Entropy and hierarchical clustering: characterising the morphology of the urban fabric in different spatial cultures

TL;DR

This paper introduces a method to estimate Shannon entropy of urban spatial configurations, enabling classification of city morphologies and exploring cultural influences on urban form.

Contribution

It presents a novel entropy-based approach for analyzing and classifying urban morphology across different cultural and regional contexts.

Findings

Entropy-based metrics can accurately classify urban forms

Hierarchical clustering reveals cultural and regional patterns

Urban morphology reflects cultural identities and historical processes

Abstract

In this work, we develop a general method for estimating the Shannon entropy of a bidimensional sequence based on the extrapolation of block entropies. We apply this method to analyse the spatial configurations of cities of different cultures and regions of the world. Findings suggest that this approach can identify similarities between cities, generating accurate results for recognising and classifying different urban morphologies. The hierarchical clustering analysis based on this metric also opens up new questions about the possibility that urban form can embody characteristics related to different cultural identities, historical processes and geographical regions.