Optimal design of urban structure resulting from merging several neighboring villages with spatial clustering algorithms

In many rural regions, the spatial dispersion of settlements poses a significant challenge to the development of infrastructure, services, and cultural coherence. Purposeful merging of geographically adjacent villages into a unified urban structure creates an opportunity to regenerate the area while preserving local identity and enabling sustainable growth. This study proposes a computational approach to design the optimal structure of such a merger using spatial clustering algorithms. The proposed model uses geographic and functional attributes (e.g., coordinates, accessibility, and land use) to cluster villages and suggest an initial layout for a combined village-city, referred to as “Shahroosta”. Algorithms such as K-Means and DBSCAN are discussed, along with methods for selecting the optimal number of clusters (e.g., Elbow method, Silhouette score). This approach aims to bridge spatial data analysis with urban design and regional development. At this stage, the article focuses on the conceptual model and methodology, with practical implementation reserved for future phases.

کلیدواژه ها:

Shahroosta ، Spatial Clustering ، K-Means ، GIS ، Village Integration