سناریو بندی یکپارچگی شبکه اکولوژیک منظر شهری بر اساس مدل بهبودیافته جاذبه (در پهنه شمال شرق تهران)
محورهای موضوعی :
مدیریت محیط زیست
حسین موسوی فاطمی
1
,
فرح حبیب
2
,
پویان شهابیان
3
1 - گروه شهرسازی، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.
2 - گروه شهرسازی، واحد علوم و تحقیقات، دانشگاه ازاد اسلامی، تهران، ایران. * (مسوول مکاتبات)
3 - گروه شهرسازی، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.
تاریخ دریافت : 1401/12/25
تاریخ پذیرش : 1402/02/05
تاریخ انتشار : 1402/01/01
کلید واژه:
سناریو بندی شبکه اکولوژیک,
سیستم اطلاعات جغرافیایی (GIS),
منظر اکولوژیک شهری,
تئوری گراف,
مدل جاذبه,
چکیده مقاله :
زمینه و هدف: توسعه سریع کلان‌شهرها سبب ناپایداری محیط زیست شهری انسان ها و متعاقباً موجب تکه‌تکه شدن اکولوژی منظر شهری شده است در واقع شهرهای امروزی نیازمند مداخلاتی نو هستند که یکی از مهم‌ترین آن ها، برنامه ریزی و طراحی برای ایجاد پیوستگی اکولوژی منظر شهری است. با توسعه شبکه های سبز شهری در کلان‌شهرهای امروزی می توان از تنوع زیستی حفاظت کرد و درنهایت به وسیله پیوستگی اکولوژیکی عاملی برای جلوگیری از انزوا جمعیت ها و گونه ها شد. هدف این مقاله اتصال شبکه‌های اکولوژیک منظر شهری و درنهایت ارائه خدمات اکوسیستمی یکپارچه در شهرها و تولید کریدورهای بالقوه پیشنهادی و سناریو بندی آن ها است.روش بررسی: در این پژوهش از مدل بهبودیافته جاذبه و توسعه سناریو و تجزیه‌وتحلیل شبکه در محیط نرم افزار GIS استفاده‌شده است.یافته ها: نتایج نشان می‌دهد که می‌توان با استفاده از لایه های هزینه، مقاومت و لکه های اصلی به مجموعه ای از کریدورهای پیشنهادی و اولویت بندی آن ها رسید؛ همچنین می‌توان سناریوهای مختلف را از طریق آنالیز شبکه کریدورها در پهنه موردمطالعه گسترش داد.بحث و نتیجه‌گیری: بر مبنای لایه مقاومت، لکه اصلی و لایه هزینه به تولید اولویت‌بندی کاربردی کریدورهای پیشنهادی پرداخته شد تا به‌واسطه آن بتوان به توسعه سه سناریو بالقوه در پهنه شمال شرق تهران دست‌یافت. درنهایت از طریق تحلیل سه سناریو پیشنهادی، راهبردهای تصمیم گیری و تبیینِ یکپارچگیِ شبکه اکولوژیِ منظر شهری، مطلوب‌ترین سناریو معرفی شد. خروجی این تحقیق می‌تواند به‌عنوان نقشه ای پایه ای برای توسعه و بازنده سازی ساختارهای منظر اکولوژیک شهری مورداستفاده قرار گیرد.
چکیده انگلیسی:
Background and Objective: The rapid development of cities has caused the unsustainability of the human urban environment and consequently fragmented the ecology of the urban landscape. Today, there is a need for a new conceptualization with which to approach ecological diversity, such as environmental planning and design for integrating the urban landscape ecology. The development of urban green networks is one of the essential factors to protect biodiversity and effectively prevent the isolation of populations and species. The purpose of this article is to connect ecological networks in the urban landscape and finally increase connectivity and provide ecosystem services in cities and presenting proposed potential corridors and their scenarios.Material and Methodology: We produced the proposed scenarios by using the improved Gravity model and network analysis in GIS software.Findings: We achieved the prioritize corridors in the northeast area of Tehran by using the cost layer, the impedance layer, and the core patches. In the final stage, three scenarios were developed in the studied area using corridor network analysis.Discussion and Conclusion: Based on the impedance layer, core patches, and cost layer, the functional prioritization of the proposed corridors was discussed to develop and analyze the proposed corridors. This map leads to decision-making strategies and achieving the integration of the ecological networks in the urban landscape. The output of this paper can be used as a basic map for the development and revitalization of urban ecological landscape structures.
منابع و مأخذ:
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Correa Ayram CA, Mendoza ME, Etter A, Salicrup DRP. Habitat connectivity in biodiversity conservation: A review of recent studies and applications. Progress in Physical Geography. 2016;40(1):7-37.
Gobattoni F, Pelorosso R, Lauro G, Leone A, Monaco R. A procedure for mathematical analysis of landscape evolution and equilibrium scenarios assessment. Landscape and urban planning. 2011;103(3-4):289-302.
Zhang Z, Meerow S, Newell JP, Lindquist M. Enhancing landscape connectivity through multifunctional green infrastructure corridor modeling and design. Urban forestry & urban greening. 2019;38:305-17.
Wanghe K, Guo X, Wang M, Zhuang H, Ahmad S, Khan TU, et al. Gravity model toolbox: An automated and open-source ArcGIS tool to build and prioritize ecological corridors in urban landscapes. Global Ecology and Conservation. 2020;22:e01012.
Etherington TR, Penelope Holland E. Least-cost path length versus accumulated-cost as connectivity measures. Landscape Ecology. 2013;28(7):1223-9.
Zhang Z. Enhancing landscape connectivity in detroit through multifunctional green corridor modeling and design 2017.
Zandbergen PA. Python scripting for ArcGIS: Esri press Redlands, CA; 2013.
Sklar FH, Costanza R. The development of dynamic spatial models for landscape ecology: a review and prognosis. Ecological studies. 1991; 82: 239-88.
Wang F, Zhong D, Lu M, editors. Research on urban greenway planning in the old city of Jinan City based on GIS interpretation and Gravity model data. Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022); 2023: SPIE.
Zhao Y, Zhang G, Zhao H. Spatial network structures of urban agglomeration based on the improved Gravity Model: A case study in China’s two urban agglomerations. Complexity. 2021;2021:1-17.
Linehan J, Gross M, Finn J. Greenway planning: developing a landscape ecological network approach. Landscape and urban planning. 1995;33(1-3):179-93.
Kong F, Yin H, Nakagoshi N, Zong Y. Urban green space network development for biodiversity conservation: Identification based on graph theory and Gravity modeling. Landscape and urban planning. 2010;95(1-2):16-27.
Davies C, McGloin C, MacFarlane R, Roe M. Green infrastructure planning guide project. Final Report. 2006.
Hellmund P. Quabbin to Wachusett wildlife corridor study. Harvard Graduate School of Design, Cambridge, MA. 1989.
Management and planning organization of Tehran Statistical Yearbook of Tehran Province 2019. (In Persian)
Mousavi Fatemi S H, Habib F, Shahabian P. Gravity model, an automatic method for prioritizing urban landscape ecology corridors (Case study: Northeast area of Tehran). Haft Hesar Journal of Enviromental Studies. In-print. (In Persian)
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Wu J. Urban sustainability: an inevitable goal of landscape research. Springer; 2010. p. 1-4.
Steiner FR. The living landscape: an ecological approach to landscape planning: Island Press; 1991.
Bunn AG, Urban DL, Keitt TH. Landscape connectivity: a conservation application of graph theory. Journal of environmental management. 2000;59(4):265-78.
Harary F. Graph theory1969.
Cantwell MD, Forman RT. Landscape graphs: ecological modeling with graph theory to detect configurations common to diverse landscapes. Landscape Ecology. 1993;8(4):239-55.
Keitt TH, Urban DL, Milne BT. Detecting critical scales in fragmented landscapes. Conservation ecology. 1997;1.(1)
Moilanen A. On the limitations of graph-theoretic connectivity in spatial ecology and conservation. Journal of Applied Ecology. 2011:1543-7.
Correa Ayram CA, Mendoza ME, Etter A, Salicrup DRP. Habitat connectivity in biodiversity conservation: A review of recent studies and applications. Progress in Physical Geography. 2016;40(1):7-37.
Gobattoni F, Pelorosso R, Lauro G, Leone A, Monaco R. A procedure for mathematical analysis of landscape evolution and equilibrium scenarios assessment. Landscape and urban planning. 2011;103(3-4):289-302.
Zhang Z, Meerow S, Newell JP, Lindquist M. Enhancing landscape connectivity through multifunctional green infrastructure corridor modeling and design. Urban forestry & urban greening. 2019;38:305-17.
Wanghe K, Guo X, Wang M, Zhuang H, Ahmad S, Khan TU, et al. Gravity model toolbox: An automated and open-source ArcGIS tool to build and prioritize ecological corridors in urban landscapes. Global Ecology and Conservation. 2020;22:e01012.
Etherington TR, Penelope Holland E. Least-cost path length versus accumulated-cost as connectivity measures. Landscape Ecology. 2013;28(7):1223-9.
Zhang Z. Enhancing landscape connectivity in detroit through multifunctional green corridor modeling and design 2017.
Zandbergen PA. Python scripting for ArcGIS: Esri press Redlands, CA; 2013.
Sklar FH, Costanza R. The development of dynamic spatial models for landscape ecology: a review and prognosis. Ecological studies. 1991; 82: 239-88.
Wang F, Zhong D, Lu M, editors. Research on urban greenway planning in the old city of Jinan City based on GIS interpretation and Gravity model data. Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022); 2023: SPIE.
Zhao Y, Zhang G, Zhao H. Spatial network structures of urban agglomeration based on the improved Gravity Model: A case study in China’s two urban agglomerations. Complexity. 2021;2021:1-17.
Linehan J, Gross M, Finn J. Greenway planning: developing a landscape ecological network approach. Landscape and urban planning. 1995;33(1-3):179-93.
Kong F, Yin H, Nakagoshi N, Zong Y. Urban green space network development for biodiversity conservation: Identification based on graph theory and Gravity modeling. Landscape and urban planning. 2010;95(1-2):16-27.
Davies C, McGloin C, MacFarlane R, Roe M. Green infrastructure planning guide project. Final Report. 2006.
Hellmund P. Quabbin to Wachusett wildlife corridor study. Harvard Graduate School of Design, Cambridge, MA. 1989.
Management and planning organization of Tehran Statistical Yearbook of Tehran Province 2019. (In Persian)
Mousavi Fatemi S H, Habib F, Shahabian P. Gravity model, an automatic method for prioritizing urban landscape ecology corridors (Case study: Northeast area of Tehran). Haft Hesar Journal of Enviromental Studies. In-print. (In Persian)
