Capital Bikeshare, the bike sharing system for Washington DC and Arlington, recently released the data on their first 1.3 million journeys. Boston’s Hubway bike sharing system also released journey data for around 5000 journeys across an October weekend, as part of a visualisation competition. Both these data releases sit alongside London’s Barclays Cycle Hire scheme, which also released data on around 3.2 million journeys made during the first part of last year.
Taking together all these data sets, I’ve used Routino and OpenStreetMap data to suggest likely routes taken for each recorded journey. This same set of data was used for Martin Zaltz Austwick’s excellent animation of bikes going around London streets. I’ve then built another set of data, an node/edge list, showing how many bike sharing bikes have probably travelled along each section of road. Finally, I’ve used node/edge visualiser Gephi and its Geo Layout plugin to visualise the sets of edges. The resulting maps here are presented below without embellishment, contextual information, scale or legend (for which I apologise – unfortunately this isn’t my current primary work focus so my time on it is restricted.)
For the two American schemes featured here, I have set the Routino profiler to not use trunk roads. Unlike most UK trunk roads, American trunk roads (“freeways”?) appear to be almost as big as our motorways, and I expect you wouldn’t find bikes on them. Unfortunately there are some gaps in the Washington DC data, which does show some cycle-lane bridges alongside such freeways, but these aren’t always connected to roads at either end or to other parts of the cycle network, so my router doesn’t discover them. This means that only a few crossings between Virginia and Washington DC are shown, whereas actually more direct ones are likely to be also in use. The profile also over-rewards cycleways – yes these are popular but probably not quite as popular as the distinctive one in the centre of Washington DC (15th Street North West) showing up as a very fat red line, suggests. The highlighting of other errors in the comments on this post is welcomed, I may optimise the profiler (or even edit OpenStreetMap a bit, if appropriate) and have another shot.