Universal patterns of intra-urban morphology: Defining a global typology of the urban fabric using unsupervised clustering

The physical dimension of cities and its spatial patterns play a crucial role in shaping society and urban dynamics. Understanding the complexity of urban systems requires a detailed assessment of their physical structure. Urban geography has long focused on framing typologies to represent common patterns in the urban fabric using various methodologies. However, only recent advancements in computational methods and global land cover data have enabled to comprehensively identify typologies of urban patterns at the city scale through new unsupervised approaches. Nevertheless, typologies of finer-grained patterns at intra-urban scale have not yet been explored comprehensively at a global level. In this paper, building upon these advances, we explore the intra-urban patterns of more than 1500 cities across the globe. We rely on a Local Climate Zone land cover classification to represent the multidimensional variabilities of intra-urban morphology. Adapting a deep learning based unsupervised clustering approach, we find a typology of 138 intra-urban patterns. Analyzing the results of this data-driven approach, we prove that each pattern identified is unique, i.e. statistically different, in its composition and configuration. With this study summarizing the global diversity of the urban fabric, we reveal that any city of the world can be described as a specific assemblage of a fraction of these 138 universal patterns. These universal patterns reveal a predominance at a global scale of built-up forms of low density in the intra-urban fabric.