Research Article

Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example

Volume: 9 Number: 1 July 30, 2024
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Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example

Abstract

In this study, the effect of urban sprawl on land change in Istanbul was examined using Geographic Information System (GIS) technologies and the CORINE Land Cover (CLC) data set produced for the years 1990-2018 and population information. According to this; It has been determined that urban sprawl in the study area has increased due to population growth, especially industrial units, city structures, mines and construction sites have increased by approximately 9%, while maquis areas, arable, mixed agricultural areas and forest areas have decreased by 9%. According to the K-means application, similarities in the districts were revealed between 1990 and 2018. According to the results obtained, it was determined that the districts that were in clusters with similar characteristics in the 1990s changed over time and were located in different clusters. As a result, it is predicted in the study that urban sprawl will increase further due to population growth in Istanbul.

Keywords

Urbanization, urban development, natural areas, conservation, Istanbul

References

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APA
Bozkurt, S. G., & Kuşak, L. (2024). Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example. Journal of Architectural Sciences and Applications, 9(1), 69-86. https://doi.org/10.30785/mbud.1333925
AMA
1.Bozkurt SG, Kuşak L. Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example. JASA. 2024;9(1):69-86. doi:10.30785/mbud.1333925
Chicago
Bozkurt, Selvinaz Gülçin, and Lütfiye Kuşak. 2024. “Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example”. Journal of Architectural Sciences and Applications 9 (1): 69-86. https://doi.org/10.30785/mbud.1333925.
EndNote
Bozkurt SG, Kuşak L (July 1, 2024) Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example. Journal of Architectural Sciences and Applications 9 1 69–86.
IEEE
[1]S. G. Bozkurt and L. Kuşak, “Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example”, JASA, vol. 9, no. 1, pp. 69–86, July 2024, doi: 10.30785/mbud.1333925.
ISNAD
Bozkurt, Selvinaz Gülçin - Kuşak, Lütfiye. “Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example”. Journal of Architectural Sciences and Applications 9/1 (July 1, 2024): 69-86. https://doi.org/10.30785/mbud.1333925.
JAMA
1.Bozkurt SG, Kuşak L. Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example. JASA. 2024;9:69–86.
MLA
Bozkurt, Selvinaz Gülçin, and Lütfiye Kuşak. “Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example”. Journal of Architectural Sciences and Applications, vol. 9, no. 1, July 2024, pp. 69-86, doi:10.30785/mbud.1333925.
Vancouver
1.Selvinaz Gülçin Bozkurt, Lütfiye Kuşak. Detection of Population Density, LULC Variation and Cross-Regional Similarities Using K-Means Clustering Algorithm in Istanbul Example. JASA. 2024 Jul. 1;9(1):69-86. doi:10.30785/mbud.1333925