Hypergraphs and City Street Networks

TL;DR

This paper introduces two algorithms to identify streets in city networks and demonstrates that street lengths scale logarithmically, suggesting a city’s spatial organization follows a pattern of extension and division.

Contribution

It presents novel algorithms for extracting street structures from city graphs and reveals a logarithmic scaling law for street lengths.

Findings

Street lengths scale logarithmically

Algorithms effectively recover street structures

City spatial organization follows a pattern of extension and division

Abstract

The map of a city's streets constitutes a particular case of spatial complex network. However a city is not limited to its topology: it is above all a geometrical object whose particularity is to organize into short and long axes called streets. In this article we present and discuss two algorithms aiming at recovering the notion of street from a graph representation of a city. Then we show that the length of the so-called streets scales logarithmically. This phenomenon leads to assume that a city is shaped into a logic of extension and division of space.