LSHTM seminar: Discovering bike share cycle behaviours through interactive visual analysis. Or why pictures are a necessary part of big data analytics

London School of Hygiene & Tropical Medicine Seminar, January 2014, London

Transcript

1. Discovering bike share cycle behaviours through interactive visual analysis. Or why pictures are a necessary part of big data analytics. Roger Beecham and Jo Wood giCentre, City University London
2. The increasing availability of sensor data in urban areas now offers the opportunity to perform continuous evaluations of transport systems and measure the effects of policy changes, in an empirical, large-scale and non- invasive way. (Lathia et al. 2012:88)
4. How, and to what extent, can the London Cycle Hire Scheme usage datasets be analysed to answer existing research questions within Transport Studies?
5. Part 1: How visualization techniques (interactive graphics) enables exploratory analysis. Part II: How visualization can support more analytically involved aspects of data analysis. Part III: How we might make confirmatory claims about behaviour -- or organise a data analysis project using these passively generated datasets in the future.
6. Part I: Exploring behaviour
7. Datasets
8. Data processing and analysis
9. Relating customer variables with space- time patterns of behaviour
11. No weighting factor
12. Weekday am Weekday pm Waterloo King’s Cross King’s Cross Waterloo
13. Exploring gendered usage In bicycle-friendly cities […] cycling is an inclusive, population-wide activity. […] In car-oriented cities […] the majority of cyclists are middle-aged men. [...] So strong is the association between cycling mode share and female rates of cycling that some observers have suggested that cycle-equity in cycling is an indicator of a cycling-friendly environment. Garrard, Handy & Dill, 2012: 211
14. Insights
15. Male King’s Cross Waterloo Hyde Park
16. Female King’s Cross Waterloo Hyde Park
17. Controlling for geodemographics
18. Male <5km Sep 2011-2012 Female <5km Sep 2011-2012
19. Women’s journeys remain spatially constrained - even controlling for access period, level of usage and geo-demographics
20. Male High RF <5km Sep 2011-2012 10,700 members; 1.7m journeys
21. Female High RF <5km Sep 2011-2012 3,200 members; 457,000 journeys
22. Part II: How visualization can support more analytically involved aspects of data analysis
23. Inferring cyclists’ workplaces and classifying commuting journeys
24. Mean-centres method
25. Mean-centres method
26. Mean-centres method
27. Mean-centres method
28. K-means method
29. Kernel density estimation method
30. Kernel density estimation method
31. Kernel density estimation method
32. Part III: towards explanatory analysis?
34. Conflating actual with GIS routes?
35. Research questions
36. Research questions RQ1. Which bridges are most likely to be used by men and women?
37. Research questions RQ1. Which bridges are most likely to be used by men and women? RQ2. To what extent are these bridges crossed equally in either direction (northbound and southbound)?
38. Research questions RQ1. Which bridges are most likely to be used by men and women? RQ2. To what extent are these bridges crossed equally in either direction (northbound and southbound)? RQ3. Are journeys that involve a river crossing generally more demanding than other journeys made between LCHS docking stations?
39. London Bridge! Southwark Bridge! Blackfriars Bridge! Waterloo Bridge! Westminster Bridge! Lambeth Bridge! Vauxhall Bridge!
41. Counted journeys over ‘suggested’ bridges
42. Men’s and women’s usage of bridges
43. Geography of men’s and women’s workplaces
44. Men’s and women’s usage of bridges
45. Men’s and women’s usage of bridges
46. Are (suggested) cycled journeys over certain bridges more demanding than others? !
47. Are (suggested) cycled journeys over certain bridges more demanding than others? !
48. Are (suggested) cycled journeys over certain bridges more demanding than others? !
49. Conclusion
50. Roger Beecham and Jo Wood giCentre, City University London roger.beecham.1@city.ac.uk; j.d.wood@city.ac.uk