Articles | Volume 5
30 May 2024
 | 30 May 2024

A Spacematrix and Clustering Approach to understanding the morphology of Singapore’s Housing Development Board (HDB) Estates

Cai Wu, Jiong Wang, Mingshu Wang, and Menno-Jan Kraak

Keywords: urban morphology, urban planning, urban pattern, spacematrix, machine learning

Abstract. Urban morphology profoundly influences city planning and experiences significant transformations as cities evolve. This paper investigates paradigm shifts in block-level planning through a case study of Singapore, a city celebrated for its precision in urban planning and swift transformation. Integrating urban morphology theories with empirical data, we explore Singapore’s block-level urban form across various stages of development. Utilising a Spacematrix approach alongside a clustering analysis of urban blocks, we categorise Singapore’s towns into four distinct clusters: Suburban, Balanced Mix, Dense Urban, and Vertical Growth, each reflecting unique density patterns and building forms. This clustering reveals how Singapore’s planning ideologies have transitioned from maximising space utilisation to prioritising sustainability and quality of living. This signifies a paradigm shift towards a comprehensive and inclusive urban design ethos. The paper contributes to the urban planning discourse by underscoring the technological advancements, especially with merging spatial data and GIS, in shaping modern urban analytics and planning. The insights from the clustering analysis enhance our understanding of Singapore’s exceptional urban path and offer valuable perspectives for other metropolises navigating the complexities of urban expansion and sustainability.