SavedAdd your journal

Journals / Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi / 2026 / Cilt: 27 Sayı: 1

Examining Climate Change Resilient Urban Areas with Artificial Intelligence (AI)-Supported Landscape Design

Yapay Zekâ (YZ) Destekli Peyzaj Tasarımıyla İklim Değişikliğine Dirençli Kentsel Alanların İrdelenmesi

Başak Yurtseven0000-0001-6074-0906
Pages
294–323
Publication Date
2026-03-31
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Overall, the results confirm that AI-supported urban landscape approaches not only increase resilience to climate change but also support the development of more sustainable, healthy, and livable urban environment.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Climate change intensifies multidimensional environmental threats in urban areas, including flooding, drought, heatwaves, and biodiversity loss, making urban resilience a critical challenge.
📊
Key Findings & Data:The findings show that AI-supported plant selection models improve drought and heat tolerance while reducing irrigation demand; AI-based optimization of green infrastructure networks enhances stormwater management and significantly reduces urban flood risk; and sensor-based monitoring systems integrated with machine learning enable continuous assessment of ecosystem health and early detection of environmental stress.
💡
Conclusion & Impact:Overall, the results confirm that AI-supported urban landscape approaches not only increase resilience to climate change but also support the development of more sustainable, healthy, and livable urban environment.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yapay zeka · Peyzaj tasarımı · İklim değişikliği

Abstract

Climate change intensifies multidimensional environmental threats in urban areas, including flooding, drought, heatwaves, and biodiversity loss, making urban resilience a critical challenge. Developing climate-resilient cities therefore requires data-driven and integrative approaches in landscape design beyond conventional engineering solutions. In this context, artificial intelligence (AI), in combination with nature-based solutions (NBS), introduces new opportunities for the planning, implementation, and management of urban landscapes. The aim of this study is to investigate how AI-based decision support systems transform landscape design practices for climate change adaptation and ecological resilience. Using a descriptive content analysis method, selected national and international case studies focusing on plant selection, water management, green infrastructure optimization, and urban ecosystem monitoring were examined. The findings show that AI-supported plant selection models improve drought and heat tolerance while reducing irrigation demand; AI-based optimization of green infrastructure networks enhances stormwater management and significantly reduces urban flood risk; and sensor-based monitoring systems integrated with machine learning enable continuous assessment of ecosystem health and early detection of environmental stress. The study’s original contribution lies in demonstrating the integrated use of digital twins, machine learning algorithms, and environmental sensors at the landscape scale, providing a structured and transferable framework for climate-responsive design decisions. Overall, the results confirm that AI-supported urban landscape approaches not only increase resilience to climate change but also support the development of more sustainable, healthy, and livable urban environment.

Özet

İklim değişikliği, kentlerde sel, kuraklık, aşırı sıcaklar ve biyolojik çeşitlilik kaybı gibi çok boyutlu çevresel tehditleri artırarak kentsel dirençliliği kritik bir mesele hâline getirmektedir. Bu nedenle iklime dirençli kentlerin geliştirilmesi, yalnızca mühendislik çözümleriyle değil, peyzaj tasarımında veri temelli ve bütüncül yaklaşımlarla mümkün olmaktadır. Bu bağlamda, yapay zekâ (YZ) teknolojilerinin doğa-temelli çözümler (NBS) ile birlikte kullanımı, kentsel peyzajın planlanması, uygulanması ve yönetiminde yeni olanaklar sunmaktadır. Bu çalışmanın amacı, YZ tabanlı karar destek sistemlerinin peyzaj tasarım süreçlerine entegrasyonunun iklim değişikliğine uyum ve ekolojik dayanıklılık üzerindeki etkilerini ortaya koymaktır. Betimsel içerik analizi yöntemiyle, bitki seçimi, su yönetimi, yeşil altyapı ağlarının optimizasyonu ve kent ekosistemlerinin izlenmesine yönelik ulusal ve uluslararası örnekler incelenmiştir. Elde edilen temel bulgular, YZ destekli bitki seçimi yaklaşımlarının kuraklık ve sıcaklık stresine dayanıklı türlerin belirlenmesini kolaylaştırarak sulama ihtiyacını azalttığını; yeşil altyapı ağlarının YZ tabanlı optimizasyonunun yağmur suyu yönetimini iyileştirerek kentsel sel riskini düşürdüğünü; sensör tabanlı çevresel izleme sistemlerinin ve makine öğrenimi algoritmalarının, kent ekosistemlerinin durumunu sürekli izlemeye ve çevresel stresin erken tespitine olanak sağladığını göstermektedir. Çalışmanın özgün katkısı, dijital ikizler, makine öğrenimi algoritmaları ve sensör tabanlı çevresel izleme sistemlerinin peyzaj ölçeğinde bütüncül biçimde ele alınarak, iklime duyarlı tasarım kararları için sistematik ve uygulanabilir bir çerçeve sunulmasıdır. Sonuç olarak, yapay zekâ destekli kentsel peyzaj yaklaşımlarının yalnızca iklim değişikliğine karşı dirençli kentler oluşturmakla kalmadığı, aynı zamanda daha sürdürülebilir, sağlıklı ve yaşanabilir kentsel çevrelerin gelişimine önemli katkılar sunduğu ortaya konulmaktadır.

🔖

Cite This Article

Yurtseven, B. (2026). Examining Climate Change Resilient Urban Areas with Artificial Intelligence (AI)-Supported Landscape Design. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, Cilt: 27 Sayı: 1, 294–323. https://doi.org/10.17474/artvinofd.1844300

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (67)

  1. Alberti M (2016) Cities That Think like Planets: Complexity, Resilience, and Innovation in Hybrid Ecosystems. London: University of Washington Press.
  2. Alper S (2022) Initiative: Peynircioglu Stream Ecological Restoration Project. https://aiph.org/green-city-case-studies/izmir-turkiye/. Erişim Tarihi: 05.02.2026.
  3. AnkaGeo (2020) Akıllı Şehir Yönetim Platformu. https://ankageo.com/bilgi-kosesi/akilli-sehir/. Erişim Tarihi: 12.02.2026.
  4. Ankara Metropolitan Municipality (2023) Sustainable Energy and Climate Action Plan Final Report. Ankara: Ankara Metropolitan Municipality. Erişim Tarihi: 20.02.2026
  5. Architecture 2030 (2026) 2030 Challenge. https://www.architecture2030.org/. Erişim Tarihi: 31.03.2026. Balacumaresan H, Imteaz M, Aziz M (2024) Use of Artificial Intelligence Modelling for the Dynamic Simulation of Urban Catchment Runoff. Water Resour Manage, 38: 3657-3683. https://doi.org/10.1007/s11269-024-03833-9
  6. Batty M (2024) Inventing Future Cities. Cambridge: MIT Press.
  7. Benediktsson J, Palmason J, Sveinsson J (2005) Classification of Hyperspectral Data from Urban Areas Based on Extended Morphological Profiles. IEEE Transactions on Geoscience & Remote Sensing, 43(3): 480-491. https://doi.org/10.1109/TGRS.2004.842478
  8. Bui Q, Pijpers R, van Leeuwen E (2021) Smart green infrastructure management: Sensor-driven environmental monitoring in European cities. Urban Forestry and Urban Greening, 60: 127063.
  9. Columbia Climate School. (2024). Landscape Assessment of AI for Climate and Nature. Columbia University. https://www.climate.columbia.edu/sites/www.climate.columbia.edu/files/content/research/AI%20for%20Climate%20&%20Nature%20- %20Bezos%20Earth%20Fund/Landscape%20Assessment%20of%20AI%20for%20Climate%20and%20Nature%20-%20May%202024.pdf
  10. Conrad P (2018) Climate Positive Design at the Global Climate Action Summit. https://thefield.asla.org/2018/10/17/climate-positive-design-at-the-global-climate-action-summit/
  11. Çiğdem A, Akyol D (2016) Ekolojik Sürdürülebilir Kentsel Yönetim Bağlamında Türkiye’de Yerel Yönetimlerin Yasal Olanakları ve 2014 Sonrasındaki Değişimi. TURAN–SAM Uluslararası Bilimsel Hakemli Dergisi, 8(32): 244-250.
  12. Demir A, Yücel G (2021) Yapay zeka temelli kentsel ısı adası analizleri: Türkiye örnekleri. Kent ve Çevre Araştırmaları Dergisi, 7(2): 85-104.
  13. Di Carlo F, Giancotti A, Reale L (2020) Re-Inventing Water-Ground Relations in Landscape Architecture Projects. Sustainability, 12(24): 10358. https://doi.org/10.3390/su122410358
  14. Dino İ (2023) UP2030: Urban planning and design ready for 2030—Artificial intelligence models for building energy performance and climate resilience. Ankara: Middle East Technical University. https://avesis.metu.edu.tr/
  15. Erkalan E (2024) Urban Planning and Design Ready for 2030 (UP2030): İstanbul’un iklim nötr ve sürdürülebilir enerji dönüşümü için yapay zekâ tabanlı yaklaşımlar. İstanbul: ODTÜ Solar Energy Application and Research Center (GÜNAM). https://www.gunam.metu.edu.tr/
  16. European Commission (2020) Guidebook 'How to develop a Sustainable Energy and Climate Action Plan (SECAP)'. European Union. https://climate-adapt.eea.europa.eu/en/metadata/guidances/how-to-develop-a-sustainable-energy-and-climate-action-plan-secap
  17. Fadeyi O, Maresova P (2020) Stakeholders’ Perception of Climate Actions in Some Developing Economies. Climate, 8(6): 66. https://doi.org/10.3390/cli8060066
  18. Fernberg P, Sturla P, Chamberlain B (2021) Pursuing an AI Ontology for Landscape Architecture. Journal of Digital Landscape Architecture, 6: 452-460. https://gispoint.de/fileadmin/user_upload/paper_gis_open/DLA_2021/537705040.pdf
  19. Folke C (2006) Resilience: The emergence of a perspective for social–ecological systems analyses. Global Environmental Change, 16(3): 253-267. https://doi.org/10.1016/j.gloenvcha.2006.04.002
  20. Folke C, Colding J, Berkes F (2004) Navigating Social and Ecological System: Building resilience and adaptive capacity in social-ecological systems. Cambridge University Press.
  21. Forman R (2014) Urban Ecology: Science of Cities. New York: Cambridge University Press.
  22. Galderisi A (2014) Urban resilience: A framework for empowering cities. A|Z ITU Mimarlık Fakültesi Dergisi, 11(1): 36-58.
  23. Ghorbanifar S (2025) Sustainable Urban Planning with AI-Driven Climate ResilienceModels. International Journal of Industrial Engineeringand Construction Management, 4(1): 12-21. https://www.ijiecm.com/index.php/ijiecm/article/view/48
  24. Grant Associates (2012) Gardens by the Bay. https://www.archdaily.com/254471/gardens-by-the-bay-grant-associates
  25. Harrison E (2013) Bouncing back? Recession, resilience and everyday lives. Critical Social Policy, 33(1): 97-113. https://doi.org/10.1177/0261018312439365
  26. Hermosilla T, Wulder M, White J, Coops N, Bater C, Hobart G (2024) Characterizing long-term tree species dynamics in Canada’s forested ecosystems using annual time series remote sensing data. Forest Ecology and Management, 572: 122313. https://doi.org/10.1016/j.foreco.2024.122313
  27. Istanbul Metropolitan Municipality (2023) UP2030 Horizon Europe project: Climate-neutral and resilient urban transformation in Istanbul. İstanbul. https://cevre.ibb.istanbul/iklim-degisikligi-sube-mudurlugu/horizon-ufuk-avrupa-projesi-up2030/
  28. Izmir Metropolitan Municipality (2020) Izmir Sustainable Energy Climate Action Plan. Izmir: Euopean Union. https://mycovenant.eumayors.eu/storage/web/mc_covenant/documents/31/98KaWT7wBZ-ITIW1A7bpSrgh9rZmmGJ6.pdf
  29. Jorgensen G, Fryd O, Lund A, Anderson P, Herslund L (2022) Nature-based climate adaptation projects, their governance and transitional potential-cases from Copenhagen. Frontiers in Sustainable Cities, 4. https://doi.org/10.3389/frsc.2022.906960
  30. Kahraman A, Avcı M (2022) Makine öğrenimi ile ekosistem hizmetlerinin mekânsal modellenmesi. Peyzaj Araştırmaları ve Planlama Dergisi, 4(1): 55-72.
  31. Konya Metropolitan Municipality (2025) Projects of Konya Metropolitan Municipality. https://mlgp4climate.com/mlgp-members/konya-metropolitan-municipality
  32. Kumar D, Shekhar S, Tewary T (2025) Editorial: Al and data analytics for climate data management. Frontiers in Environmental Sciences, 13: 1679608. https://doi.org/10.3389/fenvs.2025.1679608.
  33. Kundak S (2017) Dirençliliğin Temeli. Resilience, 1(1): 55-69. https://doi.org/10.32569/resilience.358081
  34. Lenzholzer S, Brown R (2013) Climate-responsive landscape architecture design education. Journal of Cleaner Production, 61: 89-99. https://doi.org/10.1016/J.JCLEPRO.2012.12.038
  35. Lin Y, Wu T, Wang C, Ou J, Hsu T, Lyu S,. Taniar D (2025) An intelligent plant watering decision support system for drought monitoring & analysis based on AIoT and an LSTM time-series framework. Internet of Things, 32: 101617. https://doi.org/10.1016/j.iot.2025.101617
  36. Maged A, Abdelalim A, Mohamed A (2025) Generative design optimization of tree distribution for enhanced thermal comfort in communal spaces with special reference to hot arid climates. Scientific Reports, 15: 16659. https://doi.org/10.1038/s41598-025-96763-4
  37. Mahmoud I, Garcia E (2019) Urban green infrastructure and climate resilience: A review of AI applications in city-scale planning. Urban Climate, 30: 100534.
  38. Miljo Metropolen (2011) Copenhagen Climate Adaptation Plan. City of Copenhagen, Department of Environment. https://climate-adapt.eea.europa.eu/en/mission/knowledge-and-data/signatory-reporting/31009/Q8.1.1.2/Copenhagen%20Climate%20Adaptation%20Plan%20-%202011.pdf/@@download/file
  39. Moraci F, Errigo M, Fazia C, Campisi T, Castelli F (2020) Cities under Pressure: Strategies and Tools to Face Climate Change and Pandemic. Sustainability, 12(18): 7743. https://doi.org/10.3390/su12187743
  40. Nagendra H, Bai X (2008) Urbanization and its impact on India's cities. Environment and Urbanization, 20(2): 475-490.
  41. Nagendra H, Mundoli S (2019) Cities and Canopies: Trees in Indian Cities. India: Penguin Random House. Newman P, Jennings I (2008) Cities as sustainable ecosystems: Principles and practices. Island Press. https://parfikh.wordpress.com/wp-content/uploads/2012/01/cities-as-sustainable-ecosystem.pdf
  42. Nitavska N, Mengots A (2017) Digital Tools in Landscape Architecture. Scientific Journal of Latvia University of Agriculture, Landscape Architecture and Art, 11(11): 42-50. https://doi.org/10.22616/j.landarchart.2017.11.0
  43. Özyiğit M (2025) Yenişehir Dijital İkiz Projesi ve İklim Dirençliliği Stratejileri. Mersin: Yenişehir Belediyesi. Erişim Tarihi: 04.02.2026.
  44. Pettorelli N (2012) Climate change as a main driver of ecological research. Journal of Applied Ecology, 49(3): 542-545. https://doi.org/10.1111/j.1365-2664.2012.02146.x
  45. Republic of Türkiye Ministry of Environment, Urbanization and Climate Change (2020) 2020-2023 National Smart Cities Strategy and Action Plan. Konya. Erişim Tarihi: 12.02.2026.
  46. Sağlık A, Minkara E (2024) Perception in Human Psychology and Landscape Prioritised Visualisation of Space with Artificial Intelligence. Journal of Architectural Sciences and Applications, 9(2): 831-843. https://doi.org/10.30785/mbud.1530150
  47. Santamouris M (2020) Recent progress on urban overheating and heat island research. Integrated assessment of the energy, environmental, vulnerability and health impact. Synergies with the global climate change. Energy and Buildings, 207: 109482. https://doi.org/10.1016/j.enbuild.2019.109482
  48. Shaamala A, Yiğitcanlar T, Nili A, Nyandega D (2025) Algorithmic urban greening for thermal resilience: AI-optimised tree placement and species selection. Cities, 167. https://doi.org/10.1016/j.cities.2025.106356
  49. Sheppard S (2012) Visualizing Climate Change: A Guide to Visual Communication of Climate Change and Developing Local Solution (First Edition ed.). Routledge. https://doi.org/10.4324/9781849776882
  50. Smith A (2019) The future of landscape architecture: Integrating AI and design practices. Landscape Architecture Review, 22(2): 55-65.
  51. Sodoudi S, Müller F, Kallert A (2022) AI-supported biodiversity monitoring systems for resilient urban ecosystems. Ecological Informatics, 69: 101626.
  52. Stanczuk-Galwiaczek M, Sobolewska-Mikulska K, Ritzema H, van Loon-Steensma J (2018) Integration of water management and land consolidation in rural areas to adapt to climate change: Experiences from Poland and the Netherlands. Land Use Policy, 77: 498-511. https://doi.org/10.1016/j.landusepol.2018.06.005
  53. Tebyanian N (2020) Application of Machine Learning for Urban Land-scape Design: A Primer for Landscape Architects. Journal of Digital Landscape Architecture, 5: 217-226. https://gispoint.de/fileadmin/user_upload/paper_gis_open/DLA_2020/537690023.pdf
  54. Toderas M (2025) Artificial Intelligence for Sustainability: A Systematic Review and Critical Analysis of AI Applications, Challenges, and Future Directions. Sustainability, 17(17): 8049. https://doi.org/10.3390/su17178049
  55. Tuğaç Ç (2019) Kentsel Dirençlilik Perspektifinden Yerel Yönetimlerin Görevleri ve Sorumlulukları. İdealkent, 10(28): 984-1019. https://doi.org/10.31198/idealkent.634144
  56. Türkiye Today (2025) Home. https://www.turkiyetoday.com/nation/konya-set-to-open-flagship-city-library-turkiyes-first-zero-carbon-building-130395?s=1. Erişim Tarihi: 14.01.2026.
  57. Tzoulas K, Korpela K, Venn S, Yli-Pelkonen V, Niemela J, James P (2007) Promoting ecosystem and human health in urban areas using Green Infrastructure: A literature review. Landscape and Urban Planning, 81(3): 167-178. https://doi.org/10.1016/j.landurbplan.2007.02.001
  58. UNISDR (2009) 2009 UNISDR terminology on disaster risk reduction. https://www.undrr.org/publication/2009-unisdr-terminology-disaster-risk-reduction. Erişim Tarihi: 10.01.2026.
  59. Walker B, Salt D (2006) Resilience thinking: Sustaining ecosystems and people in a changing world. Washington: Island Press.
  60. Walker B, Holling C, Carpenter S, Kinzig A (2004) Resilience, adaptability and transformability in social–ecological systems. Ecology and Society, 9(2): 5. http://www.ecologyandsociety.org/vol9/iss2/art5/
  61. Xing Y, Gan W, Chen Q, Yu P (2025) AI-generated content in landscape architecture: A survey. AI Open, 6: 220-243. https://doi.org/10.1016/j.aiopen.2025.10.002
  62. Yenişehir Municipality (2024) Yenişehir Belediyesi ’Dijital İkiz Projesi’ ile şehri dönüştürecek. https://www.iha.com.tr/mersin-haberleri/yenisehir-belediyesi-dijital-ikiz-projesi-ile-sehri-donusturecek-121687189. Erişim Tarihi: 10.02.2026.
  63. Yi S, Li X, Tu W, Zhao T (2025) Planning for cooler cities: A multimodal AI framework for hyperlocal spatio-temporal urban heat stress prediction and mitigation. Urban Forestry & Urban Greening, 114. https://doi.org/10.1016/j.ufug.2025.129101
  64. Zhou H, Wang J, Wan J, Jia H (2010) Resilience to natural hazards: a geographic perspective. Natural Hazards, 53: 21-41. https://doi.org/10.1007/s11069-009-9407-y
  65. Zhou J, Wang T (2018) Data-driven landscape architecture: The role of big data. Journal of Landscape Architecture, 13(2): 33-45.
  66. Ziersen J, Clauson-Kaas J, Rasmussen J (2017) The role of Greater Copenhagen Utility in implementing the city's Cloudburst Management Plan. Water Practice and Technology, 12(2): 338-343. https://doi.org/10.2166/wpt.2017.039
  67. Lin Y, Wu T, Wang C, Ou J, Hsu T, Lyu S,. Taniar D (2025) An intelligent plant watering decision support system for drought monitoring & analysis based on AIoT and an LSTM time-series framework. Internet of Things, 32: 101617. https://doi.org/10.1016/j.iot.2025.101617