Categories
Urban

Urban Street Network Orientation

My new article, Urban Spatial Order: Street Network Orientation, Configuration, and Entropy, has just been published in one of my favorite journals: Applied Network Science (download free PDF). This study explores the spatial signatures of urban evolution and central planning. It examines street network orientation, connectivity, granularity, and entropy in 100 cities around the world using OpenStreetMap data and OSMnx for modeling and visualization:

City street network grid orientations, order, disorder, entropy, rose plot, polar histogram made with Python, OSMnx, OpenStreetMap, matplotlib.

So, who’s got a grid and who doesn’t? Each of the cities above is represented by a polar histogram (aka rose diagram) depicting how its streets orient. Each bar’s direction represents the compass bearings of the streets (in that histogram bin) and its length represents the relative frequency of streets with those bearings. The cities above are in alphabetical order. Here they are again, re-sorted from most-ordered/gridded city (Chicago) to most-disordered (Charlotte):

Categories
Planning

City Street Orientations around the World

City street network grid orientations, order, disorder, entropy, rose plot, polar histogram made with Python, OSMnx, OpenStreetMap, matplotlib.This post is adapted from this research paper that you can read/cite for more info. It analyzes and visualizes 100 cities around the world.

By popular request, this is a quick follow-up to this post comparing the orientation of streets in 25 US cities using Python and OSMnx. Here are 25 more cities around the world:

City street network grid orientations, rose plot, polar histogram made with Python, OSMnx, OpenStreetMap, matplotlib. Bangkok, Barcelona, Beijing, Budapest, Cairo, Delhi, Dubai, Glasgow, Hong Kong, Lagos, London, Madrid, Melbourne, Mexico City, Moscow, Mumbai, Munich, Paris, Rio de Janeiro, Rome, Seoul, Sydney, Tehran, Toronto, Warsaw, Tokyo, Berlin, Venice