Check out the journal article about OSMnx. All figures in this article come from this journal article, which you can read/cite for more.
The heart of Allan Jacobs’ classic book on street-level urban form and design, Great Streets, features dozens of hand-drawn figure-ground diagrams in the style of Nolli maps. Each depicts one square mile of a city’s street network. Drawing these cities at the same scale provides a revealing spatial objectivity in visually comparing their street networks and urban forms.
We can recreate these visualizations automatically with Python and the OSMnx package, which I developed as part of my dissertation. With OSMnx we can download a street network from OpenStreetMap for anywhere in the world in just one line of code. Here are the square-mile diagrams of Portland, San Francisco, Irvine, and Rome created and plotted automatically by OSMnx:
The top row depicts the late 19th century orthogonal grids of Portland, Oregon and San Francisco, California. Portland’s famously compact walkable blocks are clearly visible but its grid is interrupted by the Interstate 405 which tore through the central city in the 1960s. In the bottom row, the business park in suburban Irvine, California demonstrates the coarse-grained, modernist, auto-centric urban form that characterized American urbanization in the latter half of the 20th century. In stark contrast, Rome has a fine-grained, complex, organic form evolved over millennia of self-organization and urban planning.
Remember these are all at the same scale: one square mile. Compare the block sizes and intersection density in Portland to those in Irvine. Compare the orthogonal grid in San Francisco and the modernist simplifications of Irvine to the complex mesh of pedestrian paths, passageways, and alleys comprising much of the circulation network in Rome.
Above, we see New York, Paris, Tunis, and Atlanta. Manhattan’s rectangular grid originates from the New York Commissioners’ Plan of 1811. You can see Broadway weaving diagonally across it. At the center of the Paris square mile lies the Arc de Triomphe, from which Baron Haussmann’s streets radiate outward, remnants of his massive demolition and renovation of 19th century Paris. At the center of the Tunis square mile lies its Medina, with a complex urban fabric that evolved over the middle ages. Finally, Atlanta is typical of many American downtowns: fairly coarse-grained, disconnected, and surrounded by freeways.
One final example: square miles of central Boston, Jumeirah circle in Dubai, suburban northeastern Sacramento, and Osaka, Japan. What can you tell about these neighborhoodsĀ from their street patterns?
To compare urban form in different kinds of places, these visualizations have depicted some downtowns, some business parks, and some suburban residential neighborhoods. These patterns also vary greatly within cities: Portland’s suburban east side looks very different than its downtown, and Sacramento’s grid-like downtown looks very different than its residential suburbs. These visualizations, rather, show us how different urbanization patterns and paradigms compare at the same scale.
Several more examples and all the code to reproduce these diagrams are in this notebook in OSMnx’s GitHub repo. You can adapt it to visualize any street network anywhere in the world. For more info, check out the paper about OSMnx. All the figures in this post come from this article, which you can read/cite.
46 replies on “Square-Mile Street Network Visualization”
[…] https://geoffboeing.com/2017/01/square-mile-street-network-visualization/ […]
Is that the densest, oldest part of Irvine? I don’t know it, but there are parts of that city that look much finer-grained than that. https://goo.gl/maps/AQmbLeXPcd62
It’s a business park in the western part of Irvine, near the airport. Most of Irvine comprises the loops-and-lollipops style of suburban form. This Irvine business park is more coarse-grained and more orthogonal, and useful to compare to other types of urban form.
This is very cool, but don’t you think controlling for land use is important? How can you compare an industrial development pattern to residential or downtown areas? The Irvine example isn’t apples to apples.
Hi Marta. Yes indeed, hence my paragraph toward the end of the article: “To compare urban form in different kinds of places, these visualizations have depicted some downtowns, some business parks, and some suburban residential neighborhoods. These patterns also vary greatly within cities: Portland’s suburban east side looks very different than its downtown, and Sacramento’s grid-like downtown looks very different than its residential suburbs. These visualizations, rather, show us how different urbanization patterns and paradigms compare at the same scale.”
hi gboeing
excellent work
how can you count the number cul-de-sacs?
thanks
See cell 4 in this example: https://github.com/gboeing/osmnx-examples/blob/v0.11/notebooks/06-example-osmnx-networkx.ipynb
And the documentation for the basic_stats() function: https://osmnx.readthedocs.io/en/stable/osmnx.html#osmnx.stats.basic_stats
Desperately want you to do Boston’s North End! Center, say on intersection of Hanover and Prince streets.
I added a new example that includes Boston’s north end.
Nice work!
Do you think it’s possible to modify/extend OSMnx such that it works on airport structures instead of street networks (see http://wiki.openstreetmap.org/wiki/Aeroways)?
One could then automatically create airport posters like these: https://shop.nomodesign.com/collections/airport-runway-series
Regards
Florian
Really nice work mate. I reckon it would have been fun to incorporate coding into your Urban-Planning(?) dissertation.
[…] 1.Ā City Street Grid Visualizations. Ā Streets are the skeletal structure of the city, and the network of streets–their width, spacing, number of intersections–defines the fabric of urban interaction. The University of California, Berkeley’s Geoff Boeing has created a series of same-scale diagrams of city street grids that allow an easy, intuitive comparison of different cities. Ā Each of the following blocks shows a single mile-square segment in the center of a large city. […]
Hi,
Found this really neat. Took your code and ran it on some cities in Chile: https://github.com/sidmitra/osmnx_playground/blob/master/01-chile-cities.ipynb
Sid, nice visualizations. The code to set road widths is at the bottom of his notebook linked above. Your visualizations would be easier to read – esp. Valparaiso. It’s just one more line of code.
Me encanta! My problem is I know nothing about coding though I would like to have two of these images of Toronto (area around first Canadian place) and Boston (area around Northeastern University)! I want to create a 3d printed version of these two cities/areas for an architectural installation. Can anyone help me out? Is there a video on how I could do this? Any help is greatly appreciated! Fantastic subject for a dissertation. Congrats!
Cool!
[…] Staedter (Seeker) explained the maps of Geoff Boeing. He calls his visualization tool OSMnx (OSM + NetworkX). The tool can create the physical characteristics of the streets of each city in a […]
Very nice Geoff!
[…] pavadinimus ir ÄÆsivaizduodamas miesto gyvenimÄ pagrindinÄse sankryžose. Tad RÅ«tai užrodžius naujÄ Pitono modulÄÆ OSMnx, kuris leidžia iÅ” openstreetmaps duomenų nupieÅ”ti labai estetiÅ”kÄ Allan Jacob knygos āGreat […]
[…] Boeing at UC-Berkeley created simple 1-square mile maps of the street grids of global cities. Visual poetry. Must […]
[…] As part of his dissertation, Geoff Boeing generated these maps that show one square mile of road network in select cities. […]
Thank you!
This is a useful way to contemplate why cities work, or don’t. Wondering if you’ve developed understanding of how these organic vs gridlike forms have affected humans.
London, anybody?
The Square Mile-ish, and Oxford Circus-centred.
https://twitter.com/ikirker/status/817018027006918656
I love this! How about Istanbul?! Oh, and do you have this in a large print for purchase?
I’m totally new to data visualization, but I was wondering if there was some way to show a USGS topographical behind the streets; perhaps to show how geographical features influence (sub)urban grids. I think the topo lines would have to be faint in order not to interfere with the most important message of the visual. But, strong enough for the viewer who wants to extract more information.
Yep, you could just load and plot a topo shapefile as another layer.
[…] a ddefnyddir yn aml i ddisgrifio cynefin rhywun yw ‘milltir sgwĆ¢r’. Yn ol Geoff Boeing, fe wnaeth Allan Jacobs greu mapiau milltir sgwĆ¢r o ddinasoedd gwahanol fel modd o gymharu eu […]
[…] Geoff Boeing, aĀ Ph.D. candidate in urban planning at UC Berkeley, put together a collection of monochrome representations of some of the world’s most iconic cities, each of which showing a square mile of the city in question. They allow you to compare the layout of the streets, all of which can be explained by a bit of historical and architectural exploration. Ā Like for example, why does Broadway just slice through town with no cares given? Turns out it follows a Wickquasgeck Trail, which was carved into the brush of Manhattan by its Native American inhabitants, prior to European settlement. […]
[…] You can read more by Boeing and/or start using OSMnx here. […]
Nice work!
[…] Street patterns. […]
[…] Geoff Boeing, a PhD student at University of California, Berkeley, developed the visualizations as part of his dissertation. […]
[…] Geoff Boeing, a PhD student at University of California, Berkeley, developed the visualizations as part of his dissertation. […]
Interesting! I’m from Sacramento, curious about what area was selected.
That’s in Arden-Arcade. You can see the exact coordinates here: https://github.com/gboeing/osmnx/blob/master/examples/09-example-figure-ground.ipynb
[…] Geoff Boeing, a PhD student at University of California, Berkeley, developed the visualizations as part of his dissertation. […]
Neat post. I think it’s worthy to note that in that particular square mile of Boston, I-93 in fact runs underground (and underwater), beneath downtown and the historic North End. Maps can be deceiving!
[…] G. (2017) āSquare-Mile Street Network Visualizationā (WWW) (https://geoffboeing.com/2017/01/square-mile-street-network-visualization; accessed […]
[…] devonzuegel Uncategorized January 31, 2018January 31, 2018 1 Minute Add Discussion Street networks in Osaka, Kyoto, and Tokyo are highly connected. The streets are narrow, and the blocks are short, which feels more human-scale and creates more opportunity for diversity. Pedestrians feel comfortable in these dense networks, which encourages walking and biking. This Kyoto side street would barely be enough space between buildings to conform to most American zoning codes, let alone to count as a street. Short blocks break the social isolation of wide, long streets. Pedestrians are more likely to stop by a shop as they walk past than if they were driving, and by permitting alternative travel routes and shortening the travel distance from nearby places, short blocks open greater access to stores and services. This mid-sized street in Japan would be a small alley in an American city. Cars go both directions, so they are careful. This makes pedestrians and cyclists comfortable to walk in the middle of the street (like you can seen in the picture above!). White lines delineate the center from the sides, which helps separate traffic and pedestrians when need be, but people are as if not more welcome than cars here. It’s useful to contrast these human-scale streets with their American counterparts. San Francisco’s South of Market (SoMa) neighborhood is an interesting case. The district’s legacy as an industrial zone left it with wide streets and longer blocks, and the effect is that pedestrians feel like second-class citizens. Cyclists are The 280 and 101 freeways furher emphasize this isolation by slicing right through the neighborhood. It’s no coincidence that the SF neighborhoods people most often describe as “charming” are the ones whose with smaller streets and shorter blocks. These tend to be the older ones north of Market St like Hayes Valley, Lower Pacific Heights, and the Castro. […]
[…] nouvel outil de visualisation de donnĆ©es prend un instantanĆ© d’un kilomĆØtre de toutes les villes et le convertit en un schĆ©ma […]
Geoff, beautiful work!
Is their a tutorial to export to SVG…was not able to locate that information.
You just pass the argument: file_format=’svg’ https://osmnx.readthedocs.io/en/stable/osmnx.html#osmnx.plot.plot_figure_ground
Hi Geoff, awesome work! what does the width of link represent in this plot? and is it possible to change the key attribute e.g. to length?
Great fun with a great tool! When adding the buildings I am loosing the square constraint of the axes, is there a quick way of fixing that? Thanks
[…] Figure 2: Birdās eye view of different cities globally (Geff Boeing 2017) […]