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Kentleşmenin karmaşıklık düzeyinin belirlenmesi ve coğrafi dağılımının araştırılması

Year 2020, Volume: 2 Issue: 2, 57 - 63, 28.12.2020

Abstract

20. yüzyıldan itibaren kentlerin siyasal, toplumsal, ekonomik ve mekânla ilgili pek çok alt sistemden oluşan kaotik bir yapıya sahip olduğu kabul edilmektedir. Ölçekten bağımsız olarak kendini tekrar eden bu kaotik yapı fraktal geometriye sahiptir. Son 30 yılda coğrafi bilgi sistemleri alanındaki gelişmeler kentlerin bu yapısının fraktal boyut analizi ile incelenmesinde büyük kolaylıklar sağlamıştır. Fiziksel kent formunu oluşturan, binalara, yollara ve imar adalarına ait geometrik şekiller aynı zamanda fraktal kent geometrisini oluşturmaktadır. Fraktal kent geometrisi hesaplanarak kentin karmaşıklık düzeyinin belirlenmesini amaçlayan bu çalışmada, bina, yol ve imar adalarına ait fraktal boyut değerleri hesaplanmış ve istatistiksel yöntemlerle bu değerlerin coğrafi dağılımı incelenmiştir. Bu kapsamda Sivas ili, merkez ilçesi, 65 mahalleden oluşan çalışma alanında fraktal kent geometrisi bileşenlerine ait fraktal boyut değerleri ayrı ayrı hesaplanmıştır. Elde edilen bu fraktal değerlerin çalışma alanı içinde coğrafi olarak nasıl dağıldığını belirleyebilmek için TwoStep Cluster analizi kullanılmıştır. Elde edilen sonuçlara göre karmaşıklık düzeyi yüksek olan mahalleler çalışma alanının %71’ini oluşturmaktadır.

References

  • Ayazli I E (2019). An empirical study investigating the relationship between land prices and urban geometry. ISPRS International Journal of Geo-Information, 8 (10).
  • Ayazlı İ E (2011). Ulaşım ağlarının etkisiyle kentsel yayılmanın simülasyon modeli: 3. Boğaz Köprüsü örneği. Yıldız Teknik Üniversitesi, Fen Bilimleri Enstitüsü.
  • Ayazlı İ E (2017). Investigation Of the Relationship Between Property Geometry and Urbanization By Calculating Fractal Dimension Values: A Case Study Of Sivas. Afyon Kocatepe University Journal of Sciences and Engineering, 17 (1), 165–171.
  • Başlık S (2008). Dinamik kentsel büyüme modeli lojistik regresyon ve cellular automata (İstanbul ve Lizbon örnekleri). Mimar Sinan Güzel Sanatlar Üniversitesi Fen Bilimleri Enstitüsü.
  • Batty M & Longley P (1994). Fractal cities: A Geometry of Form and Function. Academic Press Limited.
  • Batty M & Longley P A (1987). Urban shapes as fractals. Area, 19, 215–221.
  • Capozza D R & Helsley R W (1989). The fundamentals of land prices and urban growth. J. Urban Econ., 26, 295–306.
  • Clarke K C & Schweizer D M (1991). Measuring the fractal dimension of natural surfaces using a robust fractal estimator. Cartogr. Geogr. Inf. Syst., 18, 37–47.
  • Erdogan G & Cubukcu K M (2014). Explaining Fractal Dimension In Populous Cities. Eurau 2014 Composıte Cıtıes.
  • Fractalyse (2016). Fractalyse. www.fractalyse.org/en-doc-1.2_The_counting_methods.html
  • Frankhauser P (1990). Aspects fractals des structures urbaines. Espace Geographique, 19–20 (1), 45–69.
  • Frankhauser P (1992). Fractal properties of settlement structures. The First International Seminar on Structural Morphology.
  • Frankhauser P (1998). The fractal approach. A new tool for the spatial analysis of urban agglomerations. Population, 52 (4), 1005–1040.
  • Frankhauser P (2004). Comparing the morphology of urban patterns in Europe—A fractal approach. Eur. Cities Insights Outskirts Rep. COST Action, 10, 79–105.
  • Frankhauser P & Pumain D (2007). Fractals and Geography. In L. Sanders (Ed.), Models in Spatial Analysis, 281–300.
  • Frankhauser P & Tannier C (2005). A multi-scale morphological approach for delimiting urban areas. CUPUM 05 : Computers in Urban Planning and Urban Management, 9th Conference Organised by the CASA.
  • Goodchild M F (1980). Fractals and the accuracy of geographical measures. Journal of the International Association for Mathematical Geology, 12 (2), 85–98.
  • Guneroglu N, Acar C, Dihkan M, Karsli F & Guneroglu A (2013). Green corridors and fragmentation in South Eastern Black Sea coastal landscape. Ocean and Coastal Management, 83, 67–74.
  • IBM. (2013). IBM Kowledge Center. www.ibm.com/support/knowledgecenter/en/SSLVMB_22.0.0/com.ibm.spss.statistics.algorithms/alg_2step_cluster.htm.
  • Jaya V, Raghukanth S T G & Sonika M S (2014). Estimating fractal dimension of lineaments using box counting method for the Indian landmass. Geocarto International, 29(3), 314–331.
  • Jiang B & Anders B S (2016). A Fractal Perspective on Scale in Geography. ISPRS International Journal of Geo-Information, 5 (6).
  • Kaya H S & Bölen F (2006). Kentsel Mekan Organizasyonundakz Farklılıkların Fraktal Analiz Yöntemi ile Değerlendirilmesi. Journal of Istanbul Kültür University, 4, 153–172.
  • Kaya H S & Bölen F (2011). Kentsel dokudaki değişimin fraktal geometri yöntemiyle incelenmesi. İTÜ Dergisi/A Mimarlık, 10 (1), 39–50.
  • Landis J & Huang W (1995). Theoretical foundations and literature review. In Transit Investments, Real Estate Values, and Land Use Change: A Comparative Analysis of Five California Rail Transit Systems (pp. 13–26). UC Berkeley: Berkeley, CA, USA.
  • Ma R, Gu C, Pu Y & Ma X (2008). Mining the urban sprawl pattern: A case study on Sunan, China. Sensors, 8 (10), 6371–6395.
  • Mandelbrot B (1967). How Long Is the Coast of Britain ? Statistical Self-Similarity and Fractional Dimension Author ( s ): Benoit Mandelbrot Source : Science , New Series , Vol . 156 , No . 3775 ( May 5 , 1967 ), pp . 636-638 Published by : American Association for the Advanc. Science, 156 (3775), 636–638.
  • MIT (2015). MIT The Bayes Information Criterion (BIC). www-math.mit.edu/~rmd/650/bic.pdf
  • Nabiyev V V (2013). Algoritmalar. Seçkin Yayınevi.
  • Ozturk D (2017). Assessment of urban sprawl using Shannon’s entropy and fractal analysis: a case study of Atakum, Ilkadim and Canik (Samsun, Turkey). Journal of Environmental Engineering and Landscape Management, 25 (3), 264–276.
  • Pentland A P (1984). Fractal-Based Description of Natural Scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6 (6), 661–674.
  • Poudyal N C, Hodges D G, Tonn B & Cho S H (2009). Valuing diversity and spatial pattern of open space plots in urban neighborhoods. Forest Policy and Economics, 11(3), 194–201.
  • Purevtseren M, Tsegmid B, Indra M & Sugar M (2018). The fractal geometry of urban land use: The case of Ulaanbaatar City, Mongolia. Land, 7 (2), 1–14.
  • Shen G (2002). Fractal dimension and fractal growth of urbanized areas. International Journal of Geographical Information Science, 16(5), 419–437.
  • Terzi F & Kaya H S (2008). Analyzing Urban Sprawl Patterns Through Fractal Geometry: The Case of Istanbul Metropolitan Area. Working Papers Series, 144 (0), 0–18.
  • Thomas I, Frankhauser P & Biernacki C (2008). The morphology of built-up landscapes in Wallonia (Belgium): A classification using fractal indices. Landscape and Urban Planning, 84 (2), 99–115.
  • Thomas I, Frankhauser P, Frenay B, Verleysen M & Samos-Matisse S M (2010). Clustering patterns of urban built-up areas with curves of fractal scaling behaviour. Environment and Planning B: Planning and Design, 37 (5), 942–954. https://doi.org/10.1068/b36039
  • TÜİK. (2018). TÜİK. www.tuik.gov.tr
  • Wendt P F (1957). Theory of Urban Land Values. Land Economics, 33 (3), 228. 1
  • Zhang T, Ramakrishnan R & Livny M (1996). BIRCH: An Efficient Data Clustering Databases Method for Very Large. ACM Sigmod Record; ACM: New York, NY, USA, 25, 103–114.

Determination of the complexity level of urbanization and investigation of its geographical distribution

Year 2020, Volume: 2 Issue: 2, 57 - 63, 28.12.2020

Abstract

Since the 20th century, cities have been accepted to have a chaotic structure consisting of many subsystems related to political, social, economic life, and space. This chaotic structure that repeats itself independently of scale has a fractal geometry. Developments in the field of geographic information systems in the last 30 years have provided great conveniences in examining this structure of cities with fractal dimension analysis. The geometrical shapes of buildings, streets, and blocks that create the physical city form constitute at the same time the fractal urban geometry. The study aims to determine the complexity level of the city by calculating the fractal urban geometry. The fractal dimension values of the buildings, roads and zoning blocks were calculated and the geographical distribution of these values were examined by statistical methods. In this context, the fractal dimension values of fractal urban geometry components were calculated separately in the study area consisting of 65 neighborhoods in Sivas province, central distirict. A two-step cluster analysis was used to determine how these obtained fractal values dispersed geographically within the study area. According to the results, neighborhoods with high level of complexity constitute 71% of the study area.

References

  • Ayazli I E (2019). An empirical study investigating the relationship between land prices and urban geometry. ISPRS International Journal of Geo-Information, 8 (10).
  • Ayazlı İ E (2011). Ulaşım ağlarının etkisiyle kentsel yayılmanın simülasyon modeli: 3. Boğaz Köprüsü örneği. Yıldız Teknik Üniversitesi, Fen Bilimleri Enstitüsü.
  • Ayazlı İ E (2017). Investigation Of the Relationship Between Property Geometry and Urbanization By Calculating Fractal Dimension Values: A Case Study Of Sivas. Afyon Kocatepe University Journal of Sciences and Engineering, 17 (1), 165–171.
  • Başlık S (2008). Dinamik kentsel büyüme modeli lojistik regresyon ve cellular automata (İstanbul ve Lizbon örnekleri). Mimar Sinan Güzel Sanatlar Üniversitesi Fen Bilimleri Enstitüsü.
  • Batty M & Longley P (1994). Fractal cities: A Geometry of Form and Function. Academic Press Limited.
  • Batty M & Longley P A (1987). Urban shapes as fractals. Area, 19, 215–221.
  • Capozza D R & Helsley R W (1989). The fundamentals of land prices and urban growth. J. Urban Econ., 26, 295–306.
  • Clarke K C & Schweizer D M (1991). Measuring the fractal dimension of natural surfaces using a robust fractal estimator. Cartogr. Geogr. Inf. Syst., 18, 37–47.
  • Erdogan G & Cubukcu K M (2014). Explaining Fractal Dimension In Populous Cities. Eurau 2014 Composıte Cıtıes.
  • Fractalyse (2016). Fractalyse. www.fractalyse.org/en-doc-1.2_The_counting_methods.html
  • Frankhauser P (1990). Aspects fractals des structures urbaines. Espace Geographique, 19–20 (1), 45–69.
  • Frankhauser P (1992). Fractal properties of settlement structures. The First International Seminar on Structural Morphology.
  • Frankhauser P (1998). The fractal approach. A new tool for the spatial analysis of urban agglomerations. Population, 52 (4), 1005–1040.
  • Frankhauser P (2004). Comparing the morphology of urban patterns in Europe—A fractal approach. Eur. Cities Insights Outskirts Rep. COST Action, 10, 79–105.
  • Frankhauser P & Pumain D (2007). Fractals and Geography. In L. Sanders (Ed.), Models in Spatial Analysis, 281–300.
  • Frankhauser P & Tannier C (2005). A multi-scale morphological approach for delimiting urban areas. CUPUM 05 : Computers in Urban Planning and Urban Management, 9th Conference Organised by the CASA.
  • Goodchild M F (1980). Fractals and the accuracy of geographical measures. Journal of the International Association for Mathematical Geology, 12 (2), 85–98.
  • Guneroglu N, Acar C, Dihkan M, Karsli F & Guneroglu A (2013). Green corridors and fragmentation in South Eastern Black Sea coastal landscape. Ocean and Coastal Management, 83, 67–74.
  • IBM. (2013). IBM Kowledge Center. www.ibm.com/support/knowledgecenter/en/SSLVMB_22.0.0/com.ibm.spss.statistics.algorithms/alg_2step_cluster.htm.
  • Jaya V, Raghukanth S T G & Sonika M S (2014). Estimating fractal dimension of lineaments using box counting method for the Indian landmass. Geocarto International, 29(3), 314–331.
  • Jiang B & Anders B S (2016). A Fractal Perspective on Scale in Geography. ISPRS International Journal of Geo-Information, 5 (6).
  • Kaya H S & Bölen F (2006). Kentsel Mekan Organizasyonundakz Farklılıkların Fraktal Analiz Yöntemi ile Değerlendirilmesi. Journal of Istanbul Kültür University, 4, 153–172.
  • Kaya H S & Bölen F (2011). Kentsel dokudaki değişimin fraktal geometri yöntemiyle incelenmesi. İTÜ Dergisi/A Mimarlık, 10 (1), 39–50.
  • Landis J & Huang W (1995). Theoretical foundations and literature review. In Transit Investments, Real Estate Values, and Land Use Change: A Comparative Analysis of Five California Rail Transit Systems (pp. 13–26). UC Berkeley: Berkeley, CA, USA.
  • Ma R, Gu C, Pu Y & Ma X (2008). Mining the urban sprawl pattern: A case study on Sunan, China. Sensors, 8 (10), 6371–6395.
  • Mandelbrot B (1967). How Long Is the Coast of Britain ? Statistical Self-Similarity and Fractional Dimension Author ( s ): Benoit Mandelbrot Source : Science , New Series , Vol . 156 , No . 3775 ( May 5 , 1967 ), pp . 636-638 Published by : American Association for the Advanc. Science, 156 (3775), 636–638.
  • MIT (2015). MIT The Bayes Information Criterion (BIC). www-math.mit.edu/~rmd/650/bic.pdf
  • Nabiyev V V (2013). Algoritmalar. Seçkin Yayınevi.
  • Ozturk D (2017). Assessment of urban sprawl using Shannon’s entropy and fractal analysis: a case study of Atakum, Ilkadim and Canik (Samsun, Turkey). Journal of Environmental Engineering and Landscape Management, 25 (3), 264–276.
  • Pentland A P (1984). Fractal-Based Description of Natural Scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6 (6), 661–674.
  • Poudyal N C, Hodges D G, Tonn B & Cho S H (2009). Valuing diversity and spatial pattern of open space plots in urban neighborhoods. Forest Policy and Economics, 11(3), 194–201.
  • Purevtseren M, Tsegmid B, Indra M & Sugar M (2018). The fractal geometry of urban land use: The case of Ulaanbaatar City, Mongolia. Land, 7 (2), 1–14.
  • Shen G (2002). Fractal dimension and fractal growth of urbanized areas. International Journal of Geographical Information Science, 16(5), 419–437.
  • Terzi F & Kaya H S (2008). Analyzing Urban Sprawl Patterns Through Fractal Geometry: The Case of Istanbul Metropolitan Area. Working Papers Series, 144 (0), 0–18.
  • Thomas I, Frankhauser P & Biernacki C (2008). The morphology of built-up landscapes in Wallonia (Belgium): A classification using fractal indices. Landscape and Urban Planning, 84 (2), 99–115.
  • Thomas I, Frankhauser P, Frenay B, Verleysen M & Samos-Matisse S M (2010). Clustering patterns of urban built-up areas with curves of fractal scaling behaviour. Environment and Planning B: Planning and Design, 37 (5), 942–954. https://doi.org/10.1068/b36039
  • TÜİK. (2018). TÜİK. www.tuik.gov.tr
  • Wendt P F (1957). Theory of Urban Land Values. Land Economics, 33 (3), 228. 1
  • Zhang T, Ramakrishnan R & Livny M (1996). BIRCH: An Efficient Data Clustering Databases Method for Very Large. ACM Sigmod Record; ACM: New York, NY, USA, 25, 103–114.
There are 39 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Research Articles
Authors

İsmail Ercüment Ayazlı 0000-0003-0782-5366

Salim Boyraz This is me 0000-0003-0782-5366

Mehmet Aykut Başcı This is me 0000-0003-0782-5366

Emre Ulusu This is me 0000-0003-0782-5366

Publication Date December 28, 2020
Published in Issue Year 2020 Volume: 2 Issue: 2

Cite

APA Ayazlı, İ. E., Boyraz, S., Başcı, M. A., Ulusu, E. (2020). Kentleşmenin karmaşıklık düzeyinin belirlenmesi ve coğrafi dağılımının araştırılması. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 2(2), 57-63.

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