of the issue of poverty can play a role in identifying important and priority factors and help better planning for cities. Isfahan is one of the cities in Iran that despite its large population and physical, less research has been done in relation to poverty. In recent decades, with its horizontal expansion, the city has involving several cities, villages or even informal settlements. It has become a city with a heterogeneous social and economic context on the one hand, and physical and functional context on the other hand. Therefore, in this study, the aim is to analyze the level of social and economic poverty and also examine the physical and functional deprivation and poverty in the 15 regions of Isfahan and then analyze the significance of the relationship between the two dimensions. In this regard, based on the review of theoretical and empirical literature, relevant measures have been identified and the information needed to evaluate the measures has been collected through documentary and field interviews. Also, above measures and factors were explained and analyzed using descriptive and inferential statistics (factor analysis, linear regression and Pearson correlation analysis) and GIS and SPSS softwares. The results showed that the greatest impact on socio-economic poverty is related to the variable "average number of people per housing unit" and the lowest impact is related to "population". The impact of "population density" and "migration rate" on socio-economic poverty is low and its significance is denied. Also in the greatest effect on physical-functional poverty is related to the variable "building density" and the least effect is related to the variable "residential per capita". Evidence indicate that the deprivation and welfare of the regions of Isfahan is as follows: In term of socio-economic dimension regions 14 and 15 are very deprived, regions 2, 11 and 12 are deprived, regions 7, 8, 9 and 10 are average and regions 3, 4, 6 and 13 are in the prosperous group and regions 1 and 5 are very prosperous in terms of socio-economic dimension. It becomes. One of the reasons for the severe deprivation in regions 14 and 15 is the informal and marginal settlements of these regions. Meanwhile, until 2013, region 15 was the city of Khorasgan on the eastern outskirts of the city of Isfahan, which was joined to Isfahan by approved by the Cabinet. Agriculture, horticulture and animal farming were considered as the most important occupations of this region which gradually decreased after the drought and water shortage of Zayandeh Rood River. In terms of physical-functional dimension most regions of the east, west and north, including regions 14 also 2, 7, 8, 9, 10, 11 and 12 in terms of physical-functional, are very deprived and deprived respectively, which shows the unbalanced distribution of services and low building density. regions 1, 3, 5, and 13 also 6 are respectively prosperous and very prosperous regions in the field of physical-functional. The reasons for this are the high density of construction and the desirable quality of housing materials and the centralized distribution of services and uses in these regions. Regions 4 and 15 were moderate in terms of physical-functional. In addition to the above analyzes, through factor analysis technique, socio-economic and physical-functional variables were aggregated in each dimension and its scores were obtained. The relationship between these two dimensions was obtained through Pearson correlation coefficient of positive 0.594 and the intensity of correlation was calculated as moderate and significant. This relationship means that any regions that is socio-economically deprived is relatively physically-functionally deprived. This indicates that despite the need for areas with social and economic poverty to be addressed and given more attention based on justice-based justice policies, these areas have been ignored and less considered in metropolitan policies in the field of distribution of services and facilities. In other words, the support and priority of urban management in the implementation and implementation of justice and its empowerment should be postponed, which can make poverty relief more difficult and access to opportunities more limited. Due to the imbalance between the distribution of land uses and services in the areas of Isfahan, creating and promoting educational land in 14, 7, 12 and 8 regions; Commercial use in decentralized areas of the city such as 14 and 15, 9 and 4 regions; Establishment of local parks and green spaces in 1, 9, 5 and 13 regions; Sports use is recommended in 10 and 15 regions. While considering the importance of building density in physical-functional possession, it is suggested that building density in 2, 9 and 11 regions have a reasonable and effective increase. It need to mention that in order to control urban poverty in social and economic fields, it is necessary to create a general and inclusive flow among citizens by promoting and informing in this field at different levels so that citizens in each region, the city conditions and their living space. To be informed and through cultural programs, meetings and specialized conferences and holding training courses and production of documents and practical resources in this field, the distance between citizens and professionals and management and governance factors to be reduced and convergent collections to increase the enjoyment and empowerment of urban areas and citizens are created. 1) The forms and effects of urbanization are becoming more and more complex and widespread. In fact, the cities have a higher capacity for housing, prosperity and access to better living opportunities for people. However, urban poverty in the world is spreading rapidly and at a high rate, and despite different views on poverty and global and national programs to combat it, this problem remains a major threat and it confronts cities with effects of inefficiency (Asian Bank, 2014: 11). This issue is especially more important in developing countries (including Iran) and statistics show an increasing trend of inter-class distance and consequently the extent of relative poverty. Due to the mentioned necessity, a large number of thinkers in various fields of social sciences, geography, etc. have addressed the issue of poverty in various dimensions and this issue, along with the importance discussion of justice, has become one of the key issues of the era. Multidimensional poverty today also refers to the fact that poverty is more than inadequate income or deprivation of material resources, as well as the inability to access education, primary health care, clean drinking water or influence political processes and other important factors for the people (UNDP, 2009). Also, in addition to the importance of identifying poor people in various social, economic, etc., understanding the relationship between areas of poverty is also worth serious attention. Because determining how the relationship between different areas of the issue of poverty can play a role in identifying important and priority factors and help better planning for cities. Isfahan is one of the cities in Iran that despite its large population and physical, less research has been done in relation to poverty. In recent decades, with its horizontal expansion, the city has involving several cities, villages or even informal settlements. It has become a city with a heterogeneous social and economic context on the one hand, and physical and functional context on the other hand. Therefore, in this study, the aim is to analyze the level of social and economic poverty and also examine the physical and functional deprivation and poverty in the 15 regions of Isfahan and then analyze the significance of the relationship between the two dimensions. In this regard, based on the review of theoretical and empirical literature, relevant measures have been identified and the information needed to evaluate the measures has been collected through documentary and field interviews. Also, above measures and factors were explained and analyzed using descriptive and inferential statistics (factor analysis, linear regression and Pearson correlation analysis) and GIS and SPSS softwares. The results showed that the greatest impact on socio-economic poverty is related to the variable "average number of people per housing unit" and the lowest impact is related to "population". The impact of "population density" and "migration rate" on socio-economic poverty is low and its significance is denied. Also in the greatest effect on physical-functional poverty is related to the variable "building density" and the least effect is related to the variable "residential per capita". Evidence indicate that the deprivation and welfare of the regions of Isfahan is as follows: In term of socio-economic dimension regions 14 and 15 are very deprived, regions 2, 11 and 12 are deprived, regions 7, 8, 9 and 10 are average and regions 3, 4, 6 and 13 are in the prosperous group and regions 1 and 5 are very prosperous in terms of socio-economic dimension. It becomes. One of the reasons for the severe deprivation in regions 14 and 15 is the informal and marginal settlements of these regions. Meanwhile, until 2013, region 15 was the city of Khorasgan on the eastern outskirts of the city of Isfahan, which was joined to Isfahan by approved by the Cabinet. Agriculture, horticulture and animal farming were considered as the most important occupations of this region which gradually decreased after the drought and water shortage of Zayandeh Rood River. In terms of physical-functional dimension most regions of the east, west and north, including regions 14 also 2, 7, 8, 9, 10, 11 and 12 in terms of physical-functional, are very deprived and deprived respectively, which shows the unbalanced distribution of services and low building density. regions 1, 3, 5, and 13 also 6 are respectively prosperous and very prosperous regions in the field of physical-functional. The reasons for this are the high density of construction and the desirable quality of housing materials and the centralized distribution of services and uses in these regions. Regions 4 and 15 were moderate in terms of physical-functional. In addition to the above analyzes, through factor analysis technique, socio-economic and physical-functional variables were aggregated in each dimension and its scores were obtained. The relationship between these two dimensions was obtained through Pearson correlation coefficient of positive 0.594 and the intensity of correlation was calculated as moderate and significant. This relationship means that any regions that is socio-economically deprived is relatively physically-functionally deprived. This indicates that despite the need for areas with social and economic poverty to be addressed and given more attention based on justice-based justice policies, these areas have been ignored and less considered in metropolitan policies in the field of distribution of services and facilities. In other words, the support and priority of urban management in the implementation and implementation of justice and its empowerment should be postponed, which can make poverty relief more difficult and access to opportunities more limited. Due to the imbalance between the distribution of land uses and services in the areas of Isfahan, creating and promoting educational land in 14, 7, 12 and 8 regions; Commercial use in decentralized areas of the city such as 14 and 15, 9 and 4 regions; Establishment of local parks and green spaces in 1, 9, 5 and 13 regions; Sports use is recommended in 10 and 15 regions. While considering the importance of building density in physical-functional possession, it is suggested that building density in 2, 9 and 11 regions have a reasonable and effective increase. It need to mention that in order to control urban poverty in social and economic fields, it is necessary to create a general and inclusive flow among citizens by promoting and informing in this field at different levels so that citizens in each region, the city conditions and their living space. To be informed and through cultural programs, meetings and specialized conferences and holding training courses and production of documents and practical resources in this field, the distance between citizens and professionals and management and governance factors to be reduced and convergent collections to increase the enjoyment and empowerment of urban areas and citizens are created.

https://gep.ui.ac.ir/article_24947_71509992effe94351e51681eb2d249d9.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 31 3 2020 09 22 Optimizing the Structure of Traditional Bazaars with Emphasis on Spatial Configuration and Interconnection (Case Study: Kermanshah Bazaar) Optimizing the Structure of Traditional Bazaars with Emphasis on Spatial Configuration and Interconnection (Case Study: Kermanshah Bazaar) 79 106 25125 10.22108/gep.2020.123372.1313 FA Hasan Sajadzadeh Associate Professor of Urban Planning, Faculty of Art and Architecture, Bu-Ali Sina University, Hamedan, Iran 0000-0002-3989-9389 Mahsa Abbasi Kernachi MA in Urban and Regional Planning, Faculty of Art and Architecture, Islamic Azad University of Hamedan, Iran Neda Sohrabi MA in Urban Design, Faculty of Art and Architecture, Bu-Ali Sina University, Hamedan, Iran Journal Article 2020 06 02 Introduction: Disorders created in various physical, functional, and semantic dimensions that are the results of not paying attention to the structure and spatial organization of ancient cities and their main arrangement. Disorders make it necessary to review and explore more desirable methods of designing and organizing urban spaces. The increasing expansion of cities requires urgent measures and the city is forced to accept change. Changing urban trends in different economic, political, and cultural fields, migration-based urban growth, lack of proper development policies and disorder of urban land use distribution, inconsistencies in building composition, separation of structures and functions, lack of hierarchy in public spheres, and contradictions in different patterns have led to the combination of mass and space and the obvious distinction between the new and the old. Antiquities and traditional buildings are among the most important factors in introducing the culture and civilization of the ancestors of every nation. Among these works, the bazaar is one of the main components of the urban structure and the center of social, economic, and cultural exchanges. Meanwhile, Kermanshah bazaar with a length of 2700 meters, like many traditional bazaars with different components, has not been an exception to this change. The construction of Sepah or Modarres Street in 1935, which led to the closure of the covered bazaar of Kermanshah and the separation of the two sections of goldsmiths and Islamic, is a clear example of the lack of attention to the physical context and the current condition of this building and the hasty implementation of this street. Therefore, to prevent increasing disorganizations in the city, it is necessary to take distinct measures to establish a subtle but inseparable link between the axes and historical elements such as bazaars and current important functions in the city. The purpose of the present study is to investigate the effects of spatial configuration and interconnection as relational characteristics in the spatial understanding of traditional bazaars. Methodology: In general, field research procedures and data collection tools including observation, visit and perception of the site and the use of various libraries, as well as databases, computer networks, Web sites photo archives and magazines were used in this research. AutoCAD, GIS, and space syntax software were used for the analysis. One of the tools of spatial analysis is explanatory diagrams based on the graph theory. In this way, each space is a node and the connection between the two spaces is drawn as a line connecting the two nodes. In this research, the graph program was used. In this software, which can specify the smallest axis lines, maps are entered in JPEG format. In the present study, the area of Islamic and goldsmiths bazaars in Kermanshah was selected. In the first step, after creating a pivot map in AutoCAD, we entered it into Depthmap software to obtain the relationship between nodes and the degree of interconnection and depth. The resulting functions (Reach, Gravity, Betweenness, Closeness, and Straightness) provided outputs in the form of raw analysis that provide block performance, population role weight, and additional access role indicators in the study area. Conclusion: To determine the degree of interconnection according to the size of the study area, the area of goldsmiths and Islamic bazaars was divided into 4 zones. According to the results, in zones 2 and 4, green space forms distinct uses. According to the spatial arrangement theory, after entering maps in the graph software, the output was such that the northern parts of the body of the areas have more spatial depth and less interconnection. 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Mousavi, M. & Zargar Daghigh, H. (2008). Analize Special Structure in Tabriz at Bulwark Zone Using Space Syntax Technique. International civil Monthly Journal, 67, 58-69. - Zamani, B., & Honarvar, M. (2012). Fundamentals and Criteria of Space Layout Technique (Comparative Application: Dolatkhaneh and Mulla SadraNeighborhoods of North Isfahan). 4th Conference on Urban Planning and Management, Mashhad, Mashhad University, 2, 1-18. Introduction: Disorders created in various physical, functional, and semantic dimensions that are the results of not paying attention to the structure and spatial organization of ancient cities and their main arrangement. Disorders make it necessary to review and explore more desirable methods of designing and organizing urban spaces. The increasing expansion of cities requires urgent measures and the city is forced to accept change. Changing urban trends in different economic, political, and cultural fields, migration-based urban growth, lack of proper development policies and disorder of urban land use distribution, inconsistencies in building composition, separation of structures and functions, lack of hierarchy in public spheres, and contradictions in different patterns have led to the combination of mass and space and the obvious distinction between the new and the old. Antiquities and traditional buildings are among the most important factors in introducing the culture and civilization of the ancestors of every nation. Among these works, the bazaar is one of the main components of the urban structure and the center of social, economic, and cultural exchanges. Meanwhile, Kermanshah bazaar with a length of 2700 meters, like many traditional bazaars with different components, has not been an exception to this change. The construction of Sepah or Modarres Street in 1935, which led to the closure of the covered bazaar of Kermanshah and the separation of the two sections of goldsmiths and Islamic, is a clear example of the lack of attention to the physical context and the current condition of this building and the hasty implementation of this street. Therefore, to prevent increasing disorganizations in the city, it is necessary to take distinct measures to establish a subtle but inseparable link between the axes and historical elements such as bazaars and current important functions in the city. The purpose of the present study is to investigate the effects of spatial configuration and interconnection as relational characteristics in the spatial understanding of traditional bazaars. Methodology: In general, field research procedures and data collection tools including observation, visit and perception of the site and the use of various libraries, as well as databases, computer networks, Web sites photo archives and magazines were used in this research. AutoCAD, GIS, and space syntax software were used for the analysis. One of the tools of spatial analysis is explanatory diagrams based on the graph theory. In this way, each space is a node and the connection between the two spaces is drawn as a line connecting the two nodes. In this research, the graph program was used. In this software, which can specify the smallest axis lines, maps are entered in JPEG format. In the present study, the area of Islamic and goldsmiths bazaars in Kermanshah was selected. In the first step, after creating a pivot map in AutoCAD, we entered it into Depthmap software to obtain the relationship between nodes and the degree of interconnection and depth. The resulting functions (Reach, Gravity, Betweenness, Closeness, and Straightness) provided outputs in the form of raw analysis that provide block performance, population role weight, and additional access role indicators in the study area. Conclusion: To determine the degree of interconnection according to the size of the study area, the area of goldsmiths and Islamic bazaars was divided into 4 zones. According to the results, in zones 2 and 4, green space forms distinct uses. According to the spatial arrangement theory, after entering maps in the graph software, the output was such that the northern parts of the body of the areas have more spatial depth and less interconnection. After entering the maps in the GIS software and analyzing them through the functions that we have dealt with, it can be said that creating coherence and interconnection in the spatial organization of the city is effective both for the regeneration of the old texture, especially the old structure of the city and for the elimination of the disorders of the contemporary urban textures. Keywords: Interconnection, Organization, Spatial Depth, Kermanshah Bazaar. References: - Abbaszadegan, M. (2002). Space Layout Method in Urban Design Process, with a Look at the City of Yazd. Journal of Urban Management, 9, 64-75. - Alexander, C. (2000). The Nature of Order. UK: Oxford University Press. - Ali Al-Hesabi, M., & Abbasi, M. (2013). A Study of the need for systematic cohesion in cities and its laws from the perspective of some theorists. Specialized Monthly Journal of City and Landscape, 14, 14-19. - Bacon, E. (2008). Cities Design.Translation by Farzaneh Taheri, Second Edition. 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https://gep.ui.ac.ir/article_25125_ae8bc734506de5491a82b84c094a2d14.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 31 3 2020 09 22 The Effects of Land Use Changes on the Maximum Flood Discharge in the Songhor Watershed The Effects of Land Use Changes on the Maximum Flood Discharge in the Songhor Watershed 107 130 25190 10.22108/gep.2020.124348.1338 FA Hamed Gholamian M.Sc. Department of Natural Engineering, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran Alireza Ildoromi Associate Professor, Department of Natural Engineering, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran Journal Article 2020 08 12 At present, land use changes in a basin over time affect many processes of soil erosion and sediment production and cause loss of soil quality and fertility (Ildoromi et al. 2017). Studies have shown that land use change and its effect on hydrological processes can play an effective role in managing water resources and floods and reducing the damage caused by it, which has been considered by many researchers in recent years. Kazemi et al. (2018) in the study of the effect of land use change and drought on runoff in the Central Zagros Basin stated that the most land use change in 25 years in the field of natural resources, especially in rangelands and increased runoff and floods has been in the basin. Foroutan et al. (2019) investigated the effect of land use change and physical development of the city on changes in Asadabad urban flood runoff. The results showed that with the increase of urban land use area, surface runoff has increased by 350 m3, which is a considerable and sometimes dangerous volume of runoff in a small city. Gomindoga et al. (2015) investigated the effect of land use change in Ethiopia's Jilljal Abai watershed and concluded that reduced rangeland and forest land use increased the maximum flood. The present study aimed to investigate the effects of land use change on maximum flood discharge in the Songhor watershed using the Win TR-55 model and Landsat 7 and 8 satellite images for the years 2000-2015 using ENVI software. 2. Methodology: The Songhor watershed in Kermanshah province is a part of the Karkheh watershed with an area of 63.17 Km2 and has a cold semi-humid climate. In this study, the main variables were 24-hour rainfall, concentration-time, flood coefficient, basin area, and slope and land use change area. To study and prepare land use change maps during two periods, ETM and OLI sensor images of Landsat satellite from 2000-2015 were used. After performing geometric correction and band compositions with the help of ENVI software, the adjusted plant difference index (NDVI) was prepared. To classify the images, the classification method was supervised and the maximum probability, kappa index, and general accuracy were used for the correct evaluation. In the next stage, land use changes were classified into five land use classes including irrigated agriculture and gardening, rainfed agriculture, rangeland and forest, residential areas, impenetrable and rocky lands. Finally, land use maps of the Songhor watershed in two time periods of 2000 and 2015 were drawn in ArcGIS. In the next step, the maximum flood hydrograph under the influence of land use change was estimated using the Win TR-55 model for the years 2000-2015. To analyze the peak flow sensitivity of the basin, the values of the canal slope and to evaluate the results by WinTR-55 model, two statistics of correlation coefficient (R2) and Root Mean Square Error (RMSE) were used. 3. Discussion: The study of hydrographs showed that in all sub-basins, according to the amount and intensity of land use change, the peak discharge increased in 2015 compared to 2000. This amount decreased in sub-basin S1 due to fewer land use changes and concrete-mortar watershed structures in 2015. It showed a decrease of 4.11% compared to 2000 and indicates that the structures have reduced the speed and volume of discharge from the basin. In other sub-basins, due to the slope and topographic condition, the amount and intensity of land use changes, especially the sharp decrease in rangeland lands and the existence of residential and impenetrable areas, peak discharge values increased. The highest increase in discharge occurred in the S6 sub-basin with 24.88% and the S8 sub-basin with 22.44% in 2015 compared to 2000. Examination of the basin outlet hydrograph showed that the peak discharge rate in 2015 increased by 12.2% in the total basin. One of the effective factors is land use changes and subsequent changes in the basin CN values during the 15 years under study. The results of the sensitivity analysis of the WinTR-55 model showed that the CN parameter is very important and causes high sensitivity. The results of verification and calculation of the estimated error of the model in the return period of 2 to 100 years showed that the percentage of flow estimation error by the model in the 100-year return period has the lowest value. 4. Conclusion: Land use changes in the watershed were influenced by factors such as the suitability of rainfall in 2000-2008 and the tendency of some farmers regarding dry farmland to increase the extent of their agricultural land to increase their income. The population of the city has increased by 7.5% from 2005 to 2015 and the development of urbanization has made agricultural areas around the city become residential areas. Droughts in recent years have also destroyed some grassland species, reduced soil moisture, and increased runoff. The velocity and flow rate were the peaks. Output hydrograph survey of the basin showed that the peak discharge in 2015 increased by 12.2% in the whole basin. In general, the effective factors in increasing the discharge in the Songhor watershed are the land use changes followed by changes in the CN values over the 15 years studied. The results of WinTR-55 sensitivity analysis showed that the CN parameter was an important parameter in the model. It showed that the model a has high ability to estimate the maximum flood discharge for this type of condition in the Songhor watershed and indicated the high accuracy and efficiency of the model in investigating hydrological fluctuations. Keywords: Hydrograph, Win TR-55 Model, CN, R2, RMSE. References: - Chen, Y., Xu, Y. & Yin, Y. (2009). Impacts of Land Use Change Scenarios on Storm-Runoff Generation in Xitiaxi Basin, China. Journal of Quaternary International, 208(1-2), 121-128. - Dams, J., Dujardin, J., Reggers, R., Bashir, I., Canters, F., & Batelaan, O. (2013). Mapping Impervious Surface Change from Remote Sensing for Hydrological Modeling. Journal of Hydrology, 485, 84-95. - Forutan, S., Ildoromi, A., Noori, H., & Safari Shad, M., (2019). Impact of Land Use Change and Physical Development of the City on Urban Flood Runoff Changes Using NRCS-CN Method (Case Study: Asadabad City). Scientific Journal- Tabriz Hydrogeomorphology Research, 5(20), 1-20. - Gumindoga, W., Rientjes, T. H. M., Haile, A. T., & Dube, T. (2014). Predicting Streamflow for Land Cover Changes in the Upper Gilgel Abay River Basin, Ethiopia: A Topmodel Based Approach. Journal of Physics and Chemistry of the Earth, Parts A/B/C, 76, 3-15. - Ildoromi, A., Noori, H., & Karami, M. (2017). Evaluation of Drought and Climate Change in the Future Using General Bar Circulation Models (Case Study: Gorganroud-Ghareh SouBasin, Iran). Journal of Geographical Studies of Arid Regions, 7(26), 111-124. - Kazemi, S., Ildermi, A., & Nouri, H. (2019). The Effect of Land Use Change and Drought on the Runoff Central Zagros; Case Study: Tuyserkan Basin. Journal of Arid Studies, Hakim Sabzevari University, 8(31), 23-41. - Kumar, D. S., Arya, D. S., & Vojinovic, Z. (2013). Modeling of Urban Growth Dynamics and Its Impact On Surface Runoff Characteristics. Journal of Environment and Urban Systems, 41, 124-135. - Miller, J. D., Kim, H., Kjeldsen, T. R., Packman, J., Grebby, S., & Dearden, R. (2014). Assessing the Impact of Urbanization on Storm Runoff in a Peri-Urban Catchment Using Historical Change in Impervious Cover. Journal of Hydrology, 515, 59-70. - Rawat, J. S., & Kumar, M. (2015). Monitoring Land Use/Cover Change Using Remote Sensing and GIS Techniques: A Case Study of Hawalbagh Block, District Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Sciences, 18(1), 77- 84 - Sajikumar, N., & Remya, R. S. (2015). Impact of Land Cover and Land Use Change on Runoff Characteristics. Journal of Environmental Management, 161, 460-468. - Siriwardena, L., Finlayson, B. L., & McMahon, T. A. (2006). The Impact of Land Use Change on Catchment Hydrology in Large Catchments: The Comet River, Central Queensland, Australia. Journal of Hydrology, 326(1-4), 199-214. - Valdes, J. B., Fiallo, Y., & Rodríguez‐Iturbe, I. (1979). A Rainfall‐Runoff Analysis of the Geomorphologic IUH. Journal of Water Resources Research, 15(6), 1421-1434. - Yan, B., Fang, N. F., Zhang, P. C., & Shi, Z. H. (2014). The Impact of Land Use Change on Watershed Stream Flow and Sediment Yield: An Assessment Using Hydrologic Modelling and Partial Least Squares Regression (Case Study: China). Journal of Hydrology, 484, 26-37. - Zhou, Q., Ou, X. K., Zhang, Z. M., & Yang, M. Y. (2008). Spatial-Temporal Land Use Pattern Changes in Manwan Hydropower Station Reservoir of Lancang River, Yunnan, China. Journal of Mountain Science, 26(4), 481-489. At present, land use changes in a basin over time affect many processes of soil erosion and sediment production and cause loss of soil quality and fertility (Ildoromi et al. 2017). Studies have shown that land use change and its effect on hydrological processes can play an effective role in managing water resources and floods and reducing the damage caused by it, which has been considered by many researchers in recent years. Kazemi et al. (2018) in the study of the effect of land use change and drought on runoff in the Central Zagros Basin stated that the most land use change in 25 years in the field of natural resources, especially in rangelands and increased runoff and floods has been in the basin. Foroutan et al. (2019) investigated the effect of land use change and physical development of the city on changes in Asadabad urban flood runoff. The results showed that with the increase of urban land use area, surface runoff has increased by 350 m3, which is a considerable and sometimes dangerous volume of runoff in a small city. Gomindoga et al. (2015) investigated the effect of land use change in Ethiopia's Jilljal Abai watershed and concluded that reduced rangeland and forest land use increased the maximum flood. The present study aimed to investigate the effects of land use change on maximum flood discharge in the Songhor watershed using the Win TR-55 model and Landsat 7 and 8 satellite images for the years 2000-2015 using ENVI software. 2. Methodology: The Songhor watershed in Kermanshah province is a part of the Karkheh watershed with an area of 63.17 Km2 and has a cold semi-humid climate. In this study, the main variables were 24-hour rainfall, concentration-time, flood coefficient, basin area, and slope and land use change area. To study and prepare land use change maps during two periods, ETM and OLI sensor images of Landsat satellite from 2000-2015 were used. After performing geometric correction and band compositions with the help of ENVI software, the adjusted plant difference index (NDVI) was prepared. To classify the images, the classification method was supervised and the maximum probability, kappa index, and general accuracy were used for the correct evaluation. In the next stage, land use changes were classified into five land use classes including irrigated agriculture and gardening, rainfed agriculture, rangeland and forest, residential areas, impenetrable and rocky lands. Finally, land use maps of the Songhor watershed in two time periods of 2000 and 2015 were drawn in ArcGIS. In the next step, the maximum flood hydrograph under the influence of land use change was estimated using the Win TR-55 model for the years 2000-2015. To analyze the peak flow sensitivity of the basin, the values of the canal slope and to evaluate the results by WinTR-55 model, two statistics of correlation coefficient (R2) and Root Mean Square Error (RMSE) were used. 3. Discussion: The study of hydrographs showed that in all sub-basins, according to the amount and intensity of land use change, the peak discharge increased in 2015 compared to 2000. This amount decreased in sub-basin S1 due to fewer land use changes and concrete-mortar watershed structures in 2015. It showed a decrease of 4.11% compared to 2000 and indicates that the structures have reduced the speed and volume of discharge from the basin. In other sub-basins, due to the slope and topographic condition, the amount and intensity of land use changes, especially the sharp decrease in rangeland lands and the existence of residential and impenetrable areas, peak discharge values increased. The highest increase in discharge occurred in the S6 sub-basin with 24.88% and the S8 sub-basin with 22.44% in 2015 compared to 2000. Examination of the basin outlet hydrograph showed that the peak discharge rate in 2015 increased by 12.2% in the total basin. One of the effective factors is land use changes and subsequent changes in the basin CN values during the 15 years under study. The results of the sensitivity analysis of the WinTR-55 model showed that the CN parameter is very important and causes high sensitivity. The results of verification and calculation of the estimated error of the model in the return period of 2 to 100 years showed that the percentage of flow estimation error by the model in the 100-year return period has the lowest value. 4. Conclusion: Land use changes in the watershed were influenced by factors such as the suitability of rainfall in 2000-2008 and the tendency of some farmers regarding dry farmland to increase the extent of their agricultural land to increase their income. The population of the city has increased by 7.5% from 2005 to 2015 and the development of urbanization has made agricultural areas around the city become residential areas. Droughts in recent years have also destroyed some grassland species, reduced soil moisture, and increased runoff. The velocity and flow rate were the peaks. Output hydrograph survey of the basin showed that the peak discharge in 2015 increased by 12.2% in the whole basin. In general, the effective factors in increasing the discharge in the Songhor watershed are the land use changes followed by changes in the CN values over the 15 years studied. The results of WinTR-55 sensitivity analysis showed that the CN parameter was an important parameter in the model. It showed that the model a has high ability to estimate the maximum flood discharge for this type of condition in the Songhor watershed and indicated the high accuracy and efficiency of the model in investigating hydrological fluctuations. Keywords: Hydrograph, Win TR-55 Model, CN, R2, RMSE. References: - Chen, Y., Xu, Y. & Yin, Y. (2009). Impacts of Land Use Change Scenarios on Storm-Runoff Generation in Xitiaxi Basin, China. Journal of Quaternary International, 208(1-2), 121-128. - Dams, J., Dujardin, J., Reggers, R., Bashir, I., Canters, F., & Batelaan, O. (2013). Mapping Impervious Surface Change from Remote Sensing for Hydrological Modeling. Journal of Hydrology, 485, 84-95. - Forutan, S., Ildoromi, A., Noori, H., & Safari Shad, M., (2019). Impact of Land Use Change and Physical Development of the City on Urban Flood Runoff Changes Using NRCS-CN Method (Case Study: Asadabad City). Scientific Journal- Tabriz Hydrogeomorphology Research, 5(20), 1-20. - Gumindoga, W., Rientjes, T. H. M., Haile, A. T., & Dube, T. (2014). Predicting Streamflow for Land Cover Changes in the Upper Gilgel Abay River Basin, Ethiopia: A Topmodel Based Approach. Journal of Physics and Chemistry of the Earth, Parts A/B/C, 76, 3-15. - Ildoromi, A., Noori, H., & Karami, M. (2017). Evaluation of Drought and Climate Change in the Future Using General Bar Circulation Models (Case Study: Gorganroud-Ghareh SouBasin, Iran). Journal of Geographical Studies of Arid Regions, 7(26), 111-124. - Kazemi, S., Ildermi, A., & Nouri, H. (2019). The Effect of Land Use Change and Drought on the Runoff Central Zagros; Case Study: Tuyserkan Basin. Journal of Arid Studies, Hakim Sabzevari University, 8(31), 23-41. - Kumar, D. S., Arya, D. S., & Vojinovic, Z. (2013). Modeling of Urban Growth Dynamics and Its Impact On Surface Runoff Characteristics. Journal of Environment and Urban Systems, 41, 124-135. - Miller, J. D., Kim, H., Kjeldsen, T. R., Packman, J., Grebby, S., & Dearden, R. (2014). Assessing the Impact of Urbanization on Storm Runoff in a Peri-Urban Catchment Using Historical Change in Impervious Cover. Journal of Hydrology, 515, 59-70. - Rawat, J. S., & Kumar, M. (2015). Monitoring Land Use/Cover Change Using Remote Sensing and GIS Techniques: A Case Study of Hawalbagh Block, District Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Sciences, 18(1), 77- 84 - Sajikumar, N., & Remya, R. S. (2015). Impact of Land Cover and Land Use Change on Runoff Characteristics. Journal of Environmental Management, 161, 460-468. - Siriwardena, L., Finlayson, B. L., & McMahon, T. A. (2006). The Impact of Land Use Change on Catchment Hydrology in Large Catchments: The Comet River, Central Queensland, Australia. Journal of Hydrology, 326(1-4), 199-214. - Valdes, J. B., Fiallo, Y., & Rodríguez‐Iturbe, I. (1979). A Rainfall‐Runoff Analysis of the Geomorphologic IUH. Journal of Water Resources Research, 15(6), 1421-1434. - Yan, B., Fang, N. F., Zhang, P. C., & Shi, Z. H. (2014). The Impact of Land Use Change on Watershed Stream Flow and Sediment Yield: An Assessment Using Hydrologic Modelling and Partial Least Squares Regression (Case Study: China). Journal of Hydrology, 484, 26-37. - Zhou, Q., Ou, X. K., Zhang, Z. M., & Yang, M. Y. (2008). Spatial-Temporal Land Use Pattern Changes in Manwan Hydropower Station Reservoir of Lancang River, Yunnan, China. Journal of Mountain Science, 26(4), 481-489.

https://gep.ui.ac.ir/article_25190_8d6393449b28a540a1d4817e58e59c17.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 31 3 2020 09 22 Monitoring Changes in Sand Dunes by Analyzing Satellite Images and Wind Station Data (Case Study: Zahak Erg Region in the East of Sistan Plain) Monitoring Changes in Sand Dunes by Analyzing Satellite Images and Wind Station Data (Case Study: Zahak Erg Region in the East of Sistan Plain) 131 148 25195 10.22108/gep.2020.123597.1317 FA Mehran Maghsoudi Associate Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran Fatemeh Geravand PhD Candidate of Geomorphology, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran Bay Ram-Ali Abdinejad PhD Candidate of Geomorphology, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran Parisa Pirani PhD Candidate of Geomorphology, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran Journal Article 2020 07 20 Introduction Aeolian sand transport is a complex process influenced by many variables including wind conditions (Lancaster, 1985; Anderson & Haff, 1988; Gillette et al., 2001; Zou et al., 2001; Liu et al., 2005), grain size and sand surface moisture (Jackson, 1998; Wiggs et al., 2004), surface crusting (Leys & Eldridge, 1991), topography (Iversen & Rasmussen 1994; Hesp et al., 2005), and vegetation cover (Buckley, 1987; Kuriyama et al., 2005). The importance of sand dunes studies is due to their impacts on water and soil resources, flora and fauna, human infrastructure, and roads. Sand drifting can lead to losing agricultural lands, burying residential buildings, railways, highways, and other infrastructures in many areas of the desert (Zhu et al., 1980; Lei et al., 2003; Dong, 2004). Bagnlod (1981) has done the first study on the movement of sand dunes. In recent years, many studies have been done on the cognition of sand dune processes, which include the study of the winds and sands migration in different dunes. Needless to say that significant signs of progress have been obtained. In this regard, there is no doubt that the remote sensing technique and its capabilities, as well as the optimal time sequence of satellite imagery in mapping erg areas, have fundamental performances. Using these images, a substantial area of sand dunes can be examined in a short period of time, and then we can talk about the identification of active dunes, their expansion, and relocation. Methodology To study the changes and migration of sand dunes, this study was conducted in two stages. At the first stage, to evaluate changes in the range of sand dunes in the study area, Landsat images were used for the years 2001 and 2019. Moreover, to detect the changes in the Zahak Erg range the ENVI software was used. The results of this section can be important in the overall assessment of the area. Additionally, in order to detect the trend of changes in those parts where significant shifting occurred, we used either Landsat or the Google Earth images with different time intervals. It worth mentioning that for geo-referencing the Google Earth images of recent years (2006-2018) the Stitch Map Software was used. Moreover, to draw the sand rose, the Sand Rose software was used. Sand rose is the Graph of Portable sand by wind energy, which was used by Fryberger and Dean (1979) for the first time. In order to draw this Graph, winds that were faster than the erosion velocity threshold were developed into vector units as sand drift potential. Discussion Mobility is the most important characteristic of sand dunes. In this regard, special attention should be paid to the importance of wind in changing the sand dunes morphology. In addition, studies of sand dunes migration provide basic knowledge about wind processes and sand transfer values. In this study, monitoring and detection of the sand dunes relocation rate have been considered based on the use of Landsat images (for the years 2001-2019). At the first stage, the regions that have been faced changes were identified using the change detection technique for the entire range of Erg. Based on the output map, marked areas with the red color experienced the maximum changes, and also, in this section, sand dunes have been more developed. The differences between the two images within the sand dunes area were estimated at about 23 km2. However, the pattern of sand dunes migration represents relocation from the Northwest to the Southeast. At the next stage of the study, to understand the change rate and relocation trend, Google Earth images were used (years 2006 and 2018). Furthermore, the region with significant changes has been selected for a closer look. Moreover, using Stitch Map software, the georeferenced images were extracted. It worth mentioning that, from the five selected zones on the Erg surface, a total of 368 cases of sand dunes were quantitatively analyzed. According to the results, the greatest amount of migration was found for zone 3 with the amount of 24.72 m, in contrast, the lowest value was calculated at about 14.16 m for zone 5. In addition, the migration average rate for a period of 12 years was calculated. Here, the maximum migration belonged to zone 3 which is 2.06 meters per year. While the minimum one allocated to zone 5 was 1.18 meters per year. Conclusion In this study, the authors monitored changes in sand dunes using satellite imagery data and wind data of meteorological stations of Zahak Erg. In this regard, the sand dunes activity rate, dunes migration pattern, and also factors affecting their intensity and patterns were identified. The results of the 368 studied sand dunes in different parts of the erg surface indicated displacement with a northwest-southeast trend, which is consistent with the results of data analysis for wind pattern. But the average amount of displacement of 1.53 meters per year for a period of 12 years (2006 to 2018) with the results of data from Zabol wind station showed the amount of sand carrying more than 300 tons per meter for a year. The changes in wind speed at this station were inconsistent and it was shown that the maximum value obtained was before the stabilization of the active sand dunes. In addition, smooth sands move on the surface of the earth, independent of sand dunes, which cannot be measured by images. Keywords: Sand Dunes, Remote Sensing, Wind Data, Wind erosion, Zahak Erg. References: - Ahmadi, H. (2006). Applied Geomorphology Volume 2 Desert- Wind Erosion. Tehran: University of Tehran Press. - Ahmadian, M. A. (2008). Desert (A Systematic Approach to the Desertification and Desertification Process). Geographical Research Quarterly, 2(53), 146-159. - Al-Awadhi, J. M., Al-Helal, A., & Al-Enezi, A. (2005). Sand Drift Potential in the Desert of Kuwait. Journal of Arid Environments, 63, 425–438. - Bagnold, R. A. (1941). The Physics of Blown Sand and Desert Dunes. London: Chapman and Hall, pp. 104–106. - Baitis, E., Kocurek, G., Smith, V., Mohrig, D., Ewing, R. C., & Peyret, A. P. B. (2014). Definition and Origin of the Dune-Field Pattern at White Sands, New Mexico. Aeolian Research, 15, 269–287. - Delgado-Fernandez, I., & Davidson-Arnott, R. (2011). Meso-Scale Aeolian Sediment Input to Coastal Dunes: The Nature of Aeolian Transport Events. Geomorphology, 126(1-2), 217-232. - Dong, Z., Wang, T., & Wang, X. (2004). Geomorphology of the Megadunes in the Badain Jaran Desert. Geomorphology, 60(1-2), 191-203. - Ebrahimzadeh, I. (2018). A Regional Analysis of Urban-Rural Relationships in Sistan. PhD Thesis in Geography and Urban-Regional Planning, Faculty of Literature and Humanities, University of Isfahan, pp. 85-65. - Fryberger, S. G., AL‐Sari, A. M., Clisham, T. J., Rizvi, S. A., & ALHinai, K. G. (1984). Wind Sedimentation in the Jafurah Sand Sea, Saudi Arabia. Sedimentology, 31(3), 413-431. - Fryberger, S. G., & Dean, G. (1979). Dune Forms and Wind Regime. USA: Geological Survey Professional Paper 1052–F, pp. 137–169. - Gillies, J. A., & Lancaster, N. (2013). Large Roughness Element Effects on Sand Transport, Oceano Dunes, California. Earth Surface Processes and Landforms, 38(8), 785-792. - Hamdan, M. A., Refaat, A. A., & Wahed, M. A. (2016). Morphologic Characteristics and Migration Rate Assessment of Barchan Dunes in the Southeastern Western Desert of Egypt. Journal of Geomorphology, 257, 57-74. - Hereher, M. E. (2018). Geomorphology and Drift Potential of Major Aeolian Sand Deposits in Egypt. Journal of Geomorphology, 304, 113-120. - Hermas, E., Leprince, S., & Abou El-Magd, I. (2012). Retrieving Sand Dune Movements Using Sub-Pixel Correlation of Multi-Temporal Optical Remote Sensing Imagery, Northwest Sinai Peninsula, Egypt. Journal of Remote Sensing of Environment, 121, 51-60. - Hesp, P. A., Davidson-Arnott, R., Walker, I. J., & Ollerhead, J. (2005). Flow Dynamics Over a Foredune at Prince Edward Island, Canada. Journal of Geomorphology, 65(1-2), 71-84. - Housing Foundation of the Islamic Revolution of Sistan and Baluchestan Province. (2019). Technical Unit and Rural Development Studies. - Khosravi, M. (2005). Research Project of Ecological and Environmental Effects of 120-Day Winds in Sistan. Environmental Protection Organization of Sistan and Baluchestan Province, Consultant of Sistan and Baluchestan Institute of Earth Sciences and Geography, p.300. - Kuriyama, Y., Mochizuki, N., & Nalashima, T. (2005). Influence of Vegetation on Aeolian Sand Transport Rate from a Backshore to a Foreshore at Hasaki, Japan. Journal of Sedimentology, 52(5), 1123–1132. - Lancaster, N., Nickling, W. G., & Gillies, J. A. (2010). Sand Transport by Wind on Complex Surfaces: Field Studies in the McMurdo Dry Valleys, Antarctica. Journal of Geophysical Research: Earth Surface, 115(3). - Latifi, L. (2006). Investigating the Progress of Sand Dunes Using Satellite Images in Recent Droughts in the North and East of Sistan Plain. Master Thesis, Department of Geography, Islamic Azad University, Mashhad Branch. - Liu, L.Y., Skidmore, E., Hasi, E., Wagner, L., & Tatarko, J. (2005). Dune Sand Transport as Influenced by Wind Directions, Speed and Frequencies in the Ordos Plateau, China. Journal of Geomorphology, 67(3-4), 283–297. - Maghsoudi, M., Mohammadi, M., Khanbabaei, Z., Mahboubi, S., Baharvand, M., & Hajizadeh, A. H. (2017). Monitoring the Movement of Erg and Barkhans in the West of Lut (Peshouieh). Journal of Quantitative Geomorphological Research, 5(4), 189-176. - Maghsoudi, M., Navidfar, A., & Mohammadi, A. (2017). The Sand Dunes Migration Patterns in Mesr Erg Region Using Satellite Imagery Analysis and Wind Data. Journal of Natural Environment Change, 3(1), 33-43. - Mohamed, I. N., & Verstraeten, G. (2012). Analyzing Dune Dynamics at the Dune-Field Scale Based on Multi-Temporal Analysis of Landsat-TM Images. Journal of Remote Sensing of Environment, 119, 105-117. - Negaresh, H., & Latifi, L. (2008). Geomorphological Analysis of the Progress of Sand Dunes East of the Sistan Plain in Recent Droughts. Journal of Geography and Development, 6(12), 60-43. - Noroozhi, F. (1993). Investigating the Destructive Effects of Helmand River Floods. MA Thesis, Department of Geography, Sistan and Baluchestan University, p.195. - Piri, H., Abbaszadeh, M., Rahdari, V., & Maleki Najafabadi, S. (2013). Comparative Assessment of 4 Meteorological Drought Indices Using Cluster Analysis Method (Case Study of Sistan and Baluchestan Province). Journal of Water Resources Engineering, 6(17), 25-36. - Pye, K., & Tsoar, H. (2009). Aeolian Sand and Sand Dunes. Berlin: Springer-Verlag. - Salighe, M. (2003). Attention to the Wind in the Construction of the Physical Body of Zabol. Journal of Geography and Development, 1(2), 109-121. - Sargzi, H. (2005). Origin and Assessment of Severity and Damage of Sand Dunes in Niatak Sistan Desert. Master Thesis, Gorgan University of Natural Resources, p.136. - Sherman, D. J., & Li, B. (2012). Predicting Aeolian Sand Transport Rates: A Reevaluation of Models. Journal of Aeolian Research, 3(4), 371-378. - Sparavigna, A. C. (2013). A Study of Moving Sand Dunes by Means of Satellite Images. International Journal of Sciences, 2. - Tsoar, H. (2005). Sand Dunes Mobility and Stability in Relation to Climate. Physica A: Statistical Mechanics and its Applications, 357(1), 50-56. - Wang, X., Eerdun, H., Zhou, Z., & Liu, X. (2007). Significance of Variations in the Wind Energy Environment over the Past 50 Years with Respect to Dune Activity and Desertification in Arid and Semiarid Northern China. Journal of Geomorphology, 86(3-4), 252-266. - Wiggs, G. F. S., Atherton, R. J., & Baird, A. J. (2004). Thresholds of Aeolian Sand Transport: Establishing Suitable Values. Journal of Sedimentology, 51(1), 95-108. - Yao, Z. Y., Wang, T., Han, Z. W., Zhang, W. M., & Zhao, A. G. (2007). Migration of Sand Dunes on the Northern Alxa Plateau, Inner Mongolia, China. Journal of Arid Environments, 70(1), 80-93. - Yurk, B. P., Hansen, E. C., & Hazle, D. (2013). A Deadtime Model for the Calibration of Impact Sensors with an Application to a Modified Miniphone Sensor. Journal of Aeolian Research, 11, 43-54. - Zhang, G., Azorin-Molina, C., Shi, P., Lin, D., Guijarro, J. A., Kong, F., & Chen, D. (2019). Impact of Near-Surface Wind Speed Variability on Wind Erosion in the Eastern Agro-Pastoral Transitional Zone of Northern China, 1982–2016. Agricultural and Forest Meteorology, 271, 102-115. - Zhang, Z., Dong, Z., & Li, C. (2015). Wind Regime and Sand Transport in China’s Badain Jaran Desert. Journal of Aeolian Research, 17, 1-13. Introduction Aeolian sand transport is a complex process influenced by many variables including wind conditions (Lancaster, 1985; Anderson & Haff, 1988; Gillette et al., 2001; Zou et al., 2001; Liu et al., 2005), grain size and sand surface moisture (Jackson, 1998; Wiggs et al., 2004), surface crusting (Leys & Eldridge, 1991), topography (Iversen & Rasmussen 1994; Hesp et al., 2005), and vegetation cover (Buckley, 1987; Kuriyama et al., 2005). The importance of sand dunes studies is due to their impacts on water and soil resources, flora and fauna, human infrastructure, and roads. Sand drifting can lead to losing agricultural lands, burying residential buildings, railways, highways, and other infrastructures in many areas of the desert (Zhu et al., 1980; Lei et al., 2003; Dong, 2004). Bagnlod (1981) has done the first study on the movement of sand dunes. In recent years, many studies have been done on the cognition of sand dune processes, which include the study of the winds and sands migration in different dunes. Needless to say that significant signs of progress have been obtained. In this regard, there is no doubt that the remote sensing technique and its capabilities, as well as the optimal time sequence of satellite imagery in mapping erg areas, have fundamental performances. Using these images, a substantial area of sand dunes can be examined in a short period of time, and then we can talk about the identification of active dunes, their expansion, and relocation. Methodology To study the changes and migration of sand dunes, this study was conducted in two stages. At the first stage, to evaluate changes in the range of sand dunes in the study area, Landsat images were used for the years 2001 and 2019. Moreover, to detect the changes in the Zahak Erg range the ENVI software was used. The results of this section can be important in the overall assessment of the area. Additionally, in order to detect the trend of changes in those parts where significant shifting occurred, we used either Landsat or the Google Earth images with different time intervals. It worth mentioning that for geo-referencing the Google Earth images of recent years (2006-2018) the Stitch Map Software was used. Moreover, to draw the sand rose, the Sand Rose software was used. Sand rose is the Graph of Portable sand by wind energy, which was used by Fryberger and Dean (1979) for the first time. In order to draw this Graph, winds that were faster than the erosion velocity threshold were developed into vector units as sand drift potential. Discussion Mobility is the most important characteristic of sand dunes. In this regard, special attention should be paid to the importance of wind in changing the sand dunes morphology. In addition, studies of sand dunes migration provide basic knowledge about wind processes and sand transfer values. In this study, monitoring and detection of the sand dunes relocation rate have been considered based on the use of Landsat images (for the years 2001-2019). At the first stage, the regions that have been faced changes were identified using the change detection technique for the entire range of Erg. Based on the output map, marked areas with the red color experienced the maximum changes, and also, in this section, sand dunes have been more developed. The differences between the two images within the sand dunes area were estimated at about 23 km2. However, the pattern of sand dunes migration represents relocation from the Northwest to the Southeast. At the next stage of the study, to understand the change rate and relocation trend, Google Earth images were used (years 2006 and 2018). Furthermore, the region with significant changes has been selected for a closer look. Moreover, using Stitch Map software, the georeferenced images were extracted. It worth mentioning that, from the five selected zones on the Erg surface, a total of 368 cases of sand dunes were quantitatively analyzed. According to the results, the greatest amount of migration was found for zone 3 with the amount of 24.72 m, in contrast, the lowest value was calculated at about 14.16 m for zone 5. In addition, the migration average rate for a period of 12 years was calculated. Here, the maximum migration belonged to zone 3 which is 2.06 meters per year. While the minimum one allocated to zone 5 was 1.18 meters per year. Conclusion In this study, the authors monitored changes in sand dunes using satellite imagery data and wind data of meteorological stations of Zahak Erg. In this regard, the sand dunes activity rate, dunes migration pattern, and also factors affecting their intensity and patterns were identified. The results of the 368 studied sand dunes in different parts of the erg surface indicated displacement with a northwest-southeast trend, which is consistent with the results of data analysis for wind pattern. But the average amount of displacement of 1.53 meters per year for a period of 12 years (2006 to 2018) with the results of data from Zabol wind station showed the amount of sand carrying more than 300 tons per meter for a year. The changes in wind speed at this station were inconsistent and it was shown that the maximum value obtained was before the stabilization of the active sand dunes. In addition, smooth sands move on the surface of the earth, independent of sand dunes, which cannot be measured by images. Keywords: Sand Dunes, Remote Sensing, Wind Data, Wind erosion, Zahak Erg. References: - Ahmadi, H. (2006). Applied Geomorphology Volume 2 Desert- Wind Erosion. Tehran: University of Tehran Press. - Ahmadian, M. A. (2008). Desert (A Systematic Approach to the Desertification and Desertification Process). Geographical Research Quarterly, 2(53), 146-159. - Al-Awadhi, J. M., Al-Helal, A., & Al-Enezi, A. (2005). Sand Drift Potential in the Desert of Kuwait. Journal of Arid Environments, 63, 425–438. - Bagnold, R. A. (1941). The Physics of Blown Sand and Desert Dunes. London: Chapman and Hall, pp. 104–106. - Baitis, E., Kocurek, G., Smith, V., Mohrig, D., Ewing, R. C., & Peyret, A. P. B. (2014). Definition and Origin of the Dune-Field Pattern at White Sands, New Mexico. Aeolian Research, 15, 269–287. - Delgado-Fernandez, I., & Davidson-Arnott, R. (2011). Meso-Scale Aeolian Sediment Input to Coastal Dunes: The Nature of Aeolian Transport Events. Geomorphology, 126(1-2), 217-232. - Dong, Z., Wang, T., & Wang, X. (2004). Geomorphology of the Megadunes in the Badain Jaran Desert. Geomorphology, 60(1-2), 191-203. - Ebrahimzadeh, I. (2018). A Regional Analysis of Urban-Rural Relationships in Sistan. PhD Thesis in Geography and Urban-Regional Planning, Faculty of Literature and Humanities, University of Isfahan, pp. 85-65. - Fryberger, S. G., AL‐Sari, A. M., Clisham, T. J., Rizvi, S. A., & ALHinai, K. G. (1984). Wind Sedimentation in the Jafurah Sand Sea, Saudi Arabia. Sedimentology, 31(3), 413-431. - Fryberger, S. G., & Dean, G. (1979). Dune Forms and Wind Regime. USA: Geological Survey Professional Paper 1052–F, pp. 137–169. - Gillies, J. A., & Lancaster, N. (2013). Large Roughness Element Effects on Sand Transport, Oceano Dunes, California. Earth Surface Processes and Landforms, 38(8), 785-792. - Hamdan, M. A., Refaat, A. A., & Wahed, M. A. (2016). Morphologic Characteristics and Migration Rate Assessment of Barchan Dunes in the Southeastern Western Desert of Egypt. Journal of Geomorphology, 257, 57-74. - Hereher, M. E. (2018). Geomorphology and Drift Potential of Major Aeolian Sand Deposits in Egypt. Journal of Geomorphology, 304, 113-120. - Hermas, E., Leprince, S., & Abou El-Magd, I. (2012). Retrieving Sand Dune Movements Using Sub-Pixel Correlation of Multi-Temporal Optical Remote Sensing Imagery, Northwest Sinai Peninsula, Egypt. Journal of Remote Sensing of Environment, 121, 51-60. - Hesp, P. A., Davidson-Arnott, R., Walker, I. J., & Ollerhead, J. (2005). Flow Dynamics Over a Foredune at Prince Edward Island, Canada. Journal of Geomorphology, 65(1-2), 71-84. - Housing Foundation of the Islamic Revolution of Sistan and Baluchestan Province. (2019). Technical Unit and Rural Development Studies. - Khosravi, M. (2005). Research Project of Ecological and Environmental Effects of 120-Day Winds in Sistan. Environmental Protection Organization of Sistan and Baluchestan Province, Consultant of Sistan and Baluchestan Institute of Earth Sciences and Geography, p.300. - Kuriyama, Y., Mochizuki, N., & Nalashima, T. (2005). Influence of Vegetation on Aeolian Sand Transport Rate from a Backshore to a Foreshore at Hasaki, Japan. Journal of Sedimentology, 52(5), 1123–1132. - Lancaster, N., Nickling, W. G., & Gillies, J. A. (2010). Sand Transport by Wind on Complex Surfaces: Field Studies in the McMurdo Dry Valleys, Antarctica. Journal of Geophysical Research: Earth Surface, 115(3). - Latifi, L. (2006). Investigating the Progress of Sand Dunes Using Satellite Images in Recent Droughts in the North and East of Sistan Plain. Master Thesis, Department of Geography, Islamic Azad University, Mashhad Branch. - Liu, L.Y., Skidmore, E., Hasi, E., Wagner, L., & Tatarko, J. (2005). Dune Sand Transport as Influenced by Wind Directions, Speed and Frequencies in the Ordos Plateau, China. Journal of Geomorphology, 67(3-4), 283–297. - Maghsoudi, M., Mohammadi, M., Khanbabaei, Z., Mahboubi, S., Baharvand, M., & Hajizadeh, A. H. (2017). Monitoring the Movement of Erg and Barkhans in the West of Lut (Peshouieh). Journal of Quantitative Geomorphological Research, 5(4), 189-176. - Maghsoudi, M., Navidfar, A., & Mohammadi, A. (2017). The Sand Dunes Migration Patterns in Mesr Erg Region Using Satellite Imagery Analysis and Wind Data. Journal of Natural Environment Change, 3(1), 33-43. - Mohamed, I. N., & Verstraeten, G. (2012). Analyzing Dune Dynamics at the Dune-Field Scale Based on Multi-Temporal Analysis of Landsat-TM Images. Journal of Remote Sensing of Environment, 119, 105-117. - Negaresh, H., & Latifi, L. (2008). Geomorphological Analysis of the Progress of Sand Dunes East of the Sistan Plain in Recent Droughts. Journal of Geography and Development, 6(12), 60-43. - Noroozhi, F. (1993). Investigating the Destructive Effects of Helmand River Floods. MA Thesis, Department of Geography, Sistan and Baluchestan University, p.195. - Piri, H., Abbaszadeh, M., Rahdari, V., & Maleki Najafabadi, S. (2013). Comparative Assessment of 4 Meteorological Drought Indices Using Cluster Analysis Method (Case Study of Sistan and Baluchestan Province). Journal of Water Resources Engineering, 6(17), 25-36. - Pye, K., & Tsoar, H. (2009). Aeolian Sand and Sand Dunes. Berlin: Springer-Verlag. - Salighe, M. (2003). Attention to the Wind in the Construction of the Physical Body of Zabol. Journal of Geography and Development, 1(2), 109-121. - Sargzi, H. (2005). Origin and Assessment of Severity and Damage of Sand Dunes in Niatak Sistan Desert. Master Thesis, Gorgan University of Natural Resources, p.136. - Sherman, D. J., & Li, B. (2012). Predicting Aeolian Sand Transport Rates: A Reevaluation of Models. Journal of Aeolian Research, 3(4), 371-378. - Sparavigna, A. C. (2013). A Study of Moving Sand Dunes by Means of Satellite Images. International Journal of Sciences, 2. - Tsoar, H. (2005). Sand Dunes Mobility and Stability in Relation to Climate. Physica A: Statistical Mechanics and its Applications, 357(1), 50-56. - Wang, X., Eerdun, H., Zhou, Z., & Liu, X. (2007). Significance of Variations in the Wind Energy Environment over the Past 50 Years with Respect to Dune Activity and Desertification in Arid and Semiarid Northern China. Journal of Geomorphology, 86(3-4), 252-266. - Wiggs, G. F. S., Atherton, R. J., & Baird, A. J. (2004). Thresholds of Aeolian Sand Transport: Establishing Suitable Values. Journal of Sedimentology, 51(1), 95-108. - Yao, Z. Y., Wang, T., Han, Z. W., Zhang, W. M., & Zhao, A. G. (2007). Migration of Sand Dunes on the Northern Alxa Plateau, Inner Mongolia, China. Journal of Arid Environments, 70(1), 80-93. - Yurk, B. P., Hansen, E. C., & Hazle, D. (2013). A Deadtime Model for the Calibration of Impact Sensors with an Application to a Modified Miniphone Sensor. Journal of Aeolian Research, 11, 43-54. - Zhang, G., Azorin-Molina, C., Shi, P., Lin, D., Guijarro, J. A., Kong, F., & Chen, D. (2019). Impact of Near-Surface Wind Speed Variability on Wind Erosion in the Eastern Agro-Pastoral Transitional Zone of Northern China, 1982–2016. Agricultural and Forest Meteorology, 271, 102-115. - Zhang, Z., Dong, Z., & Li, C. (2015). Wind Regime and Sand Transport in China’s Badain Jaran Desert. Journal of Aeolian Research, 17, 1-13.

https://gep.ui.ac.ir/article_25195_742c6a11e1c94171c127df1e26660d3e.pdf