An elastic urban morpho-blocks (EUM) modeling method for urban building morphological analysis and feature clustering

Abstract

Rapid urbanization on a global scale has shown temporal and spatial complexity in urban morphology. Urban planners, searching for effective analytical tools to understand changes in urban form and its relationship with other planning-related issues, often face two challenges – computational complexity derived from over-complicated patterns of modern cities, and determining a consistent analytical scale for spatio-temporal comparison across blocks and cities. This study first proposed the elastic urban morpho-blocks (EUM) method, which introduces EUM as a new analytical unit, which is scalable and flexible for efficient and automated morphology feature extraction and analysis. The method was then examined through a demonstration of the Atlanta city with the real-world dataset and further applied to eight US cities. This paper shows that, with the EUM cluster method, urban planners can effectively and efficiently identify and analyze the morphological features of self-defined block clusters for their planning purposes.