New quests in the rural-urban dilemma: Clustering of settlement units using the K-means algorithm Kır-kent ikileminde yeni arayışlar: K-means algoritması ile yerleşim birimlerinin kümelendirilmesi

BAYDAN E., YENİGÜL S. B., GÜREL Z. A.

Journal of the Faculty of Engineering and Architecture of Gazi University, cilt.40, sa.3, ss.1467-1478, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 40 Sayı: 3
  • Basım Tarihi: 2025
  • Doi Numarası: 10.17341/gazimmfd.1417659
  • Dergi Adı: Journal of the Faculty of Engineering and Architecture of Gazi University
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Art Source, Compendex, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.1467-1478
  • Anahtar Kelimeler: artificial intelligence, clustering, K-means, machine learning, rural-urban distinction
  • Gazi Üniversitesi Adresli: Evet

Özet

This study aims to analyze and characterize the settlement units (neighborhoods) of Ankara province within the framework of the rural-urban dichotomy. In this context, settlement units have been subjected to clustering using the K-means algorithm. In the study, models obtained through the K-means algorithm were compared using two different classification methods based on TÜİK (Turkish Statistical Institute) and Ankara Metropolitan Municipality council decisions. According to the artificial intelligence model developed using the K-means algorithm, 9% of the settlements (1432 units) in Ankara province are clustered as densely rural (cluster-2), 11% as densely urban (cluster-3), 38% as urban with rural interaction (cluster-0), and 42% as rural with urban interaction (cluster-1). The results indicate that the K-means algorithm can be useful in evaluating the effects of various strategies and policies in planning processes. However, it is essential to consider the specific parameter dependencies and limitations of this model. The study is envisioned to provide a more detailed perspective on the distinction between urban and rural areas, aiming to offer a fresh understanding in areas such as regional planning, resource management, and public service delivery.