In an experiment that attempts to capture urban movement, Till Nagel and Christopher Pietsch, two researchers at the Urban Complexity Lab in Potsdam, Germany, developed a comparative visualization of urban bike sharing schemes across three cities. Their interactive installation, titled cf. city flows, compares urban mobility flows on shared bikes on three high-resolution screens, comparing urban movement in Berlin, New York City and London.
With bike-sharing schemes in more than 700 cities in 50 countries, and with more cities encouraging commuters to take to two-wheels, there is a greater need to understand where – and when – people cycle. In cf. city flows, Nagel and Pietsch extracted data from bike-sharing systems to visualize different aspects of bike-sharing mobility. By combining established mapping and visualization techniques with an aesthetic framework, cf. city flows presents an animated representation of urban mobility. “With our visualizations we want to understand the pulse of urban mobility and create portraits of a city defined by its transient dynamics,” says their website.
Although the team did not have access to real-time GPS route information (none of the bike systems provide GPS tracked information), they did have access to the start and end destinations of the bicycles. The data for London’s Santander Cycles was acquired from Transport for London‘s website and the data for New York, from Citi Bike‘s website, while Call a Bike Berlin’s data was available via Berlin Open Data.
cf. city flows includes three different viewing modes. The citywide view shows an aggregate of all bike-sharing trips within a specific time frame in a city on an animated map, with bike trips on a given day displayed as thinner paths; trails visualize the bike trips at a selected time, rendered in what the team calls “firefly style.”
The station view shows trips to and from a selected station in a city, color-coding incoming (green) and outgoing (orange) trips. Color-coding allowed the team to observe spatiotemporal patterns in London, for example, which showed a large number of trips beginning at the City’s central Waterloo Station in the mornings, indicating that commuters arriving by train used shared bicycles as a last mile fulfillment on their way to work.
Finally, the small-multiples view provides more detailed information by separating incoming and outgoing trips to and from selected stations, as well as separating morning and evening trips into different boxes; incoming trips are green while outgoing trips are orange, and morning trips are displayed on the left while afternoon trips are displayed on the right. The view allows visitors to see the urban fingerprint of three different stations, as well as to see spatiotemporal mobility patterns.
By aligning bike movements with actual roads, the team is able to compare the usage of urban infrastructure. A separate dashboard shows details about each city’s bike-sharing system, including information about the total number of stations, bikes, trips and morning and evening trips in each city.
Visitors to the exhibition could see spatiothermal patterns in the different cities; for example, visitors could easily see the barriers between Middle Manhattan and Central Park in New York, as well as the separation of Berlin’s inner city area. Street layouts were also more visible, with New York’s grid layout contrasting sharply with the more organically-developed layouts of Berlin and London.
Another notable difference was the small number of journeys in Berlin (less than 2,000) compared by London and New York, which each had about 35,000 trips. The team attributed this to the usage of Berlin’s bike-sharing by tourists and leisure cyclers rather than by Berliners, who have a strong cycling culture and mostly own their bikes.