Urban Spatial Order: Street Network Orientation, Configuration, and Entropy
20 Pages Posted: 23 Aug 2018 Last revised: 10 Feb 2019
Date Written: February 1, 2019
Street networks may be planned according to clear organizing principles or they may evolve organically through accretion, but their configurations and orientations help define a city's spatial logic and order. Measures of entropy can reveal a city's streets' order and disorder. Past studies have explored individual cases of orientation and entropy, but little is known about broader patterns and trends worldwide. This study examines street network orientation, configuration, and entropy in 100 cities around the world using OpenStreetMap data and OSMnx. It measures the entropy of street bearings in weighted and unweighted network models, along with each city's typical street segment length, average circuity, average node degree, and the network's proportions of four-way intersections and dead-ends. It also develops a new indicator of orientation-order that quantifies how a city's street network follows the geometric ordering logic of a single grid. It finds significant statistical relationships between a city's orientation entropy and other indicators of spatial order, including street circuity and measures of connectedness. These indicators, taken in concert, help reveal the extent and nuance of the grid. On average, the US/Canada study sites are far more grid-like than those elsewhere, exhibiting less entropy and circuity. These methods demonstrate automatic, scalable, reproducible tools to empirically measure and visualize city spatial order, illustrating complex urban transportation system patterns and configurations around the world.
Keywords: City Planning, Urban Form, Urban Design, Urban Morphology, OpenStreetMap, Python, Data Science, Gis, Geospatial, Spatial Analysis, Entropy, Orientation, Configuration, Network Analysis, Street Networks, Graph Theory, Transportation, Transportation Planning, Data Visualization
JEL Classification: R00, R40
Suggested Citation: Suggested Citation