Category: Mashups

Steve, here in the lab at CASA, has adapted his popular Tweet-O-Meter display of Twitter activity in cities around the world, for my bike hire maps, to create Bike-O-Meter. Now, on a single screen, you can see lots of Google-powered gauges, showing how busy the bike share schemes around the world are right now. Some show massive spikes during their rush hours, while others are more popular at weekends. Most dials will move every two minutes, a few (the Velib ones) update every 10 or 20 minutes.

At the time of writing, the bike share schemes of the Spanish cities, particularly Barcelona, Girona and Valencia, are the ones being most actively used. Spanish rush-hours at lunchtimes seem generally to be as big as the morning/evening ones! Biking home for the siesta?

There’s a second mode, accessed here, that shows how unbalanced the schemes are – high values indicate that a lot of the bikes are concentrated in one part of the city, and there’s a lot of empty docking stations in another part. The metric is the percentage of bikes that would need to be moved to balance out the docking stations across the city.

Thanks Steve for making this awesome visualisation!

I’ve made a couple of enhancements to my live London cycle hire map – you can now choose from several colour sets. A couple of the sets also change the circle sizes, so that these correspond to the number of bikes (or spaces) rather than the dock size. This means the circles grow or shrink as the bikes get used, rather than remaining static as before.

Using value-based colour ramps and/or circle size changes, rather than the standard hue-based colour ramp, are are a more “correct” way to show quantitative data graphics such as the hire map, as the data values aren’t distorted by “colour bias” (where a particular hue has more of an impact to the viewer).

I’ve also added a couple of panels to show how busy the hire scheme currently is, and how this compares to the same time 24 hours ago, and added a ticker which lists changes as they happen (e.g. docks becoming full or emptying quickly), in the style of the old BBC Grandstand vidi-printer.

Very few people have been using the bikes to commute home this evening (and yesterday evening) as it’s been raining a lot here in London! We have a weather station here at CASA, with historical data, so it should be possible to quantify the relationship between how hard it’s raining and what proportion of people decide to try another way to get home.

[A final word on my cycle hire visualisation – which you can see here.]

James has posted a video showing how the colours (i.e. bike usage patterns) changed during Wednesday – a typical day with good weather (so high usage) and sharply defined rush hours. The video shows one hour every second and starts at midnight (so look out for the main changes at 9s and 18s in.)

Another quirk is a characteristic move from red to purple of several stations overnight (i.e. in the first 5s of the video) in the northern edge of the zone, i.e. around Angel, travelling from east to west. A redistribution vehicle at work?

Today’s evening rush hour is showing quite a different pattern – a much less pronounced spike in usage, spread out over a longer time interval. This is probably because of the rain showers this afternoon and correspondingly damp roads, but possibly because Thursdays are traditionally team drinks nights in the City for many people, and so people will either be delaying the journey home, or deciding not to take the bike at all after a few drinks (not a bad idea really.) Certainly I’ve noticed a large difference in the numbers of people spilling out of the traditional City drinking dens on Thursday (and to a lesser extent Friday) evenings, compared with Monday-Wednesday.

Aidan’s sparklines, showing yesterday’s data as grey lines and today’s in orange, show this lag effect strikingly.

Neal Lathia, a research fellow here at UCL alerted me to a study carried out on usage patterns of a very similar scheme in Barcelona – even the dock numbers and scheme shape match London – clustering and categorising docking stations based on their usage patterns. Their method of data capture is also very similar to what I’m doing and the resulting dataset should lend itself to an equivalent categorisation in London. Things will only get more interesting when “casual” (i.e. non-registered) users get access to the scheme, which may happen next month, and new user types, such as foreign tourists, get involved, and the seasons (and weather) will also probably play a part, as different user types have different levels of willingness to use the system based on daily conditions.

The BBC’s Tom Edwards has an interview with the operators of the scheme, which includes at one point a screenshot of the internal (Google-maps based) map used by them to see what docking points are on their way to becoming full or empty.

I’ve created a visualisation of how the TFL Cycle Hire scheme in London is being used – the so-called “Boris Bikes”. Around 4000 bikes have been placed in 400 cycle parking stands in the centre of the city, and people have been using them to get from A-B.

Some distinctive if not entirely surprising patterns have appeared already – with heavy usage (~10% of total bikes out on the streets) during the rush-hours, which occur in a strikingly small time interval – a narrow, sharp dip appearing only between 5:30pm to 6pm. Usage is much less in rainy weather, such as has happened today, and weekend use is both lower, and quite different in “shape”. During weekday days, the City tends to have a lot of the bikes, while in the evening, the bikes end up at the cycle parking stands near the big terminal train stations and in Pimlico in the south-west of the area – probably the biggest residential area covered by the scheme, and also a popular place for city workers to live…

10am Tuesday: Straight after a sunny morning rush-hour, before redistribution kicks in – many of the central stands are now completely full of bikes (red with yellow borders.)

8pm Tuesday: A typical evening pattern – the bikes are on the edge, and at the terminal stations, particularly around Waterloo and King’s Cross, while the centre is short of bikes…

The visualisation consists of coloured dots, which change from blue to red as each stand fills up with docked bikes. A purple dot indicates a half-full stand. The size of the dots corresponds to the total capacity of the stand.

You can click on a stand’s dot to see information about its current status, as well as its use over the last 24 hours, represented as a minimalistic graph. A graph of overall usage can also be viewed. Both get updated as the new data comes in.

The data comes from TFL’s own map of the stands in central London, and is updated at source typically every six minutes – my own visualisation updates every two minutes, so you should never be more than ten minutes out of date, looking at the map.

The background is a bespoke render of central London, from OpenStreetMap data.

See it here.

Here’s how the total number of available bikes has fluctuated, since Friday morning (click for larger version):

[Update: Some articles about the visualisation – Telegraph, Londonist, Road.cc, Real Cycling, Bikeradar]