A diffusion-based approach to obtaining the borders of urban areas

TL;DR

This paper introduces a diffusion-based method for automatically delineating urban area borders from a single seed point, utilizing street network data to characterize urban geometry and topology.

Contribution

The paper presents a novel, straightforward approach that combines diffusion processes with street network analysis to accurately define urban boundaries.

Findings

Successfully characterized 21 urban regions from 8 countries.

Demonstrated the method's ability to analyze urban geometry using lacunarity.

Analyzed street topology through betweenness centrality and street classification.

Abstract

The access to an ever increasing amount of information in the modern world gave rise to the development of many quantitative indicators about urban regions in the globe. Therefore, there is a growing need for a precise definition of how to delimit urban regions, so as to allow proper respective characterization and modeling. Here we present a straightforward methodology to automatically detect urban region borders around a single seed point. The method is based on a diffusion process having street crossings and terminations as source points. We exemplify the potential of the methodology by characterizing the geometry and topology of 21 urban regions obtained from 8 distinct countries. The geometry is studied by employing the lacunarity measurement, which is associated to the regularity of holes contained in a pattern. The topology is analyzed by associating the betweenness centrality of the streets with their respective class, such as motorway or residential, obtained from a database.