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Silifke (Mersin) İlçesi Kentsel Yayılımının Yeşil Alanlar Odağında Değerlendirilmesi: 2050 Yılı Projeksiyonu

Year 2024, Volume: 9 Issue: 1, 227 - 248, 30.07.2024
https://doi.org/10.30785/mbud.1444609

Abstract

Bu çalışmanın amacı, geçmişten geleceğe (1990-2020-2050) uzanan arazi değişimi eğilimleri ile dirençli kentler yaratmayı amaçlayan mekânsal planlama çalışmalarına bir çerçeve sunmaktır. Ayrıca kentsel ekosistem hizmetleri sağlayan kentsel yeşil alanların mevcut ve gelecekteki durumu ortaya konarak sonuçların mekânsal planlama stratejilerine rehberlik etmesi amaçlanmaktadır. Bu kapsamda, Silifke ilçesi örneğinde, 2050 yılı arazi değişimi eğilimleri ortaya konarak sonuçlar kentsel yeşil alan ihtiyaçları açısından değerlendirilmiştir. Adana-Mersin Çevre Düzeni Planında belirtilen gelişim alanlarının çoğunda yapılaşma beklendiği görülmüştür. Bu alanların tamamı sırasıyla tarımsal alanlardan (202 ha) ve çıplak alanlardan (46 ha) oluşmaktadır. 2050 yılı nüfusuna göre Silifke ve Taşucu-Kum Mahallesi imar sınırlarındaki yerleşimlerde sırasıyla yaklaşık 102.923 ve 24.815 kişinin bulunacağı tahmin edilmektedir. Mekânsal plan mevzuatına göre 2050 yılı imar planı sınırlarındaki kentsel yeşil alan miktarının sırasıyla en az 1.029.230m² ve 248.150 m² olması gerekmektedir. Sonuç olarak, mekânsal planlama çalışmalarını yapacak karar vericilerin, kentsel yeşil alan stratejilerini bu bulgular rehberliğinde belirlemeleri beklenmektedir.

Ethical Statement

Makale ulusal ve uluslararası araştırma ve yayın etiğine uygundur. Makalenin Etik Kurul İzin Belgesi Gerektirmeyen Bir Çalışma Olduğunu Beyan Ederiz.

Supporting Institution

Bu çalışma Ç.Ü. Araştırma Projeleri Birimi Tarafından Desteklenmiştir. Proje No: FDK-2019-11889

Project Number

FDK-2019-11889

References

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  • Alphan, H. & Derse, M. A. (2013). Change detection in Southern Turkey using normalized difference vegetation index (NDVI). Journal of Environmental Engineering and Landscape Management, 21:1, 12-18, DOI: 10.3846/16486897.2012.663091
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  • Batty, M., Besussi, E., Chin, N. X. & Asami, Y. (2019). Urban modelling: Algorithms, calibrations, predictions. Cambridge University Press.
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  • Hess, A., Iyer, H. & Malm, W. (2001). Linear trend analysis: a comparison of methods. Atmospheric Environment 35 (2001) 5211–5222
  • Lambin, E. F., Geist, H. J. & Lepers, E. (2003). Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environment and Resources, 28(1), 205-241.
  • LI, Landscape Institute. (2009). Green infrastructure: connected and multifunctional landscapes. Landscape Institute Position Statement, The Landscape Instute Policy Commitee, London.
  • Li, F., Wang, L., Chen, Z., Clarke, K.C. & Li, M. (2018). Extending the SLEUTH model to integrate habitat quality into urban growth simulation Journal of Environmental Management 217 (2018) 486-498. doi.org/10.1016/j.jenvman.2018.03.109
  • LMS, Land Monitoring Service (Copernicus) (2020). https://land.copernicus.eu/user-corner/technical- library/clc-country-coverage-1990-2018-v20u1 Accessed: 24.02.2020
  • MAES. (2015). Mapping and assessment of urban ecosystems and their services; EUR 27706 EN; doi:10.2788/638737
  • MAES. (2016). Mapping and Assessment of Ecosystems and Their Services. Urban Ecosystems. 4th Report – Final May 2016. Publications Office of the European Union, Luxembourg. Sf 61
  • Masek, J. G., Huang, C., Wolfe, R., Cohen, W., Hall, F., Kutler, J. & Nelson, P. (2008). North American forest disturbance mapped from a decadal Landsat record." Remote Sensing of Environment, 112(6), 2914-2926. doi:10.1016/j.rse.2007.06.022.
  • MBS. (2014). Mevzuat Bilgi Sistemi Mekânsal Planlar Yapım Yönetmeliği, 2014. https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=19788&MevzuatTur=7&MevzuatTertip=5 Erişim: 29.10.2022
  • MBS. (2017). Mevzuat Bilgi Sistemi Planlı Alanlar İmar Yönetmeliği, 2017. https://www.mevzuat.gov.tr/mevzuat? MevzuatNo=23722&MevzuatTur=7&MevzuatTertip=5 Erişim: 29.10.2022
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  • Silva, E.A. & Clarke, K.C. (2002). Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Comput., Environ. and Urban Systems 26 (2002) 525–552
  • Symeonakis, E. (2016). Modelling land cover change in a Mediterranean environment using Random Forests and a multi-layer neural network model. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016, pp. 5464-5466, doi: 10.1109/IGARSS.2016.7730423.
  • Tatlıdil, H. ( 1992). Uygulamalı çok değişkenli istatistiksel analiz. Engin Yayınları.
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  • Türker, B. H. & Gül, A. (2022). Kentsel açık ve yeşil alanlarının niceliksel analizi ve irdelenmesi: Uşak Kent merkezi Örneği, Kent Akademisi Dergisi, 15(4):2088-2109. https://doi.org/10.35674/kent.999451
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Evaluating the Urban Expansion of Silifke (Mersin) District with a Focus on Green Spaces: The 2050 Projection

Year 2024, Volume: 9 Issue: 1, 227 - 248, 30.07.2024
https://doi.org/10.30785/mbud.1444609

Abstract

The aim of this study is to provide a framework for spatial planning aimed at creating resilient cities through land change trends from the past to the future (1990-2020-2050). Additionally, it aims to guide planning strategies by highlighting the current and future status of urban green areas. In this context, the trends for 2050 were evaluated in terms of green area requirements, using the Silifke example. Most of the development areas in Adana-Mersin RegionalPlan are expected to be built. All of these areas consist of agricultural (202 ha) and bare lands (46 ha). It is estimated that by 2050, the populations of Silifke-Taşucu-Kum Neighborhood will be 102,923 and 24,815, respectively. According to spatial planning regulations, the minimum green area within the 2050 urban plan boundaries should be 1,029,230 m² and 248,150 m², respectively. Consequently, decision-makers are expected to determine green area strategies guided by these findings in spatial planning studies.

Ethical Statement

The article complies with national and international research and publication ethics. We declare that the article is a study that does not require ethics committee permission.

Supporting Institution

This study was supported by Cukurova University Research Projects Unit. Project Number: FDK-2019-11889.

Project Number

FDK-2019-11889

References

  • Ahern, J. (2007). Green infrastructure for cities: The spatial dimension. C 2007 IWA Publishing. Cities of the Future Towards Integrated Sustainable Water and Landscape Management by Vladimir Novotny and Paul Brown. ISBN: 1843391368. Published by IWA Publishing, London, UK.
  • Akın, T. & Gül, A. (2020). Isparta-Atabey yöresinin ekoturizm potansiyeli ve turizm rotalarının belirlenmesi. Mimarlık Bilimleri ve Uygulamaları Dergisi, 5(2), 221-240.
  • Alphan, H. & Derse, M. A. (2013). Change detection in Southern Turkey using normalized difference vegetation index (NDVI). Journal of Environmental Engineering and Landscape Management, 21:1, 12-18, DOI: 10.3846/16486897.2012.663091
  • Alphan, H., Karamanlı, E., Derse, M. A. & Uslu, C. (2022). Analyzing pattern features of urban/rural residential land use change: The case of the southern coast of Turkey. Land Use Policy, 122(2022), 106348.
  • Batty, M., Besussi, E., Chin, N. X. & Asami, Y. (2019). Urban modelling: Algorithms, calibrations, predictions. Cambridge University Press.
  • Benedict, M. A. & McMahon, E. T. (2002). Green infrastructure: Smart conservation for the 21st Century. Renewable Resources Journal 20.3 (2002): 12-17.
  • Chang, Q., Li, X., Huang, X. & Wu, J. (2012). A GIS-based green infrastructure planning for sustainable urban land use and spatial development. (International Conference on Environmental Science and Engineering (ICESE 2011)) Prodecia Environmental Sciences. 12, 491-498.
  • Derse, M. A. (2023). Suya Dayalı Ekosistem Servislerinin Mekânsal Planlama Sürecine Entegrasyonu: Silifke Örneğinde Yeşil Altyapı Yaklaşımı (Doktora Tezi). Çukurova Üniversitesi, Fen Bilimleri Enstitüsü, Adana, 221.
  • Eastman, J. R., Solorzano, L. & Fossen, M. V. (2005). Transition Potential Modeling for Land-Cover Change. In GIS, Spatial Analysis and Modeling, edited by David J. Maguire, Micheal Batty ve Michael F. Goodchild, 357-385. Redlands, CA: ESRI Press, 2005.
  • EC. (2013). EC-European Commission, Building a Green Infrastructure for Europe. Luxembourg: Publications Office of the European Union, 2013 — 24 pp. ISBN 978-92-79-33428-3, doi: 10.2779/54125.
  • EEA, European Environment Agency. (2014). Spatial analysis of green infrastructure in Europe, EEA Technical report, No 2/2014, ISNN 1725-2237, sf: 9.
  • EEA, European Environment Agency. (2017). Updated CLC illustrated nomenclature guidelines, Prepared by: Barbara Kosztra, György Büttner, Gerard Hazeu, Stephan Arnold, Service Contract No 3436/R0- Copernicus/EEA.56586 Task 7, D7.2 – Part 1.
  • EEA, European Environment Agency. (2019). Land Use/Land Cover. Accessed January 24, 2024. https://www.eea.europa.eu/data-and-maps/dashboards/land-cover-and-change-statistics
  • EEA, European Environment Agency. (2020). Corine Land Cover (CLC). Retrieved from https://land.copernicus.eu/pan-european/corine-land-cover.
  • EU. (2016). Mapping Guide for a European Urban Atlas, Pg 21. European Commission, 2016.
  • Elmqvist, T., Fragkias, M., Goodness, J., Güneralp, B., Marcotullio, P.J., McDonald, R.I., Parnell, S., Schewenius, M., Sendstad, M., Seto, K.C. & Wilkinson, C. (edts) (2013). Urbanization, Biodiversity and Ecosystem Services: Challenges and Opportunities: A Global Assessment, DOI 10.1007/978-94-007-7088-1.
  • Fan, X., Zhao, L. & He, D. (2020). Land Use change and its driving forces in the coastal zone. Pol. J. Environ. Stud., 29(2), 1143-11560. doi:10.15244/pjoes/108516.
  • Feng, H. H., Liu, H. P. and L¨u, Y. 2012. Scenario prediction and analysis of urban growth using SLEUTH model. Pedosphere. 22(2): 206–216.
  • Firehock, K. & Walker, R. A. (2015). Strategic Green Infrastructure Planning: A Multi-Scale Approach. The Green Infrastructure Center Inc., Island Press, ISBN: 978-1-61091-692-9.
  • Gezer, A. & Gül, A. Eds. (2009). Kent Ormancılığı (Kavramsal-Teknik ve Kültürel Boyutu). SDU Orman Fakültesi, Kitap Yayın No: 86, s: 01-246. Isparta. 2009. (ISBN: 978-9944-452-30-4) SDU Basım evi- Isparta. https://www.researchgate.net/profile/Atila- Gul/publication/348522666_KENT_ORMANCILIGI_Kavramsal_teknik_ve_Kulturel_Yaklasimlar/links/600216b445851553a049292f/KENT-ORMANCILIGI-Kavramsal-teknik-ve-Kueltuerel-Yaklasimlar.pdf
  • Gül, A. & Küçük, V. (2001). Kentsel açık-yeşil alanlar ve Isparta kenti örneğinde irdelenmesi,” Süleyman Demirel Üniversitesi Orman Fakültesi Dergisi. Seri: A, Sayı: 2, Yıl: 2001, ISSN: 1302-7085, Sayfa: 27-48.
  • Forman, R. T. T. (2016). Urban ecology principles: are urban ecology and natural area ecology really different?. Landscape Ecology, 31(8), 1653-1662.
  • Hepcan, Ç. C. & Hepcan, Ş. (2017). Ege Üniversitesi Lojmanlar yerleşkesinin hava kalitesinin iyileştirilmesine yönelik düzenleyici ekosistem servislerinin hesaplanması. Ege Üniv. Ziraat Fak. Derg., 54 (1):113-120.
  • Hepcan, Ç. Ç. & Hepcan, Ş. (2018). Kentsel yeşil altyapı analizi: Bornova örneği. Mediterranean Agricultural Sciences (2018), 31(1):DOI:10.29136/mediterranean.378073
  • Hess, A., Iyer, H. & Malm, W. (2001). Linear trend analysis: a comparison of methods. Atmospheric Environment 35 (2001) 5211–5222
  • Lambin, E. F., Geist, H. J. & Lepers, E. (2003). Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environment and Resources, 28(1), 205-241.
  • LI, Landscape Institute. (2009). Green infrastructure: connected and multifunctional landscapes. Landscape Institute Position Statement, The Landscape Instute Policy Commitee, London.
  • Li, F., Wang, L., Chen, Z., Clarke, K.C. & Li, M. (2018). Extending the SLEUTH model to integrate habitat quality into urban growth simulation Journal of Environmental Management 217 (2018) 486-498. doi.org/10.1016/j.jenvman.2018.03.109
  • LMS, Land Monitoring Service (Copernicus) (2020). https://land.copernicus.eu/user-corner/technical- library/clc-country-coverage-1990-2018-v20u1 Accessed: 24.02.2020
  • MAES. (2015). Mapping and assessment of urban ecosystems and their services; EUR 27706 EN; doi:10.2788/638737
  • MAES. (2016). Mapping and Assessment of Ecosystems and Their Services. Urban Ecosystems. 4th Report – Final May 2016. Publications Office of the European Union, Luxembourg. Sf 61
  • Masek, J. G., Huang, C., Wolfe, R., Cohen, W., Hall, F., Kutler, J. & Nelson, P. (2008). North American forest disturbance mapped from a decadal Landsat record." Remote Sensing of Environment, 112(6), 2914-2926. doi:10.1016/j.rse.2007.06.022.
  • MBS. (2014). Mevzuat Bilgi Sistemi Mekânsal Planlar Yapım Yönetmeliği, 2014. https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=19788&MevzuatTur=7&MevzuatTertip=5 Erişim: 29.10.2022
  • MBS. (2017). Mevzuat Bilgi Sistemi Planlı Alanlar İmar Yönetmeliği, 2017. https://www.mevzuat.gov.tr/mevzuat? MevzuatNo=23722&MevzuatTur=7&MevzuatTertip=5 Erişim: 29.10.2022
  • MEA. (2003). Millennium Ecosystem Assessment,2003. Ecosystems and Human Well-Being. A Framework for Assessment. ISLAND Press, Washington, DC, ISBN: 1-55963-402-2.
  • MEA. (2005). Millennium Ecosystem Assessment, 2005. Ecosystems and Human Well-being: Synthesis. Island Press, Washington, DC. 1-59726-040-1.
  • Mell, I. C. (2010). Green infrastructure: Concepts, perceptions and its use in spatial planning. School of Architecture, Planning and Landscape, Newcastle University, Doktora Tezi.
  • MGM. (2022). Meteoroloji Genel Müdürlüğü https://www.mgm.gov.tr/veridegerlendirme/il-ve-ilceler- istatistik.aspx?m=ICEL Accesed: 27.07.2022
  • Önder, S., Polat, A. & Korucu, S. (2011). The evaluation of existing and proposed active green spaces in Konya Selçuklu District, Turkey. African Journal of Agricultural Research. Vol. 6(3), pp. 738-747, 4 February 2011 Available online at http://www.academicjournals.org/AJAR DOI: 10.5897/AJAR10.326 ISSN 1991-637X.
  • Sahaa, P., Mitrab, R., Chakrabortyb, K. & Roy, M. (2022). Application of multi layer perceptron neural network Markov Chain model for LULC change detection in the Sub-Himalayan North Bengal. Remote Sensing Applications: Society and Environment 26 (2022) 100730.
  • Sankarrao, L., Ghose, D. K. & Rathinsamy, M. (2021). Predicting land-use change: Intercomparison of different hybrid machine learning models. Environmental Modelling & Software, 145, November 2021, 105207 doi.org/10.1016/j.envsoft.2021.105207
  • SB, Silifke Belediyesi. (2019). https://silifke.bel.tr/Content?header=5&title=21 Accesed: 26.07.2022
  • Seto, K. C., Güneralp, B. & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16083-16088.
  • Silva, E.A. & Clarke, K.C. (2002). Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Comput., Environ. and Urban Systems 26 (2002) 525–552
  • Symeonakis, E. (2016). Modelling land cover change in a Mediterranean environment using Random Forests and a multi-layer neural network model. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016, pp. 5464-5466, doi: 10.1109/IGARSS.2016.7730423.
  • Tatlıdil, H. ( 1992). Uygulamalı çok değişkenli istatistiksel analiz. Engin Yayınları.
  • TerrSet. (2016). TerrSet Geospatial Monitoring and Modeling System, Manual Book. Clark Labs., Clark Unv. Ed: J. Ronald Eastman.
  • Türker, B. H. & Gül, A. (2022). Kentsel açık ve yeşil alanlarının niceliksel analizi ve irdelenmesi: Uşak Kent merkezi Örneği, Kent Akademisi Dergisi, 15(4):2088-2109. https://doi.org/10.35674/kent.999451
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There are 52 citations in total.

Details

Primary Language English
Subjects Landscape Planning
Journal Section Research Articles
Authors

Mehmet Ali Derse 0000-0001-9894-7945

Hakan Alphan 0000-0003-1139-4087

Project Number FDK-2019-11889
Publication Date July 30, 2024
Submission Date February 28, 2024
Acceptance Date May 23, 2024
Published in Issue Year 2024 Volume: 9 Issue: 1

Cite

APA Derse, M. A., & Alphan, H. (2024). Evaluating the Urban Expansion of Silifke (Mersin) District with a Focus on Green Spaces: The 2050 Projection. Journal of Architectural Sciences and Applications, 9(1), 227-248. https://doi.org/10.30785/mbud.1444609