Assessment of Urban Green Space Distribution within the Scope of European Green Deal Using NDVI Indice; Case of Nicosia/Cyprus
Year 2022,
Volume: 7 Issue: 2, 615 - 623, 30.12.2022
Buket Eyileten
,
Çiğdem Esendağlı
,
Serdar Selim
Abstract
In this study, the urban green space distribution was determined, and the city's compliance with the European Green Deal was evaluated. Firstly, Landsat 8 satellite images were radiometrically corrected with the Quantum GIS software. Then, NDVI was produced using the Red-Green-Blue and Near-Infrared bands of the processed data obtained. Finally, the NDVI image with a value between -1 and +1 was reclassified to define urban open green spaces. The classification data showed that open green areas have a nonhomogeneous distribution throughout the city, and the amount of green space per capita is approximately 200 m². According to the classification results of Northern Nicosia, a surface area of 475 km², the amount of green space is calculated as 16m², constituting 2.97%. Thus, it has been concluded that open green regions are denser in certain parts of the city than others and do not have a homogeneous distribution that can serve the whole town.
Thanks
An oral presentation of this study was made in TUFUAB 2022: XI. Turkish National Photogrammetry and Remote Sensing Association Technical Symposium. And the abstract of this article was published in the abstract booklet of the same conference. The article complies with national and international research and publication ethics. Ethics committee permission was not required for the study.
References
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Metropolis. Journal of Cleaner Production, 261, 121183.
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Remote Sensing and Space Science, 23(1), 63–75.
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Remote Sensing, 7(1), 600–626.
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Urban Forestry & Urban Greening, 31, 56–66.
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classification. In E3S Web of Conferences (Vol. 153, p. 02004). EDP Sciences.
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Environment, 164, 298–313.
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spectral response and a vegetation index. International Journal of Remote Sensing and Earth Sciences (IJReSES), 18(2), 177-188.
- Schebella, M., Weber, D., Schultz, L., & Weinstein, P. (2019). The wellbeing benefits associated with perceived and measured biodiversity in Australian urban green spaces. Sustainability,
11(3), 802.
- Selim, S. (2021). Yeşil Mutabakat çerçevesinde kentsel yeşil alanların yeşil altyapı sistemine entegrasyonu: Antalya-Konyaaltı örneği. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü
Dergisi, 25(3), 636–643.
- Selim, S. & Karakuş, N. (2016). Sufficiency of Public Open-Green Spaces in Fethiye Town/Turkey and Accessibility Analysis with GIS Techniques. I. Uluslararası Akademik Araştırmalar
Kongresi Bildiriler Kitabı (INES 2016), Antalya, Türkiye, 3-5 Kasım 2016, vol.1, s.82-87.
- Selim, S., & Demir, N. (2018). Analysis of landscape patterns and connectivity between tree clusters derived from LIDAR data. Fresenius Environmental Bulletin, 27(5A), 3512-3520.
- Selim, S., & Demir, N. (2019). Detection of ecological networks and connectivity with analyzing their effects on sustainable urban development. International Journal of Engineering and
Geosciences, 4(2), 63-70.
- Semeraro, T., Scarano, A., Buccolieri, R., Santino, A., & Aarrevaara, E. (2021). Planning of Urban Green Spaces: An Ecological Perspective on Human Benefits. Land, 10(2), 105.
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- Tuğluer, M. & Çakır, M. (2019). Examination of the components of UFORE model serving the urban ecosystem. Journal of Architecture Sciences and Applications, 4 (2), 193-200. Doi:
https://doi.org/10.30785/mbud.586754
- Tuğluer, M. & Çakır, M. (2021). Ecological importance of urban trees and their role in sustainable cities. Şebnem Ertaş Beşir, M. Bihter Bingül Bulut and İrem Bekar (Ed.). Architectural
Sciences and Sustainability. 2021, Volume:2, 81-96. ISBN: 978-625-8061-43-7. Iksad Publications.
- Tutak, M., Brodny, J., & Bindzár, P. (2021). Assessing the level of energy and climate sustainability in the European Union Countries in the context of the European green deal strategy and
agenda 2030. Energies, 14(6), 1767.
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foundation-remote-sensing-phenology
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Avrupa Yeşil Mutabakatı Kapsamında Lefkoşa’nın Kentsel Yeşil Alan Dağılımının NDVI ile Değerlendirilmesi
Year 2022,
Volume: 7 Issue: 2, 615 - 623, 30.12.2022
Buket Eyileten
,
Çiğdem Esendağlı
,
Serdar Selim
Abstract
Bu çalışmada, şehrin kentsel yeşil alan dağılımı belirlenmiş ve mevcut yeşil alan varlığı Avrupa Yeşil Mutabakatı kapsamında değerlendirilmiştir. Çalışmada, Landsat 8 OLI görüntüleri kullanılmış olup, görüntülere öncelikle Quantum GIS yazılımı ile radyometrik düzeltme işlemi yapılmıştır. Ardından elde edilen işlenmiş verilerin Kırmızı-Yeşil-Mavi ve Yakın Kızılötesi bantları kullanılarak Normalleştirilmiş Fark Bitki Örtüsü İndeksi üretilmiştir. Son olarak, -1 ile +1 arasında değer olan NDVI görüntüsü, kentsel açık yeşil alanları belirlemek üzere yeniden sınıflandırılmıştır. Sınıflandırma verileri, açık yeşil alanların şehir genelinde homojen olmayan bir dağılıma sahip olduğunu ve kişi başına düşen yeşil alan miktarının yaklaşık 200 m² olduğunu göstermiştir. 475 km² yüzölçümüne sahip Kuzey Lefkoşa'nın sınıflandırma sonuçlarına göre yeşil alan miktarı %2,97 olmak üzere 16m² olarak hesaplanmıştır. Böylece açık yeşil bölgelerin kentin belirli bölgelerinde diğerlerine göre daha yoğun olduğu ve tüm kente hizmet edebilecek homojen bir dağılıma sahip olmadığı sonucuna varılmıştır.
References
- Ardahanlioglu, Z. R., Selim, S., Karakus, N., & Cinar, I. (2020). GIS-Based Approach to Determine Suitable Settlement Areas Compatible with the Natural Environment. Journal of Environmental Science and Management, 23(1), 71–82.
- Arghavani, S., Malakooti, H., & Ali Akbari Bidokhti, A. A. (2020). Numerical assessment of the urban green space scenarios on urban heat island and thermal comfort level in Tehran
Metropolis. Journal of Cleaner Production, 261, 121183.
- Arora, N. K., Fatima, T., Mishra, I., Verma, M., Mishra, J., & Mishra, V. (2018). Environmental sustainability: challenges and viable solutions. Environmental Sustainability, 1(4), 309–340.
- Artmann, M., Inostroza, L., & Fan, P. (2019). Urban sprawl, compact urban development and green cities. How much do we know, how much do we agree? Ecological Indicators, 96, 3–9.
- Chowdhury, M., Hasan, M. E., & Abdullah-Al-Mamun, M. (2020). Land use/land cover change assessment of Halda watershed using remote sensing and GIS. The Egyptian Journal of
Remote Sensing and Space Science, 23(1), 63–75.
- Czapla-Myers, J., McCorkel, J., Anderson, N., Thome, K., Biggar, S., Helder, D., Aaron, D., Leigh, L., & Mishra, N. (2015). The Ground-Based Absolute Radiometric Calibration of Landsat 8 OLI.
Remote Sensing, 7(1), 600–626.
- Çakır, M. (2021). Conservation Landscaping and Turfgrasses. Atila Gül and Mert Çakır (Eds.). Architectural Sciences and Protection & Conservation & Preservation. 2021, Volume:1, 623-
652. ISBN: 978-625-8061-45-1. Iksad Publications.
- Devlet Planlama Örgütü. (2010). 2008 Yılı Makroekonomik ve Sektörel Gelişmeler. Lefkoşa: KKTC Devlet Basımevi.
- Farahani, L. M., & Maller, C. J. (2018). Perceptions and preferences of urban greenspaces: a literature review and framework for policy and practice. Landscape Online, 61, 1-22.
- Feltynowski, M., Kronenberg, J., Bergier, T., Kabisch, N., ŁAszkiewicz, E. & Strohbach, M. W. (2018). Challenges of urban green space management in the face of using inadequate data.
Urban Forestry & Urban Greening, 31, 56–66.
- Hong, D., Yokoya, N., Ge, N., Chanussot, J., & Zhu, X. X. (2019). Learnable manifold alignment (LeMA): A semi-supervised cross-modality learning framework for land cover and land use
classification. ISPRS Journal of Photogrammetry and Remote Sensing, 147, 193–205.
- Kamal, M., Muhammad, F. H., & Mahardhika, S. A. (2020). Effect of image radiometric correction levels of Landsat images to the land cover maps resulted from maximum likelihood
classification. In E3S Web of Conferences (Vol. 153, p. 02004). EDP Sciences.
- Kaşot, N. Kıbrıs Adası’nda dağılış gösteren çizgili kaplumbağa’nın MauremysRivulata ekolojisi ve biyolojisi hakkında bir ön çalışma. Kıbrıs Araştırmaları Dergisi, 17(40), 35-58.
- Ke, Y., Im, J., Lee, J., Gong, H., & Ryu, Y. (2015). Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations. Remote Sensing of
Environment, 164, 298–313.
- Kıbrıs Newspaper (2021). https://www.kibrisgazetesi.com/kibris/nufus-245-bin869-2-ilcede-vekil-sayilari-degisti-h121605.html
- KKTC Tarım Bakanlığı (2007). Tarım Bakanlığı İstatistik ve Planlama Şubesi, Kuzey Kıbrıs Türk Cumhuriyeti. Tarımsal Yapı ve Üretim 2007. s. 10
- Kuzey Kıbrıs’ta Doğal Yaşam - Flora. (2009, April 25). Retrieved August 31, 2010, from http://www.odtu.edu.tr/~kktctntm/KKTC_tarihi/dogal_yasam.html
- Lin, B., & Zhu, J. (2018). Changes in urban air quality during urbanization in China. Journal of Cleaner Production, 188, 312–321.
- Liu, O. Y., & Russo, A. (2021). Assessing the contribution of urban green spaces in green infrastructure strategy planning for urban ecosystem conditions and services. Sustainable Cities
and Society, 68, 102772.
- Malik, M. S., Shukla, J. P., & Mishra, S. (2019). Relationship of LST, NDBI and NDVI using landsat-8 data in Kandaihimmat watershed, Hoshangabad, India.
- Montanarella, L., & Panagos, P. (2021). The relevance of sustainable soil management within the European Green Deal. Land use policy, 100, 104950.
- Muchsin, F., Supriatna, S., Harmoko, A., Prasasti, I., Rahayu, M. I., Fibriawati, L., & Pradhono, K. A. (2022). Comparison of the radiometric correction of landsat-8 images based on object
spectral response and a vegetation index. International Journal of Remote Sensing and Earth Sciences (IJReSES), 18(2), 177-188.
- Schebella, M., Weber, D., Schultz, L., & Weinstein, P. (2019). The wellbeing benefits associated with perceived and measured biodiversity in Australian urban green spaces. Sustainability,
11(3), 802.
- Selim, S. (2021). Yeşil Mutabakat çerçevesinde kentsel yeşil alanların yeşil altyapı sistemine entegrasyonu: Antalya-Konyaaltı örneği. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü
Dergisi, 25(3), 636–643.
- Selim, S. & Karakuş, N. (2016). Sufficiency of Public Open-Green Spaces in Fethiye Town/Turkey and Accessibility Analysis with GIS Techniques. I. Uluslararası Akademik Araştırmalar
Kongresi Bildiriler Kitabı (INES 2016), Antalya, Türkiye, 3-5 Kasım 2016, vol.1, s.82-87.
- Selim, S., & Demir, N. (2018). Analysis of landscape patterns and connectivity between tree clusters derived from LIDAR data. Fresenius Environmental Bulletin, 27(5A), 3512-3520.
- Selim, S., & Demir, N. (2019). Detection of ecological networks and connectivity with analyzing their effects on sustainable urban development. International Journal of Engineering and
Geosciences, 4(2), 63-70.
- Semeraro, T., Scarano, A., Buccolieri, R., Santino, A., & Aarrevaara, E. (2021). Planning of Urban Green Spaces: An Ecological Perspective on Human Benefits. Land, 10(2), 105.
- Sikora, A. (2021, January). European Green Deal–legal and financial challenges of the climate change. In Era Forum (Vol. 21, No. 4, pp. 681-697). Springer Berlin Heidelberg.,
- Tuğluer, M. & Çakır, M. (2019). Examination of the components of UFORE model serving the urban ecosystem. Journal of Architecture Sciences and Applications, 4 (2), 193-200. Doi:
https://doi.org/10.30785/mbud.586754
- Tuğluer, M. & Çakır, M. (2021). Ecological importance of urban trees and their role in sustainable cities. Şebnem Ertaş Beşir, M. Bihter Bingül Bulut and İrem Bekar (Ed.). Architectural
Sciences and Sustainability. 2021, Volume:2, 81-96. ISBN: 978-625-8061-43-7. Iksad Publications.
- Tutak, M., Brodny, J., & Bindzár, P. (2021). Assessing the level of energy and climate sustainability in the European Union Countries in the context of the European green deal strategy and
agenda 2030. Energies, 14(6), 1767.
- U.S.G.S. (2018). NDVI, the Foundation for Remote Sensing Phenology. Retrieved March 28, 2022, from https://www.usgs.gov/special-topics/remote-sensing-phenology/science/ndvi-
foundation-remote-sensing-phenology
- WHO, (2017). World Health Organisation, Urban Green Spaces; a brief for action. Office for Europe UN City, Marmorvej 51, Copenhagen, Denmark, 24p.
- Zheng, X., Jia, J., Guo, S., Chen, J., Sun, L., Xiong, Y., & Xu, W. (2021). Full parameter time complexity (FPTC): A method to evaluate the running time of machine learning classifiers for land
use/land cover classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 2222-2235.