Kentleşmenin karmaşıklık düzeyinin belirlenmesi ve coğrafi dağılımının araştırılması

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.

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

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.

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