دانشگاه اصفهان برنامه ریزی فضایی 2228-7485 14 4 2024 12 21 Optimizing Sustainable Rural Tourism: Key Factors for Development in Semi-Arid Regions (A Case Study of Abadeh County) تبیین استراتژی مطلوب مبتنی بر عوامل مؤثر در توسعۀ گردشگری پایدار روستایی در نواحی نیمهخشک (مورد مطالعه: شهرستان آباده) 1 26 28720 10.22108/sppl.2024.142303.1800 FA امید خادم حسینی دانشجوی دکتری جغرافیا و برنامه‌ریزی روستایی، دانشگاه شهید بهشتی، تهران، ایران 0000-0001-5089-7352 بیژن رحمانی بیژن رحمانی، دانشیار، دانشکدۀ علوم زمین، گروه جغرافیای انسانی و آمایش، دانشگاه شهید بهشتی، تهران، ایران شهریار خالدی استاد، دانشکدۀ علوم زمین، گروه جغرافیای طبیعی، دانشگاه شهید بهشتی، تهران، ایران علی اصانلو دانشیار، گروه جغرافیا، دانشکدۀ فرماندهی و ستاد، دانشگاه جامع علوم انتظامی امین، تهران، ایران Journal Article 2024 07 30 Abstract Background: Tourism plays a crucial role in rural development, serving as a valuable approach for economic growth. Effective development in this sector requires a thorough understanding of both internal and external factors to ensure stability. The semi-arid regions of Iran present unique conditions for the advancement of tourism. Purpose: This research aimed to identify optimal strategies for developing sustainable rural tourism in Iran's semi-arid areas, specifically focusing on Abadeh County. The study analyzed internal and external factors to provide actionable insights. Research Method: The research employed a quantitative, descriptive-analytical approach through surveys. The statistical population consisted of experts from various departments in Abadeh County with a sample size of 50 participants determined using the snowball sampling method. Data were collected using a researcher-designed questionnaire that included internal and external factors. Analyses were conducted using SWOT, AHP, and VIKOR models. Findings: The results indicated that the key strengths, weaknesses, opportunities, and threats affecting sustainable rural tourism development included: the spirit of ethnocentrism and collectivism in villages (final weight: 0.388); a lack of tourist accommodations in villages (final weight: 0.427); the potential for attracting private sector investment (final weight: 0.375); and the challenges posed by drought and water scarcity in recent years (final weight: 0.523). The most effective strategy identified for the development of sustainable rural tourism in semi-arid areas was diversification, particularly focusing on attracting investment and enhancing tourism branding. Additionally, the VIKOR model identified the villages of Bidak and Firuzi as top priorities for implementing effective diversification strategies in tourism development. Keywords: Strategy, Sustainable Tourism, Rural Development, Semi-Arid Areas, Abadeh County. Introduction In the semi-arid regions of Iran, the sustainability challenges posed by climatic and environmental conditions are particularly significant. Tourism in these rural areas offers a promising solution to mitigate environmental impacts and tensions as it fosters economic diversification and reduces residents' reliance on natural resources. Abadeh County, a notable semi-arid area, holds considerable potential for tourism development. The villages within this region boast various assets, including ethnic and cultural diversity, ecotourism attractions, a culture of hospitality, handicrafts, community cooperation, and strategic geographic locations. To harness these strengths, it is essential to create a framework that aligns with tourism objectives, enabling rural areas in semi-arid regions to achieve sustainability. Developing optimal strategies that consider both the capacities and limitations of Abadeh County's villages is crucial. A thorough understanding of the tourism landscape will not only clarify the current situation, but also inform the strategies and priorities necessary for advancing rural tourism. This research aimed to explain optimal strategies for developing sustainable rural tourism in the semi-arid areas of Iran, focusing specifically on Abadeh County through an analysis of internal and external factors. Materials & Methods This study employed a descriptive-analytical research method classified as applied research based on its objectives. Data were collected through a survey using a structured questionnaire. The validity of the questionnaire was assessed by experts, while reliability was evaluated by administering the questionnaire to a sample outside the primary statistical group. For reliability testing, 30 individuals were randomly selected from outside the main sample and the data analysis confirmed a Cronbach's alpha coefficient of greater than 0.70. The statistical population consisted of experts from various departments in Abadeh County. Due to research constraints, 50 experts were identified and surveyed using the snowball sampling method. Data analysis was conducted by utilizing the SWOT model, AHP model, and VIKOR method. Research Findings Development of sustainable rural tourism is influenced by a variety of promoting and hindering factors. Among the positive factors (strengths and opportunities) were the spirit of ethnocentrism and collectivism in the villages, diversity of rural tourism attractions, hospitality culture of the local residents, a potential for private sector investment, and enhancement of income and employment opportunities for villagers. Additionally, the region possessed a significant potential for nomadic tourism and branding rural tourism. Conversely, the main inhibiting factors (weaknesses and threats) included a lack of tourist accommodations, insufficient rural tourism services and facilities, limited awareness of the region’s tourism potential, drought, water scarcity, and emergence of a new communication route between Isfahan and Shiraz, alongside the region's hot and dry climate. Each of these factors significantly impacted the process of sustainable rural development through tourism. Effective management and mitigation of tensions in this area were crucial. Given the interplay between promoting and inhibiting factors, it was possible to leverage the strengths and opportunities to address and reduce the weaknesses and threats. Analysis of the results indicated that the most critical strategies for developing sustainable rural tourism in the semi-arid regions of Iran centered around diversification. These strategies focused on capitalizing on opportunities while minimizing weaknesses. The analysis of proposed strategies for the villages of Abadeh revealed that attracting investment to enhance rural infrastructure was the most vital diversification strategy. Additionally, prioritization of the villages for implementing these diversification strategies identified Bidak, Firouzi, and Heshmatiyeh as the top three priorities for the execution of effective strategies. Discussion of Results & Conclusion The findings indicated that the semi-arid areas studied possessed a range of limitations and capacities concerning tourism development. It was crucial to acknowledge these limitations and address them by leveraging available opportunities and driving factors in rural tourism. The region held significant potential for tourism, which could contribute to the sustainability of its villages. The optimal strategy identified was a diversification strategy where weaknesses were mitigated by capitalizing on opportunities. To effectively implement this strategy, it is recommended that planning for the villages be prioritized based on their tourism potential. Additionally, a comprehensive approach to tourism advertising and branding for semi-arid rural areas should be developed and executed to enhance visibility and attract visitors. امروزه گردشگری به‌عنوان یک رویکرد مطلوب در توسعۀ روستایی نقش مهمی دارد. توسعۀ این بخش اقتصادی نیازمند شناخت عوامل داخلی و خارجی مؤثر با هدف ایجاد پایداری است. نواحی نیمه‌خشک ایران شرایط خاص خود را برای توسعۀ این بخش دارد. پژوهش حاضر با هدف تبیین استراتژی مطلوب مبتنی بر تحلیل عوامل داخلی و خارجی برای توسعۀ گردشگری پایدار روستایی در نواحی نیمه‌خشک ایران به‌صورت موردی شهرستان آباده انجام شده است. این پژوهش از‌نظر ماهیت در زمرۀ پژوهش‌های کمّی و از نوع توصیفی–تحلیلی با رویکرد پیمایشی است. جامعۀ آماری پژوهش کارشناسان اداره‌های شهرستان آباده بوده است که با روش گلوله‌برفی حجم نمونه 50 نفر تعیین شد. ابزار گردآوری داده‌ها پرسشنامۀ محقق‌ساخته شامل عوامل داخلی و خارجی بوده است. تحلیل‌ها با سه مدل SWOT، AHP و Vokor انجام شده است. نتایج نشان داد که مهم‌ترین عوامل قوت، ضعف، فرصت و تهدید به‌ترتیب در‌زمینۀ توسعۀ گردشگری پایدار روستایی شامل روحیۀ قوم‌گرایی و جمع‌گرایی در روستاها با وزن نهایی (388/0)، کمبود اقامتگاه گردشگری در روستاها با وزن نهایی (427/0)، امکان جذب سرمایه‌گذاری از بخش خصوصی با وزن نهایی (375/0)، خشکسالی و کم‌آبی در سال‌های اخیر با وزن نهایی (523/0) است. در این مطالعه بهترین استراتژی برای تحقق توسعۀ گردشگری پایدار روستایی «استراتژی تنوع» تعیین شد که مهم‌ترین آنها شامل جذب سرمایه در‌حوزۀ گردشگری و برندسازی است. همچنین، بر‌اساس مدل ویکور روستای بیدک و فیروزی در اولویت اجرای استراتژی‌های مطلوب از نوع تنوع برای توسعۀ گردشگری شناخته شدند.

https://sppl.ui.ac.ir/article_28720_eca3264efced3b6b04e916a55384e052.pdf

دانشگاه اصفهان برنامه ریزی فضایی 2228-7485 14 4 2024 12 21 Spatial Analysis of the Concentration of Knowledge-Based Firms in Iran تحلیل تمرکز فضایی شرکت‌های دانش‌بنیان در ایران 27 52 28721 10.22108/sppl.2024.138926.1742 FA نجم الدین یزدی پژوهشگر پژوهشکدۀ سیاست‌گذاری، دانشگاه صنعتی شریف، تهران، ایران مهدی فاتح راد عضو هیئت‌علمی پژوهشکدۀ سیاست‌گذاری، دانشگاه صنعتی شریف، تهران، ایران جمال کدخداپور مدیرعامل سازمان عامل استقرار و توسعه منطقه ویژه علم و فناوری یزد، یزد، ایران سیامک طهماسبی پژوهشگر پژوهشکده سیاستگذاری، دانشگاه صنعتی شریف، تهران، ایران Journal Article 2023 09 17 Abstract The significance of knowledge-based firms in transitioning to a knowledge-based economy and fostering regional development has become increasingly evident to researchers and policymakers. Over the past decade, Iran has witnessed remarkable growth in knowledge-based firms supported by various financial and non-financial incentives from the government. However, research has largely overlooked the spatial patterns of distribution and concentration of these firms at both national and sub-national levels, as well as the factors driving their concentration in specific regions. Understanding these spatial patterns and centralizing forces is crucial for policymakers aiming to design effective strategies for the development of peripheral regions and establishment of a regional innovation system. This study aimed to analyze the spatial concentration of knowledge-based firms and the factors influencing this process. To measure spatial concentration, we employed global Moran’s I and Getis-Ord Gi* statistics, while Ordinary Least Squares (OLS) regression was used to identify determinants. The results indicated that the distribution of knowledge-based firms was predominantly concentrated in metropolitan areas with no significant clusters forming in marginal regions, which had not reaped the associated benefits. The centralizing forces of economies of scale and urbanization had played a pivotal role in this spatial concentration. Additionally, our findings revealed a low degree of specialization among knowledge-based firms. Finally, we presented policy implications aimed at providing incentives for the geographical redistribution of knowledge-based firms in less developed and peripheral regions, while also promoting regional specialization. Keywords: Knowledge-Based Firms, Spatial Concentration; Urbanization Economies, Economies of Scale, New Economic Geography. Introduction Knowledge is a fundamental driver of economic growth and a crucial component in enhancing competitiveness among countries and regions. In the shift toward a knowledge-based economy, knowledge-based firms play a vital role and have garnered increasing attention from both academic literature and policymakers. Industries and companies tend to cluster in specific locations, a phenomenon supported by extensive global evidence. The study of the geographic concentration of economic activities has a long history and has gained significant interest in recent years. Geographic concentration is essential for regional development as it enhances efficiency and fosters innovation among firms. However, some studies have also highlighted its negative aspects, such as the exacerbation of regional inequality. The self-reinforcing nature of spatial concentration creates favorable economic conditions for certain areas while leaving others relatively underdeveloped. Moreover, in regions where companies, industries, and populations are concentrated, negative externalities can arise, including congestion costs, pollution, high land rents, and disruptions to essential services, such as healthcare, education, and urban infrastructure. In Iran, the number of knowledge-based firms has grown significantly over the past decade with over 8,400 firms now registered. Given the importance of these firms in regional development, it is crucial to examine their geographic distribution patterns and concentration. A comprehensive understanding of the spatial distribution of knowledge-based firms is essential for policymakers seeking to implement effective innovation and regional policies at local, regional, and national levels. This research aimed to analyze the spatial distribution and concentration of knowledge-based firms in Iran and investigate the factors that contributed to this concentration. Materials & Methods This research was classified as applied and exploratory-confirmatory in nature, employing various methods to achieve its objectives. To measure the spatial concentration of knowledge-based firms, we utilized global Moran's I and local Moran's I statistics, along with Ordinary Least Squares (OLS) regression, to model the relationships between determining factors and spatial concentration. Data on knowledge-based firms were obtained from the website of the Vice Presidency for Technology and the Knowledge-Based Economy, while the data related to the independent variables were sourced from the annual publications of the Iranian Statistics Center. Research Findings The spatial distribution of knowledge-based companies was analyzed across several technology fields: 1) electricity and electronics, photonics, telecommunications, and automation systems; 2) information and communication technology and software; 3) advanced machinery and equipment; 4) advanced medicine, diagnostic, and treatment products; 5) commercialization services; 6) biotechnology, agriculture, and food industries; 7) cultural industries, creative industries, and human sciences; 8) medical devices, necessities, and equipment; and 9) advanced materials and products based on chemical technologies. The findings indicated a significant increase in the number of companies. In terms of technology sectors, the largest concentrations were found in electricity and electronics (1,822 companies), information technology (1,777 companies), and advanced machinery and equipment (1,721 companies). However, the distribution of knowledge-based firms was uneven, primarily concentrated in specific regions, particularly in the North-West (East Azerbaijan) and North-East (Khorasan-Razavi) areas. Notably, over half of the knowledge-based firms (51.5%) were located in Tehran Province followed by Isfahan (9.3%) and Razavi Khorasan (5.3%). This distribution aligned with the presence of metropolitan areas (cities with populations exceeding one million). Additionally, the degree of specialization among companies was assessed using the Herfindahl index, revealing an overall low level of specialization. In contrast, the southern and southeastern provinces demonstrated greater diversity in their knowledge-based industries. The Moran's I index for the total number of knowledge-based firms, as well as for specific fields, such as electricity and electronics, advanced machinery and equipment, advanced materials and technology-based products, and medical devices and equipment, yielded positive values. With 999 random permutations, these results were significant at a level of less than 0.005. Thus, we rejected the assumption of randomness in the distribution of these firms and confirmed the presence of clustering, indicating spatial dependence in the data distribution. In contrast, Moran's I values for firms in information and communication technology, commercialization services, and biotechnology and agriculture were not significant, suggesting a lack of spatial autocorrelation. To identify local clusters, we employed the Getis-Ord statistic, which revealed a substantial cluster of high concentrations of knowledge-based firms extending from the northern region (Mazandaran Province) to the central areas (Isfahan Province). Conversely, clusters of low concentrations were observed in Hormozgan and Ilam provinces. We utilized the OLS regression model to analyze the conditions and factors influencing the concentration of knowledge-based companies in specific regions. The results indicated that the independent variables accounted for 36% of the variance. Among these variables, the rate of industrialization and logarithm of the population in provincial capitals exhibited a positive and significant relationship with the concentration of knowledge-based firms. In contrast, the percentage of individuals with higher education and GDP share of provinces did not show significant correlations. Higher rates of industrialization and larger populations in provincial capitals were associated with greater concentrations of knowledge-based companies. This suggested that firms were more likely to establish themselves in areas with a robust industrial presence, which provided the necessary infrastructure, resources, and business ecosystem to support innovation and technological advancement. Additionally, larger urban populations typically offered more potential customers, a larger talent pool for skilled labor, and better access to services and amenities, all of which were attractive factors for knowledge-based companies. Discussion of Results & Conclusion Utilizing spatial data allowed us to circumvent the limitations associated with classical statistical methods for measuring spatial concentration. The findings indicated that knowledge-based firms exhibited autocorrelation and were concentrated in clusters within specific regions. However, the overall degree of specialization among these firms remained low. Clustering served as a strategy to leverage the positive externalities associated with spatial concentration. The concentration of knowledge-based firms was not attributable to a single factor; rather, a combination of centripetal forces drove this phenomenon. In this study, we focused on several of these centripetal forces with urbanization economies and economies of scale identified as the most significant contributors to the concentration of firms in particular areas. The results had important implications for policies aimed at امروزه اهمیت شرکت‌های دانش‌بنیان در گذار به اقتصاد دانش‌بنیان و توسعۀ منطقه‌ای برای پژوهشگران و سیاست‌گذاران آشکار شده است. شرکت‌های دانش‌بنیان طی یک دهۀ گذشته در ایران رشد چشمگیری داشته و دولت نیز مشوّق‌های مالی و غیرمالی متعدّدی را برای رشد و گسترش آنها انجام داده است؛ با این ‌حال شناسایی الگوهای فضایی توزیع و تمرکز شرکت‌های دانش‌بنیان در‌سطح ملی-منطقه‌ای و شرایطی که آنها را به‌سوی تمرکز در مناطق خاصی سوق می‌دهد، مورد غفلت واقع ‌شده است. شناخت و درک این الگوهای فضایی و نیروهای تمرکزگرا می‌تواند به سیاست‌گذاران در طراحی سیاست‌های کارآمد برای توسعۀ مناطق حاشیه‌ای و ایجاد نظام نوآوری منطقه‌ای کمک کند. پژوهش حاضر با هدف تحلیل توزیع فضایی شرکت‌های دانش‌بنیان و عواملی که تمرکز فضایی را شکل می‌دهد، انجام شده است. در این مطالعه برای سنجش تمرکز فضایی از روش‌های Global Moran’s I وGettis-Ord Gi* و برای شناسایی نیروهای مؤثر بر تمرکز از رگرسیون حداقل مربعات استفاده شده است. نتایج نشان داد شرکت‌های دانش‌بنیان بیشتر در کلانشهر‌ها توزیع شده و خوشه‌های آن در مناطق حاشیه‌ایی شکل نگرفته است؛ بنابراین چنین مناطقی از مزیت‌های این شرکت‌ها بهره‌مند نشده است. دو نیروی تمرکزگرای صرفه‌های ناشی از شهرنشینی و مقیاس نقش مهمی در تمرکز فضایی شرکت‌های دانش‌بنیان داشته‌اند. همچنین، یافته‌ها نشان داد که میزان تخصصی‌شدن شرکت‌های دانش‌بنیان پایین است. در پایان، دلالت‌های سیاستی با هدف ارائۀ مشوّق‌های لازم برای باز‌توزیع جغرافیایی شرکت‌های دانش‌بنیان در مناطق کمتر توسعه‌یافته و حاشیه و حرکت به‌سوی تخصصی‌شدن منطقه‌ای ارائه شد.

https://sppl.ui.ac.ir/article_28721_5cd6315f1e11ebe94ed36e7c8a36f0c0.pdf

دانشگاه اصفهان برنامه ریزی فضایی 2228-7485 14 4 2024 12 21 Impact of Climate Change on Groundwater in Cham Anjir Aquifer تأثیر تغییر اقلیم بر منابع آب زیرزمینی حوضة آبخیز چم انجیر 53 80 28747 10.22108/sppl.2024.141550.1790 FA مریم آریا صدر دانشجوی دکتری اقلیم شناسی، گروه جغرافیا طبیعی ، دانشکده علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان، اصفهان، ایران. داریوش رحیمی استاد هیدرواقلیم، گروه جغرافیای طبیعی، دانشکده علوم جغرافیایی و برنامه ریزی ،دانشگاه اصفهان، اصفهان، ایران هادی امیری دانشیار اقتصاد، گروه اقتصاد ،دانشکده اقتصاد و علوم اداری ، دانشگاه اصفهان، اصفهان، ایران مهران زند دانشیار ، پژوهشکده حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران. Journal Article 2024 05 25 Abstract Groundwater and aquifers play a crucial role in sustaining human life and ecosystems, serving as vital sources for drinking water, agriculture, industry, and regulation of water and land systems. This study focused on Cham Anjir Basin representative of the Karkheh River to assess the impact of climate change on water resources. We utilized hydroclimatic data, including discharge, water levels, well discharge, number of wells, precipitation, temperature, and groundwater quality parameters, covering the statistical period from 1991 to 2020. To estimate the effects of climate change on water resources, we applied the output from the Lars-WG7 exponential microscale model for the two future periods of 2021-2040 and 2041-2060 under optimistic, realistic, and pessimistic scenarios. Our findings indicated significant increases in well withdrawals, temperature, Total Hardness (TH), Sodium Adsorption Ratio (SAR), and sodium percentage in groundwater, alongside a significant decline in discharge. According to the HadCM3 model outputs, rainfall in the basin was projected to increase from 2021 to 2060 compared to the observed period (1991-2020). However, a decrease in rainfall was expected from 2041 to 2060 relative to the previous period (2021-2040). Discharge was anticipated to decline consistently from 2021 to 2060. The regression model relating discharge and precipitation suggested that groundwater levels would decrease during 2021-2060, while groundwater quality indicators (anions, cations, and electrical conductivity) were expected to rise. Given the reliance on groundwater due to limited surface water resources, the impacts of climate change on both the quality and quantity of groundwater were significant. Therefore, advancements in water management, technology, and education would be essential in mitigating the effects of climate change on groundwater resources. Keywords: Aquifer, Climate Change, Discharge, Cham Anjir, Water Quality. Introduction Groundwater and aquifers are essential for the survival of humans and other living organisms, serving as vital sources for drinking water, agriculture, industry, and regulation of ecosystems. Given their importance, it is crucial to protect these resources. Over-extraction of aquifers, pollution from industrial and agricultural effluents, and impacts of climate change are significant factors threatening the quantity and quality of groundwater resources. Climate change poses a serious challenge to water resources as various climatic, human, and geological factors jeopardize groundwater availability. Poor management and over-exploitation of natural resources, particularly in water management, have led to declines in both the volume and quality of water in river headwaters. This issue is particularly evident in the Karkheh River Basin. This study aimed to assess the effects of climate change on groundwater quality in the upper reaches of the Karkheh River, specifically in Cham Anjir Sub-basin in Lorestan Province. Changes in precipitation and temperature, along with the over-extraction of groundwater, had resulted in a decrease in reservoir levels in Cham Anjir Basin. Variations in water levels, precipitation, and discharge also indicated frequent droughts and water shortages in the area. Concurrently, there was a significant upward trend in both minimum and maximum temperatures, while discharge levels were significantly declining. Additionally, recent statistical data revealed an increase in the number of wells in Cham Anjir Basin, highlighting the growing demand for groundwater resources. Materials & Methods To investigate the effects of climate change on the quantity and quality of groundwater resources in Cham Anjir Basin, we utilized hydroclimatic data, including discharge, water table levels, well discharge, water quality parameters, precipitation, and temperature. These data were sourced from hydrometric stations, observation wells, meteorological stations, and the statistical yearbook of Lorestan Province, covering the period from 1951 to 2021. For analyzing the future impacts of climate change on water quantity, we employed scenarios SSp1-2.6, SSP2-4.5, and SSP5-8.5 from the sixth climate change assessment report, focusing on two timeframes: 2020-2040 and 2040-2060. The LarsWG7 microscale model was also used in this analysis. In this study, we applied the Z-score method to identify trends in climatic data and water quality parameters and detect data anomalies. Pettitt's Test was utilized for homogenization to determine the turning points in the data. We used correlation coefficients and regression models to identify the most اضافه برداشت از آبخوان‌ها، تغییر اقلیم، فعالیت‌های انسانی و زمین‌شناسی از‌جمله عوامل اثرگذار بر کمیت و کیفیت منابع آب زیرزمینی است. در پژوهش حاضر برای ارزیابی تغییر اقلیم بر منابع آب از داده‌های روزانة دبی، ایستابی، تخلیۀ چاه، بارش، دما و کیفیت آب زیرزمینی (در سال‌های 1991-2021 آبخوان چم انجیر) در‌ حوضۀ خرم‌آباد استفاده شد. یافته‌ها نشان داد که در‌حوزۀ چم انجیر روند برداشت از چاه، دما و شاخص‌های شیمیایی نسبت جذب سدیم (SAR) و درصد سدیم (% Na) افزایشی معنادار و سختی کل (TH) و روند دبی کاهشی معنادار داشته است. طبق خروجی مدل، تغییرات بارش در دورۀ 2041-2060نسبت به دورۀ مشاهداتی کاهش و دورۀ 2021-2040 نسبت به دورۀ مشاهداتی افزایش خواهد داشت؛ اما مقدار دبی در دورۀ 2021-2060 کاهش خواهد یافت. روند افزایشی دو عنصر SAR و %Na تحت‌تأثیر کل مواد جامد محلول (TDS) و هدایت الکتریکی (EC) است. با افزایش TDS و EC میزان SAR و Na % افزایش می‌یابد. همبستگی TDS با Na% و SAR به‌ترتیب ۷۱۵/۰ و ۶۳۶/۰ و همبستگی بین EC با SAR و %Na به‌ترتیب ۷۱۳/۰ و ۶۳۵/۰ است. بر‌اساس مدل رگرسیون دبی و بارش، سطح ایستابی در دوره‌های 2021 تا 2060 روند کاهشی و عناصر کیفیت آب زیرزمینی (آنیون، کاتیون و هدایت الکتریکی) روند افزایشی خواهد داشت. نتیجۀ این تغییرات کاهش کمیت و کیفیت منابع آب زیرزمینی و افزایش تنش‌های آبی است؛ بنابراین بازنگری در مدیریت و تخصیص منابع آب، سازگاری با تغییر اقلیم، مدیریت الگوی کشت، افزایش راندمان آبیاری و تعامل با جوامع محلی و ذی‌نفعان می‌تواند در بهبود شرایط مؤثر باشد.

https://sppl.ui.ac.ir/article_28747_24fe813b16eaaacbf16042de264a09fc.pdf

دانشگاه اصفهان برنامه ریزی فضایی 2228-7485 14 4 2024 12 21 Analysis of Factors Affecting Political Participation in Rural Communities: A Case Study of Lenjan Township تحلیل عوامل مؤثر بر مشارکت سیاسی در جوامع روستایی (مطالعۀ موردی: شهرستان لنجان) 81 102 28953 10.22108/sppl.2024.141754.1792 FA اصغر نوروزی دانشیار گروه جغرافیا و برنامه‌ریزی روستایی، دانشگاه پیام نور، تهران، ایران 0000-0002-5609-7855 Journal Article 2024 06 10 Abstract Participation is a crucial indicator of sustainable rural development and political participation serves as a benchmark for the political development of societies. In rural areas with a substantial portion of the population, fostering political engagement is essential for achieving this goal at the national level. This research evaluated and analyzed the factors influencing political participation among the villagers of Lenjan Township. The study was applied in nature, employing a descriptive-analytical and survey-based methodology. Data collection involved both library research and field methods, specifically through the administration of a researcher-designed questionnaire. A total of 250 villagers over the age of 18, eligible to participate in elections, were surveyed using a simple random sampling method and interviews. The validity of the questionnaire was confirmed by experts and its reliability was measured using Cronbach's alpha, which yielded a score of 0.78. For data analysis, appropriate descriptive statistics (mean, percentage, graphs) and inferential statistics (one-sample t-test) were applied, alongside factor analysis using SPSS, Excel, and GIS software. The results indicated that the overall level of participation was higher than average with a mean score of 3.51. Among the various components of political participation, the "voting" aspect stood out with the highest average of 4.13. Factor analysis revealed that political awareness, media influence, social factors, and government performance were the most significant determinants of political participation, collectively accounting for 65.91% of the total variance. Additionally, correlation analysis showed no significant relationship between voting participation and individual characteristics, such as gender, age, marital status, and education. Keywords: Political Participation, Election, Village, Lenjan. Introduction Participation has been an integral part of human life since ancient times and its significance has only grown in contemporary society. It serves as a foundation for social solidarity and national support. As such, public participation is a fundamental condition and operational aspect of development often equated with the concept of development itself. Involvement of rural communities in shaping their own destinies is a key principle of rural governance. Political participation is essential for the political development of nations, encompassing voluntary and conscious actions taken either directly or indirectly to influence decisions related to societal administration. It plays a crucial role in assessing the legitimacy and effectiveness of political systems. Among the various forms of political participation, voting is the most practical and accessible means for citizens to engage in the political process. Numerous factors influence electoral participation and behavior, which can vary across different election cycles. Additionally, according to the latest data from the Iranian Statistics Center, 26% of the country's population resides in rural areas. Ignoring this demographic influence in elections poses significant risks to the political landscape. Therefore, this study aimed to investigate and analyze the factors affecting the level of political participation among the rural population of Lenjan Township. Materials & Methods This research was practical in nature, employing a descriptive-analytical and survey-based methodology. Data collection utilized both library and field methods. The library component involved reviewing books, articles, and electronic resources to compile the theoretical foundations and background relevant to the study. In the field component, the researcher visited selected villages and engaged directly with residents to administer the questionnaire. The statistical population consisted of individuals aged 18 and older. A total of 250 questionnaires were completed for analysis. The validity of the research instrument was confirmed by expert evaluation, and its reliability was established using Cronbach's alpha, yielding a score of 0.78. The study area encompassed Lenjan Township, which covered 1,171 m2 and was situated in the southwest of Isfahan Province. Research Findings Out of the 250 respondents, 52% were men and 48% were women. The participants' ages ranged from a minimum of 18 to a maximum of 76 years, with the largest age group (29.2%) falling within the 39-48 year range. Regarding marital status, 60.8% reported being married. In terms of education, 10% of respondents were illiterate, 24.8% had completed elementary to diploma level, 27.2% held a diploma, 34% had a bachelor’s or postgraduate degree, and 4% had postgraduate qualifications beyond that. Employment status revealed that 8% of participants were unemployed, 33% were privately employed, 22% worked as government or corporate employees, 13% were students, 22% were homemakers, and 2% were identified as soldiers. Regarding household income, 21.6% reported earning below 5 million Tomans, 27.2% earned between 5 and 8 million, 22.4% earned between 9 and 12 million, 18% earned between 13 and 16 million, and 10.8% earned over 16 million Tomans. The largest household size reported was for families of 3-4 members. To evaluate the level of political participation among villagers, a one-sample t-test was conducted. In response to general questions about "political participation", the voting option had an average score of 4.13. Participation in local elections averaged 3.74, efforts to support a specific candidate averaged 3.66, affiliation with a political group averaged 3.52, and engaging in political discussions averaged 3.14. The overall average for these categories was above 3, while participation in political assemblies had the lowest average at 2.87. An analysis of the correlation between electoral participation and personal characteristics indicated no significant relationships. Specifically, the correlations were as follows: gender (0.07), age (-0.04), marital status (-0.01), and education level (0.02); none of these demonstrated a significant connection. To identify the most significant factors affecting political participation among villagers, exploratory factor analysis was employed. The results from the factor analysis conducted using SPSS software indicated that "political awareness" was the primary factor, accounting for 14.19% of the total variance. The second factor, "media", accounted for 7.47% of the variance followed by the third factor, "social factors", which accounted for 6.10%. The fourth factor, "government performance", accounted for 5.80%. Discussion of Results & Conclusion Participation is a key indicator of sustainable rural development, with political participation serving as a crucial criterion for the political advancement of societies. In rural areas with substantial populations, fostering this participation is essential for achieving national significance. In Iran, elections are held for nearly all branches of government with a strong emphasis on increasing public participation. The current research examined and analyzed the factors influencing political participation within the rural communities of Lenjan. The findings revealed that, among the 250 respondents, 52% were male and 48% were female. The largest age group comprising 29.2% of participants fell within the 39-48 year range. Additionally, 60.8% of respondents reported being married. In terms of educational attainment, those with bachelor’s and postgraduate degrees constituted 34% of the sample, while 27.2% held a diploma. Regarding employment status, 8% were unemployed, while 55% were employed in private, government, or corporate sectors. The remaining respondents were identified as students, homemakers, or soldiers. The highest monthly household income bracket was reported by 27.2% of participants, who earned between 5 and 8 million Tomans. The results indicated that the overall level of political participation was above average with a mean score of 3.51. Among the various components of political participation, the "voting" aspect received the highest average score of 4.13. An examination of the correlation between electoral participation (voting) and individual characteristics—such as gender, age, marital status, and education—showed no significant relationships among these variables. The factor analysis results identified political awareness, media influence, social factors, and government performance as the most significant determinants of political participation in that order. In total, these 13 components accounted for 65.91% of the total variance. مشارکت از شاخص‌های مهم توسعۀ پایدار روستایی و مشارکت سیاسی به‌عنوان معیاری در توسعة سیاسی جوامع است. نواحی روستایی با درصد چشمگیری از جمعیت می‌تواند زمینه‌ساز تحقق این مهم در‌سطح ملی باشد؛ بنابراین در پژوهش حاضر عوامل مؤثر بر مشارکت سیاسی روستاییان شهرستان لنجان ارزیابی و تحلیل شده است. پژوهش از نوع کاربردی و روش آن توصیفی-تحلیلی و مبتنی بر پیمایش است. برای جمع‌آوری اطلاعات از دو شیوة کتابخانه‌ای (فیش‌برداری) و میدانی (تکمیل پرسشنامة محقق‌ساخته) استفاده شده است. بر این اساس، پرسشنامه با تعداد 250 نفر از روستاییان با بیش از 18 سال در نواحی روستایی شهرستان که شرایط شرکت در انتخابات را داشتند، به روش تصادفی ساده و شیوة مصاحبه‌ای تکمیل شد. روایی صوری پرسشنامه از‌دیدگاه متخصصان و پایایی آن به روش آلفای کرونباخ 78/0 محاسبه شد. برای تجزیه‌و‌تحلیل داده‌های گردآوری‌شده از آزمون‌های مناسب آمار توصیفی (میانگین، درصد، نمودار) و استنباطی (تی تک نمونه‌ای)، مدل تحلیل عاملی و نرم‌افزارهای SPSS ، Excel و GIS استفاده شده است. نتایج نشان داد که وضعیت مشارکت به‌طور کلی با میانگین 51/3 بیشتر از حد متوسط است. در بین مؤلفه‌های مختلف مشارکت سیاسی نیز مؤلفة «رأی‌دادن» با میانگین 13/4 در بیشترین سطح قرار دارد. نتایج حاصل از کاربرد مدل تحلیل عاملی نشان داد که به‌ترتیب عوامل آگاهی سیاسی، رسانه، عامل اجتماعی و عملکرد دولتمردان مهم‌ترین عوامل است. در‌مجموع، مؤلفه‌های سیزده‌گانه 91/65% از واریانس کل را برآورد می‌کند. همچنین، نتایجِ همبستگی بین شرکت در انتخابات (رأی‌دادن) با ویژگی فردی (جنسیت، سن، تأهل و تحصیلات) نشان از عدم رابطة معنادار بین متغیرها را دارد.

https://sppl.ui.ac.ir/article_28953_200cf25698e5702a71e410020db5a454.pdf

دانشگاه اصفهان برنامه ریزی فضایی 2228-7485 14 4 2024 12 21 Spatial Analysis of the Relationship between Ecological Factors and Housing Prices in Tehran تحلیل فضایی رابطۀ عوامل اکولوژیکی و قیمت مسکن در شهر تهران 103 124 28973 10.22108/sppl.2024.142377.1802 FA عاطفه کلیائی گروه جغرافیا و برنامه‌ریزی شهری، دانشکدۀ علوم جغرافیایی، تهران، ایران. طاهر پریزادی گروه جغرافیا و برنامه‌ریزی شهری، دانشکدۀ علوم جغرافیایی، تهران، ایران. حبیب اله فصیحی گروه جغرافیا و برنامه‌ریزی شهری، دانشکدۀ علوم جغرافیایی، تهران، ایران Journal Article 2024 08 06 Abstract Humans seek locations that offer a high quality of life, which is significantly influenced by environmental factors. Consequently, these factors play a crucial role in determining real estate values. This research aimed to explore the extent to which spatial variations in residential property prices in Tehran were affected by ecological factors. Data were collected from various sources, including real estate websites, meteorological synoptic stations, air quality monitoring stations, a GIS file of Tehran's land use, and the Information and Communication Technology Organization of Tehran Municipality. The data were integrated into a Geographic Information System (GIS), focusing on 400 points representing the geometric centers of neighborhoods in Tehran. These points served as the basis for analytical calculations with information gathered for all relevant variables. Using ArcGIS software and Spatial Analyst Tools, we generated the necessary data. The findings indicated a decreasing desirability of ecological factors from the north to the south of the city corresponding to a decline in housing prices. The correlation coefficient of +0.71 demonstrated a strong relationship between housing prices and desirability of ecological factors. Notably, there was approximately a threefold difference in average housing prices between District 1 (the northernmost district) and District 20 (the southernmost). In conclusion, despite the influence of political and economic factors and the profound changes brought about by modernity, the socio-economic gradient from north to south in Tehran remained aligned with the gradient of ecological desirability, suggesting a shift from natural environmental qualities to the role of capital in shaping real estate values. Keywords: Housing, Ecological Factors, Spatial Correlation, Tehran. Introduction In many cities, houses that are nearly identical can vary significantly in price based on their neighborhood or even specific locations within the same neighborhood. People seek out areas that offer a high quality of life, which is largely influenced by environmental factors. Consequently, these factors play a crucial role in determining real estate values. The spatial variations in housing prices within a geographical area profoundly affect the distribution of socio-economic classes. Wealthier individuals typically have the freedom to choose where they live, often opting for the most desirable neighborhoods that align with favorable ecological conditions. In contrast, lower-income groups often lack this choice and are frequently confined to less desirable areas, sometimes as a result of systemic pressures that limit their options. Access to housing is a fundamental human need and understanding the spatial disparities in housing prices—along with the ecological factors that influence them—can help inform urban management strategies aimed at achieving greater equity in housing distribution. This research sought to explore the extent to which the variations in residential property prices in Tehran were influenced by ecological factors. Materials & Methods This study examined 8 key components that represented ecological factors: climatic elements (precipitation and temperature), green coverage, number of clean air days, river valleys, fault lines, elevation, and slope. The climatic data were collected from 8 meteorological stations. Green coverage was calculated using the land use GIS file for Tehran. The number of clean air days was obtained from data provided by 35 air quality control stations. Information regarding the locations of river valleys, fault lines, and elevation was sourced from the Information and Communication Technology Organization of Tehran Municipality. To create maps for slope and elevation, data from the Digital Elevation Model (DEM) layer were utilized. The dependent variable in this analysis was the price per square meter of residential properties (apartments) sold in March 2024 as reported by the Real Estate Website of the Ministry of Roads and Urban Development. The analysis was based on 400 points representing the geometric centers of neighborhoods in Tehran, from which housing prices were extracted. To analyze the correlation among variables, each vector layer was converted into a raster layer, allowing for the generation of point layers corresponding to the 400 housing price locations. ArcGIS software was employed, utilizing Spatial Analyst, Spatial Join, and Zonal Statistics functions to create the necessary datasets. The study encompassed the urban area of Tehran, which consisted of 22 municipal districts, covering approximately 615 km² and housing a population of 8.7 million people. Research Findings The findings revealed a clear trend: as one moved from the north to the south of Tehran, the desirability of ecological factors diminished, which corresponded with a decline in housing prices. District 1 located in the northern part of the city offered the most favorable ecological conditions, while District 20 in the south presented the least desirable conditions. Consequently, housing prices increased from south to north with the highest prices found in Districts 1, 2, and 3, while Districts 18, 20, and 21 exhibited the lowest prices. Notably, there was approximately a threefold difference in the average housing price between District 1 and District 20. The correlation coefficient of +0.71 indicated a strong relationship between housing prices and desirability of ecological factors. In areas of Tehran where ecological indicators were more favorable, housing prices tended to be higher. Among the independent variables, the average annual temperature, distance from river valleys, distance from fault lines, and green coverage showed the highest correlation coefficients; however, these relationships were negative, indicating an inverse correlation. This suggested that in locations with higher housing prices, the values of these ecological indicators tended to decrease. Conversely, the indicators of elevation, average annual precipitation, slope, and number of days with clean air exhibited a positive correlation with housing prices. Generally, properties with higher exchange values were situated at greater elevations, received more annual rainfall, and had more favorable slope characteristics and a higher number of clean air days per year. Discussion of Results & Conclusion Tehran has long been characterized by a correspondence between its geographical north and its socio-economic north. This segregation of socio-economic classes—where higher-income groups reside in the northern areas and lower-income groups are pushed to the south—has historical roots linked to the city's expansion during governmental development. Despite the significant impacts of political economy and the sweeping changes brought about by modernism, the socio-economic gradient from north to south remains aligned with the gradient of ecological desirability. This alignment suggests that the socio-economic landscape continues to be influenced by both capital and the inherent ecological characteristics of the environment, reflecting a complex interplay between economic forces and natural desirability. انسان‌ها به‌دنبال مکان‌هایی هستند که کیفیت زندگی خوبی دارند. کیفیت زندگی تا حدود زیادی تابع عوامل محیطی است. از این نظر، عوامل محیطی تأثیر چشمگیری بر ارزش دارایی دارد. هدف از پژوهش حاضر پی‌بردن به این مفهوم است که در شهر تهران تا چه میزان تفاوت‌های فضایی قیمت املاک مسکونی تابع عوامل اکولوژیکی است؟ در این مطالعه داده‌ها از سامانۀ املاک، ایستگاه‌های سینوپتیک هواشناسی، ایستگاه کنترل کیفیت هوا، شیپ فایل کاربری اراضی و سازمان فناوری اطلاعات و ارتباطات شهرداری تهران به دست آمده است. با ورود داده‌ها به سیستم اطلاعات جغرافیایی برای هر‌کدام یک لایه اطلاعاتی ساخته شده است. ۴۰۰ نقطه با مرکزیت محله‌های شهر تهران ملاک محاسبات تحلیلی بوده که اطلاعات مربوط به آنها برای تمامی متغیرها حاصل شده است. برای تولید و تحلیل داده‌های لازم از نزم‌افزار ArcGIS و توابعSpatial Analyst Tools استفاده شده است. یافته‌ها دلالت بر این دارد که مطلوبیت عوامل اکولوژیکی از شمال به جنوب شهر کاسته می‌شود و به‌دنبال آن قیمت مسکن نیز کاهش می‌یابد. رقم همبستگی 71/0+ نشان می‌دهد که میان قیمت ملک و مطلوبیت عوامل اکولوژیکی در‌سطح بالایی رابطه وجود دارد. در ارزش مبادلاتی مسکن منطقۀ 1 به‌عنوان شمالی‌ترین منطقه و منطقۀ 20 به‌عنوان جنوبی‌ترین منطقه است که میانگین قیمت در آنها حدود 3 برابر متفاوت است؛ بنابراین با‌وجود نقش‌آفرینی اقتصاد سیاسی و دگرگونی‌های عمیقی که با ورود و تجلی مدرنیسم در کالبد شهر ایجاد شده است، هنوز هم شیب اقتصادی-اجتماعی شمال به جنوب شهر با شیب مطلوبیت اکولوژکی که با جایگزینی اقتصاد سیاسی و بازیگری سرمایه در جای مطلوبیت طبیعی محیط بازتولید می‌شود، انطباق دارد.

https://sppl.ui.ac.ir/article_28973_82d6b0229fca22cd62ca35847ff6b2ad.pdf

دانشگاه اصفهان برنامه ریزی فضایی 2228-7485 14 4 2024 12 21 Analysis of the Causes of Urban Sprawl in Iran تحلیل علل پراکنده‌رویی شهری در ایران 125 148 28997 10.22108/sppl.2024.140937.1778 FA کرامت اله زیاری استاد گروه جغرافیای انسانی و برنامه‌ریزی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران سعید زنگنه شهرکی دانشیار گروه جغرافیای انسانی و برنامه‌ریزی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران نگین رجب زاده گروه جغرافیای انسانی و برنامه ریزی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران محسن عباس نژاد جلوگیر دانشجوی دکتری جغرافیا و برنامه‌ریزی شهری، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران 0009-0009-8808-5582 Journal Article 2024 04 08 Abstract In the era of rapid urbanization, urban sprawl is undeniably one of the most significant challenges facing cities, particularly in developing countries. Iranian cities are no exception to this trend. Effective planning to manage urban sprawl and achieve sustainable urban land management requires a thorough understanding of the forces and causes that contribute to scattered urban development. This research aimed to investigate both the direct and indirect causes of urban sprawl in Iranian cities. The study employed a qualitative and descriptive-analytical approach, utilizing document-based data collection methods. Approximately 80 domestic articles on urban sprawl were gathered, analyzed, and coded using MAXQDA2020 software through a systematic process. The reasons for urban sprawl identified in the literature were categorized into 16 general themes. The findings indicated that the key factors contributing to urban sprawl in Iranian cities included weaknesses, ambiguities, and inefficiencies in urban laws and regulations; inadequate planning, monitoring, and control over urban growth; development of transportation infrastructure; macro-level urban policies; migration to urban areas; land speculation; planned settlements; natural population growth; impacts of urban planning approvals; and establishment of light and heavy industries on city peripheries. These factors were interconnected and arose from various contextual influences. Keywords: Urban Sprawl, Iranian Cities, Content Analysis, MAXQDA Software. Introduction Urban sprawl has been a topic of interest for social science researchers since the mid-20th century (Rubiera-Morollón et al., 2020). Experts suggest that urban sprawl in the United States and Western Europe can be understood through 3 historical stages: 1) urban sprawl under the Keynesian-Fordist model of urbanization (1945-1975), 2) the period of urban reconstruction and intensive city redevelopment (1975-1985), and 3) the emergence of a neoliberal and globalized urban model (from 1985 onward) (Bueno-Suárez et al., 2020, pp. 5-9). Since the 1960s, the concept of urban dispersion has gained prominence in urban studies historically associated with American cities (Meshkini et al., 2013, p. 118). However, this spatial evolution is not confined to the United States; it has now affected many cities worldwide. In recent decades, Iranian cities have experienced significant urban sprawl exacerbated by specific macroeconomic, social, political, and environmental factors, which have, in turn, impacted the social fabric and health of residents (Hosseini & Hosseini, 2014, p. 33). Understanding urban sprawl requires examining its causes, contexts, and consequences. It is challenging to apply a one-size-fits-all framework to cities globally. To create effective strategies for mitigating this issue, it is essential to investigate the similarities and differences in urban sprawl patterns across various cities (Pourahmad et al., 2019, p. 67). The first step in addressing urban sprawl is to control and prevent its escalation. Effective management cannot occur without a clear understanding of the conditions, contexts, processes, and causes that contribute to sprawl. Identifying and managing the physical growth of cities necessitates a comprehensive approach at both urban and regional levels (Ziyari et al., 2016, p. 497). Therefore, the aim of this research was to identify the factors and indicators contributing to urban sprawl in Iranian cities. Materials & Methods This research employed a qualitative approach. The data collection method utilized was document-based analysis. Data were gathered through content analysis and processed using MAXQDA 2020 software. To achieve the research objectives, approximately 80 relevant articles on urban sprawl were collected with no time limit imposed on the selection. In the first step, about 40 articles specifically addressing the causes of urban sprawl were identified and extracted using MAXQDA. In the second step, these selected articles were coded. Each article was read in its entirety and instances cited as reasons for sprawl were designated as codes and organized into specific subject categories. In the third step, all the codes generated from the previous stage were compiled and transferred to Word software for further analysis. Finally, in the fourth step, the selected codes underwent a screening process to eliminate duplicates and condense the information, resulting in a final summary table. Research Findings The research identified 16 categories of causes contributing to urban sprawl in Iranian cities, highlighting the complexity and interrelationship of these factors. The primary findings were summarized as follows: Urban Management and Planning: A significant cause of sprawl was the weakness and inefficiency of urban laws and regulations, particularly in construction and growth control. This category received the highest frequency of mentions (12 occurrences). Infrastructure and Urban Elements: The development of transportation networks and urban infrastructure was frequently cited (10 occurrences), emphasizing the role of communication routes in facilitating sprawl. Economic Factors: The rise in urban land prices and land speculation was identified as a key economic driver of sprawl (14 occurrences), affecting land availability and accessibility. Migration: The ongoing trend of migration to urban areas was noted as a major contributing factor (19 occurrences) driven by job opportunities and urban development. Socio-Cultural Changes: Researchers highlighted shifts in lifestyle among Iranian families, which had implications for urban expansion. Natural Factors: Environmental aspects, such as geography and climate, were recognized as influences on urban growth patterns. Political Factors: The expansion of government structures and policies impacting land use were also noted with specific references to industrial and military developments on urban peripheries. Inner-City Problems: Issues, such as land hoarding and deterioration of central urban areas, were mentioned, indicating challenges within existing urban fabrics. Marginalization and Informal Settlements: The growth of informal settlements around cities (5 occurrences) was emphasized, reflecting socio-economic disparities. Peri-Urban Integration: Factors leading to the integration of surrounding villages into cities were discussed, particularly the lack of physical barriers and proximity to transport routes. Demographic Factors: Natural population growth (15 occurrences) was another critical element affecting urban sprawl. The research revealed that the city of Tehran was the most studied city regarding urban sprawl followed by Sari, Ahvaz, and Mashhad. Each city displayed unique characteristics and factors contributing to its sprawl, demonstrating that while certain causes were widespread, local contexts significantly shaped urban development patterns. In conclusion, the findings suggested that urban sprawl in Iranian cities resulted from a confluence of factors, many of which were interrelated and influenced by government policies. Effective management and planning must address these multifaceted causes to create sustainable urban environments. Discussion of Results & Conclusion The causes of urban sprawl in Iran were categorized into 15 distinct dimensions: city form, urban management and planning, infrastructure and urban elements/transportation, land and housing management, planning, and policy, migration and land preparation, socio-cultural factors, natural factors, economic factors, urban plans, political factors, inner-city problems, marginalization and informal settlement issues, urban peripheral problems, demographic factors, and other factors. Within the dimension of city form, spatial-functional discontinuity was noted as a contributing factor (3 occurrences in the sources). In terms of urban management and planning, the weaknesses, deficiencies, ambiguities, and inefficiencies of urban laws and regulations—particularly concerning construction and urban growth control—were highlighted (12 occurrences). Regarding infrastructure and urban elements, significant emphasis was placed on the development of transportation technology and communication networks, as well as the enhancement of urban infrastructure and information technology (10 occurrences). Current government urban policies, particularly those related to land and housing—such as the development of new cities, various urban plans, land transfer, preparation, zoning, and policies addressing informal settlements—were identified as key factors (16 occurrences). The trend of migration to urban areas emerging as a prevalent cause of sprawl was noted 19 times in the sources. Additionally, researchers emphasized changes in the lifestyle of Iranian families as a socio-cultural factor influencing urban expansion. Natural factors, including climate, landform, water resources, soil conditions, and river systems, also played a critical role in the spread of cities in Iran. Furthermore, the rising prices of urban land, speculation, and fluctuations in the real estate market were identified as significant economic drivers of urban sprawl (14 occurrences). In conclusion, the multifaceted nature of urban sprawl in Iran was influenced by a complex interplay of factors across various dimensions. Understanding these causes was essential for developing effective strategies to manage and mitigate urban sprawl in Iranian cities. Regarding urban planning, the existing policies and development plans, including comprehensive plans, specific projects, land preparation, and regional and local strategies, had been emphasized by Iranian researchers as significant indicators of urban sprawl (1 occurrence in the sources). A notable political factor contributing to urban expansion was the growth of government structures and organizations, which was mentioned 7 times in the sources. Additionally, the presence of large-scale developments, such as industrial and military centers, was cited as a contributing factor (3 occurrences). Other inner-city issues identified included land hoarding within urban areas (3 occurrences) and deterioration of central urban fabrics (3 occurrences). In terms of marginalization and informal settlements, proliferation of informal communities surrounding cities had been a focal point in research on urban sprawl (5 occurrences). Furthermore, peri-urban challenges included the integration of peripheral villages into urban areas, which were driven by factors, such as absence of physical barriers, commercial interests, proximity to transport routes, and political-administrative influences (9 occurrences). Population dynamics also played a crucial role, with natural population growth being cited as a significant factor contributing to urban sprawl (15 occurrences). Additional factors included expansion of universities and higher education institutions within cities, as well as strengthening of functional relationships between the central city and its suburbs (3 occurrences). Research on urban sprawl had focused on 27 cities across Iran. Notably, Tehran was the subject of more studies than any other cities, with 7 investigations addressing the causes of urban sprawl. Other cities, such as Sari, Ahvaz, and Mashhad, had been analyzed in 3 studies each, while Kerman, Shiraz, Sanandaj, Bojnoord, and Yasouj were the focus of 2 studies. Furthermore, 3 studies had explored the causes of urban sprawl in Babolsar, various urban areas in Iran, and the coastal regions of the Caspian Sea. The following section will examine the causes of urban sprawl in selected cities in greater detail. The reasons for sprawl in these cities vary widely, with some factors being more common and others more unique. For instance, natural population growth was identified as a contributing factor in the cities of Mashhad, Khorramdarreh, and Lamerd. Infrastructure and transportation had also played significant roles in the sprawl of Mashhad, Rasht, Lamerd, and Bastak, where urban expansion was largely focused along suburban communication routes. It is important to note that even within a shared dimension, the underlying causes could differ. For example, in Mashhad, migration had occurred from historical neighborhoods to newer parts of the city. In Khorramdarreh, migration had been driven by industrial development and increased job opportunities over the past few decades, while in Lamerd, a significant portion of the regional population had moved to the main city, contributing to urban sprawl. The establishment of industries within city limits in areas, such as Khorramdarreh and Lamerd had also significantly fueled urban sprawl. This industrial growth had attracted labor and created demand for both planned and unplanned housing for the workforce. Additionally, natural factors, such as geographic location, had influenced the extent of urban sprawl in certain cities. For example, the flat terrain of Lamerd and Khorramdarreh had facilitated more intensive urban expansion. An examination of the available domestic scientific literature on urban sprawl revealed that the drivers of this phenomenon in Iranian cities were numerous and often interrelated. Among the dimensions of sprawl, urban management and planning, as well as land and housing policy, were identified as significant contributors with 22 identified factors. Similarly, the dimensions of infrastructure and urban elements, along with economic factors, accounted for 23 contributing elements, marking them as the most critical aspects of urban planning in Iran. The research findings indicated that several key factors drove urban sprawl in Iranian cities, including the general trend of migration to urban areas, current government policies regarding land and housing, rising urban land prices and speculation, and weaknesses, ambiguities, and inefficiencies in urban laws and regulations—particularly those governing construction and growth control. Additionally, the establishment and expansion of specialized facilities, industries, and factories both within and around urban areas played a significant role. A careful analysis of these findings led to the conclusion that the primary causes of urban sprawl in Iran—especially since the Islamic Revolution—were directly and indirectly linked to the actions and policies of successive governments. Based on the research findings, any planning aimed at controlling and managing urban sprawl must be framed within the context of government action. In other words, an effective and scientifically sound approach to managing urban sprawl in Iranian cities requires careful planning within a hierarchical structure that spans from the national to the local level. Each factor contributing to sprawl should be addressed with specific plans that include a comprehensive set of measures supported by legal frameworks and operational authority from various levels of government. Furthermore, by comparing the causes of urban sprawl in Iranian cities with those documented in the global literature on urbanization, we can achieve valuable insights. The analysis indicated that, in terms of quantity, nature, and content, the dimensions of sprawl in Iranian cities closely overlapped with those in cities around the world. While there were similarities in some aspects of urban sprawl, differences also emerged in other dimensions, reflecting the unique contexts and challenges faced by Iranian cities. پراکنده‌رویی شهری را بی‌شک باید یکی از مهم‌ترین چالش‌های پیش روی شهرها به‌ویژه در کشور‌های درحال توسعه دانست. شهرهای ایران نیز از این قاعده مستثنی نیست. هرگونه برنامه‌ریزی برای کنترل پدیدۀ پراکنده‌رویی شهری و سپس دستیابی به الگوی مدیریت پایدار اراضی شهری مستلزم شناخت نیروها و علل به وجود آورنده و هدایت‌کنندۀ پراکنده‌رویی شهری است. در این راستا، هدف از پژوهش حاضر شناخت علل مستقیم و غیر‌مستقیم پراکنده‌رویی در شهرهای ایران است. پژوهش حاضر از‌نوع کیفی و به‌صورت توصیفی-تحلیلی و روش جمع‌آوری داده‌های آن به‌صورت اسنادی-کتابخانه‌ای بوده است. در راستای دستیابی به هدف پژوهش حدود 80 مقالۀ داخلی در موضوع پراکنده‌رویی شهری (در دو دهۀ گذشته) جمع‌آوری و در چند ‌مرحلۀ منظم در نرم‌افزار MAXQDA2020 تحلیل و کدگذاری شد. دلایل پراکنده‌رویی شهری استخراج‌شده از منابع بررسی‌شده در 16 دستۀ کلی تقسیم‌بندی شد. بر‌اساس نتایج پژوهش عواملی همچون ضعف، کمبود، ابهام و ناکارآمدی قوانین و مقررات شهری، نبود برنامه‌ریزی، نظارت و کنترل رشد و توسعۀ شهر، توسعۀ مسیر‌های ارتباطی و زیرساخت‌های حمل‌و‌نقل، سیاست‌های شهری کلان، مهاجرت به شهر، سوداگری زمین، شهرک‌سازی‌های برنامه‌ریزی‌‌شده، رشد طبیعی جمعیت، اثر‌های تهیه و تصویب طرح‌های شهری و توسعۀ صنایع سبک‌و‌سنگین در حاشیۀ شهر‌ها را می‌توان از مهم‌ترین علل پراکنده‌رویی در شهر‌های ایران دانست که هر‌یک نتیجۀ زمینه‌ها و علل مختلف دیگری است

https://sppl.ui.ac.ir/article_28997_3d88cad886d72b7f68430e4ed4bced03.pdf