The recent explosion in bike sharing is one of the biggest urban stories of the last few years. And there’s a rich history behind it, going all the way back to the 1960s — check out this fantastic visual history of bike sharing from Sarah Goodyear.
But have no fear! Visual designers Till Nagel and Christopher Pietsch, of Potsdam, Germany, have answered the call. (Hat tip to Max Galka at the Guardian.)
In an interactive installation called cf. city flows, hosted by Potsdam’s Urban Complexity Lab, they used GPS data from bike-share systems in New York City, London, and Berlin to create visual representations of bike-share use.
Just look at them.
Nagel and Pietsch did a lot of interesting technical work to create these elegant visualizations; check out the cf. city flows website for more.
Substituting intelligence for stuff (a recurring theme)
The designers chose these three cities because there is GPS data available on their bike-share systems. Individual bikes and bike trips are not tracked via GPS — that would be a little creepy — but these cities track when and where bikes are checked in and out. That enables the designers to represent individual trips, traffic at specific stations, and at a larger level, the flow of total bike-share traffic over time.
Taking raw information and representing in a way that can be understood intuitively is an increasingly vital skill these days. In this case, it can empower the folks who plan and manage bike sharing systems. They can use the visual data to target resources at particular locations or times of day, loosen bottlenecks, and more closely match supply and demand.
It’s all part of a larger trend toward smarter cities. GPS and sensors are becoming more and more ubiquitous in city infrastructure, getting cheaper and more accurate along the way. There will be more and more information like this available to city planners, who can use it to better anticipate the needs of city dwellers, and to the public, who can hack and manipulate it in all sorts of ways we can’t anticipate now.
As I keep saying, the clean-energy transition is going to be about software as much as hardware. The glut of information now available, along with incredibly cheap (and getting cheaper) computing power, enables us to do far more with the resources already available — to substitute intelligence for stuff.
As these visualizations show, smarter can be beautiful.