This past Tuesday marked the 111th anniversary of the New York City Subway, an iconic transport system which to-date has the most active stations of any underground system in the world. Subways operate in over 55 countries globally, throughout a growing collection of 150-some cities; and the art of mapping subterranean transit continues to fascinate information designers and commuters alike.
This past week, Cooper Union hosted a sold-out event called “The Subway Map: The Last 50 Years, The Next 50 Years” for a packed crowd of New Yorkers, and in honor of this, we’ve assembled a quick collection of some of the most interesting subway maps in CartoDB, along with a little tutorial on using subway data in your own maps.
The New York City Subway lines are available in CartoDB’s Common Data Library, available to all users. You can also check out Steven Romalewski’s datasets of MTA data, and otherwise check out OKFN’s Transit data dashboard, for a collection of all available transit data by city. You can also help “groom” the datasets by submitting changes for versioning or recommendations for review.
You can also fork these public datasets in various formats on CartoDB:
Many members of our community have made pretty clever maps with ridership data.
Many users have built functional maps of NYC subway design. Like this one featuring subway entrances and lines in NYC.
Or this one featuring the real-time repair status of MTA lines.
SUBWAY DESERTS Sometimes the absence of transport is information nearly as critical as its presence. Chris Whong mapped a lack of access using buffers around subways to showcase transportation “deserts” in his map of New York City.
Sometimes the micro-economies that subway access can highlight become topics for some pretty awesome maps, like this one overlaying average income on a distance map to the NYC subways.
Beyond mapping the lines and stops, you might also be interested in the human impact of these transit systems, on integrating [ridership data into your study of subways]. Below is an example of a Torque map that shows ridership entry data for rail stations in Chicago. The oscillations in station-point size reflect the number of people entering a station on any particular day, with a noticeable dip on the weekends. The data took some munging, but you can find subway ridership data in many city open data portals.
Thanks for reading, and happy subway mapping!
This post was written by Liveli, our master reseller in the Asia Pacific region. –Use Cases
Site Selection, Relocation, and Consolidation are often referenced as the defacto use cases of Location Intelligence, particularly in verticals such as Retail & Real Es...Use Cases
Given the large number of open source spatial analysis libraries available today it can often be difficult to understand how best to combine the strengths of each tool - es...Use Cases
Please fill out the below form and we'll be in touch real soon.