Volunteered Geographic Information for planning: the case for „emergent” cycle lanes in cities
Stefano Picascia, Antonello Romano
University of Siena
Sensors embedded in everyday devices produce a wealth of geographical information, contributed implicitly in particular by those who track their walking and cycling activities. Such geographical data have several potentially groundbreaking applications in the field of urban planning.
In this work we present an experiment based on the combination of user generated cycling data with PGIS sources and official open data, to (1) assess the effectiveness of cycle networks in cities around the world, (2) suggest potential extensions to existing networks and (3) offer guidance in designing cycle networks where they do not exist.
We show how VGI data – in the form of large datasets of cycle trips contributed through the STRAVA app – can be used very effectively to make sense of cycling patterns in cities, and therefore can be helpful in grounding the design of a cycle network in unbiased (or only slightly biased), user-centered evidence – i.e. the existing preferences and habits of cyclists.
In particular, we show how VGI data can highlight criticalities in existing cycle networks, such as Paris’s, and suggest ways for local authorities to address them.
In certain areas of cities like Chicago, where a cycling network has never been implemented, we show that a sort of „implicit”, spontaneous cycling network does, in fact, exist – emerging from the recurring routes that cyclists take. We argue that these routes could form the basis for a data-driven design of a cycle lane network.