Visualising Bike Share (#geomob 21 October 2010)


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From Boris Bikes in London to Bike Share across the World. Introducing, visualising and analysing bike share schemes in Europe, America and Asia, including London's Barclays Cycle Hire, Montreal's Bixi, Barcelona's Bicing and Paris's Velib. Who's using them, when are they using them and what do the schemes look like?

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  • The picture is of the T-shirt that was given out to the first 1000 people that signed up for the scheme in London.
  • Fully automated, including sign-up and operation. However London, at least, employs workers at some of the stations at rush-hour to provide extra capacity (bikes in the morning, spaces in the evening). This is a short term measure. Waterloo will shortly get 350 docks which should alleviate this problem.
  • This is a familiar scene to commuters leaving the terminal stations in the morning, or leaving the City in the evening...
  • Above: Minneapolis “Nice Ride”. Below: Barcelona “Bicing”
  • The cities are at roughly the same scale (exactly the same zoom level, which = scale * cosine (latitude))
  • Screenshot of empty bike stations in west Barcelona at 9pm on Wednesday.
  • Note this is just one day’s worth of data – and doesn’t control for weather conditions or special events.
  • Note this is just one day’s worth of data – and doesn’t control for weather conditions or special events.
  • London, Dublin and Brussels have a slightly earlier evening peak than Milan and Paris. Vienna doesn’t use the scheme to commute.
  • Use at lunch is as much as (or more than) during the evening rush hour, and the evening peak occurs at around 7pm – the Spanish “siesta” working pattern”. Girona is very small, so usage rises gradually during the day, rather than having a morning rush hour.
  • Denver doesn’t have the rush hour peaks – showing that few commuters are using the scheme, possible due to the U.S car culture?
  • Usage in general much lower than during the week, and mainly late afternoon use, particularly in Paris and Milan.
  • Spain still has a siesta at the weekends! (The effect is noticeable in four of the five Spanish cities included.) The bikes also get used all through the evenings.
  • Higher usage at the weekend than during weekdays, in the US.
  • Comparing world city dynamics based on bike shares!
  • Visualising Bike Share (#geomob 21 October 2010)

    1. 1. Visualising Bike Share From Boris Bikes in London to Bike Share across the World Oliver O’Brien UCL CENTRE FOR ADVANCED SPATIAL ANALYSIS Photo CC-NC-By-SA Adam Bowie on Flickr
    2. 2. Contents • Intro to bike share • Around the world • Visualising • Analysing trends • Other community efforts Photo CC-By Charlotte Gilhooly on Flickr
    3. 3. What is a Bike Share? • A scheme allowing bikes to be hired from (and returned to) certain locations • City or campus based • Typical use is for short durations • Generally fully automated (in theory) • Require an account linked to a credit card Photo CC-NC-By-ND Terry Freedman on Flickr
    4. 4. • Docks – The things which hold onto the bikes and release them • Stations – groups of docks • Spaces – docks which are empty Photo CC-By Les Hutchins on Flickr Terminology
    5. 5. The Bikes • Normally “odd” looking, “lively” colours – Eye catching amongst street furniture – For sponsor branding – To discourage theft • Custom designed with non-standard parts, to prevent part theft. Photos CC-By tsuacctnt and CC-NC-By-ND Monica Vidal on Flickr
    6. 6. Worldwide Distribution of Bike Shares From
    7. 7. Current Locations for my Visualisation City Official Name Installed System # of Bikes London Barclays Cycle Hire July 2010 Bixi 4,300 Barcelona Bicing March 2007 Bikemi 4,200 Milan Bikemi December 2008 Bicing 1,100 Saragossa Bizi May 2008 Bicing 800 Girona Girocleta September 2009 TNT 100 Washington DC and Arlington Capital Bikeshare September 2010 Bixi 650 Montreal Bixi May 2009 Bixi 4,200 Minneapolis Nice Ride June 2010 Bixi 600 Denver B-cycle April 2010 B-cycle 350 Melbourne Bike Share June 2010 Bixi 400
    8. 8. Rejected Locations  City Official Name System # of Bikes Reason Shanghai Forever Forever 50,000 Rate limiting Stockholm City Bikes Bicing 1,000 Blocking the data Cardiff OYBike OYBike 100 Key changes at midnight Lyon Velo’V Velib 3,000 Scraping proving difficult Paris Velib Velib 17,300 Take-down request Brussels Villo Velib 1,700 Take-down request Dublin dublinbikes Velib 400 Take-down request Valencia Valenbisi Velib 1,000 Take-down request Seville Sevici Velib 1,850 Take-down request Vienna Citybike Velib 750 Take-down request Toyama Cyclocity Velib 130 Take-down request Brisbane CityCycle Velib 500 Would result in take-down request
    9. 9. To Be Added City Official Name Installed System # of Bikes Mexico City Ecobici February 2010 Bicing 1,000 Rio Samba November 2009 Samba 100 Torino Tobike June 2010 Tobike 1,200 Dijon Velodi June 2008 Bikemi 350 • Any others which have websites with location data for stations and counts for both bikes and spaces – Not Nextbike schemes in Eastern Europe (no spaces) • But they do have bike IDs for up to 5 bikes at each dock – Not various large schemes in China (no website) – Not Velib (as requested by operator)
    10. 10. Melbourne – Helmets • Scheme started in June 2010, slow to grow – By law, helmets must be worn (or AU$150 fine) – Helmets are not supplied with the scheme – Can now buy AU$5 helmet from two vending machines or a supermarket chain • Return to a supermarket for AU$3 cash-back – Also launched in the middle of winter Source and image from
    11. 11. Brussels – Where’s My Villo? • Campaign group – Aiming to improve: • Reliability • Distribution • Service level transparency – Tracking performance measures – Interested in comparing with other cities Source and images from
    12. 12. Denver – Conspiracy • “Republican gubernatorial candidate Dan Maes is warning voters that Denver Mayor John Hickenlooper's policies, particularly his efforts to boost bike riding, are ‘converting Denver into a United Nations community.’ “Dan Maes said Denver's B-Cycle bike-sharing program was promoted by a group that puts the environment above citizen rights.” – article in the Denver Post Source, photo CC-By-NC Trace Altman on Flickr
    13. 13. Let’s Visualise Them! • Obtain the data from the operators’ websites – Some provide XML/JSON/KML – Lots of Regex parsing – Velib-based systems require two stages • Store it for analysis • Stick it on a map – OpenLayers has some nice vector styling for points – OpenStreetMap-based background – Charts of historical trends via the Google Chart API 'id:"([0-9]+?)".*?name:"(.+?)".*?lat:"(.+?)".*?long:"(.+?)".*?nbBikes:"([0-9]+?)".*? nbEmptyDocks:"([0-9]+?)".*?installed:"(.+?)".*?locked:"(.+?)".*?temporary:"(.+?)".*?'
    14. 14. Background map CC-By-SA OpenStreetMap contributors
    15. 15. Background map CC-By-SA OpenStreetMap contributors
    16. 16. Animation over 48 hours • All in Javascript – Using SVG (or VML in Internet Explorer) • The animation is extremely slow in I.E. • Not great in Firefox • Excellent in Chrome/Safari
    17. 17. N Europe: 1. London 2. Paris 3. Dublin 4. Brussels Spain: 1. Barcelona 2. Girona 3. Valencia 4. Seville America: 1. Wash. DC 2. Montreal 3. Minneapolis 4. Denver 1. Vienna 2. Milan 3. Toyama, JP 4. Melbourne
    18. 18. Bike/Dock Ratio • A key component in the optimisation of a bike hire scheme • For the users, having too many bikes is very bad – Frustrating if you can’t drop off your bike while the clock is ticking. • But more bikes mean more visibility for the scheme and promotion for the sponsors
    19. 19. Bike/Dock Ratio • No of bikes per 100 docks – Based on max availability at around 5am (“no” usage) – Averaged over a few weeks City Ratio/100 Melbourne 60 London 56 Montreal 56 Denver 54 Milan 52 Dublin 51 Minneapolis 50 Toyama 50 Barcelona 49 Washington DC 49 Girona 48 Paris 47 Vienna 47 Brussels 46 Seville 42 Valencia 39 Average 50 Background map CC-By-SA OpenStreetMap contributors Preliminary/unreviewed data
    20. 20. Peak Usage % (Weekday) • Max % of bikes being used – Data from last Wednesday – Not directly measurable – Assumes that usage dropped to zero overnight – Simple analysis, not considering the effect of weather conditions, public holidays or special events City Peak Dublin 41% London 25% Valencia 22% Girona 21% Barcelona 20% Seville 20% Milan 18% Paris 15% Montreal 13% Melbourne 12% Washington DC 11% Brussels 10% Toyama 9% Vienna 9% Denver 8% Minneapolis 6% Photos CC-NC-By-ND D1v1d on Flickr Preliminary/unreviewed data
    21. 21. Peak Usage % (Weekend) • Max % of bikes being used – Data from last Saturday – Weekend usage much higher than weekday usage for the U.S. cities, lower for Europe City Peak Dublin 25% Barcelona 20% Washington DC 19% Denver 18% Girona 17% Valencia 16% Vienna 12% Seville 11% Milan 11% Minneapolis 11% London 10% Paris 10% Montreal 8% Brussels 7% Melbourne 5% Toyama 3% Photos CC-NC-By DDOT DC on Flickr Preliminary/unreviewed data
    22. 22. Bike-o-Meter • Tweet-o-Meter for bikes – Steven Gray (@frogo) – Using Google Gauges • See the real life Tweet- o-Meters at the new British Library “Growing Knowledge” exhibition – Should be easy to hack to show the Bike-o- Meters instead 
    23. 23. Weekday Use – 1. Europe ex-Spain Preliminary/unreviewed data
    24. 24. Weekday Use – 2. Spain Preliminary/unreviewed data
    25. 25. Weekday Use – 3. Rest of World Preliminary/unreviewed data
    26. 26. Weekend Use – 1. Europe ex-Spain Preliminary/unreviewed data
    27. 27. Weekend Use – 2. Spain Preliminary/unreviewed data
    28. 28. Weekend Use – 3. Rest of World Preliminary/unreviewed data
    29. 29. More Analysis • London • Graph shows number of bikes available to hire • Effect of rain – Using the CASA weather station • Effect of the tube strikes Preliminary/unreviewed data
    30. 30. More Analysis! Clustering • Geodemographics of a city area based on usage patterns of stations within it? • Could combine with existing demographic data to predict likely usage patterns of new stations Clustering output courtesy of James CheshirePreliminary/unreviewed data
    31. 31. Even More Analysis! Redistribution Effectiveness • Distribution – Which cities have the most effective redistributions? – When does the redistribution occur? – Does it actually make things worse?
    32. 32. Redistribution Effectiveness Preliminary/unreviewed data
    33. 33. Even More Analysis Possible? • Shapes and sizes of cities and their schemes – How convenient is the scheme for the intended users? – Coverage in residential versus commercial areas • Dock station densities – How far away from your destination to you need to go to find a docking station? • Flows – Would require “bike-level” information rather than “station-level” as at present
    34. 34. Also in the Community • Adrian Short (@adrianshort) – first “Boris Bikes” API for London – • Andrew Larcombe (@andrewl) – Where Are The Bikes API - A universal PHP API for extracting data for bike share schemes – Currently includes over 60 schemes –
    35. 35. Also in the Community • Aidan Slingsby (City Uni) – • Includes “seeing ahead” for the next four hours • Tom Taylor – Cycle Hire Explorer • Includes total usage counts • • Lots of cycle hire apps for iPhone/Android Screenshot of Aidan Slingsby’s TFL Bikes graphs
    36. 36. Also in the Community Screenshots of some of the apps on the iPhone (iOS4) for the London Cycle Hire scheme. Clockwise from top left: Cycle Hire Live, iLondonCycle, London Cycle, Bixou Lite, Blue Lanes, Apple App Store
    37. 37. Thanks! Email: o.obrien [at] Blog: Twitter: @oobr Photo CC-NC-By Kurtis Garbutt on Flickr