Animation of Cycle Hire Patterns

I’ve now added a historic view of my cycle hire dock visualisation – you can “replay” the dock capacity changes over the last 48 hours by clicking on the “Animation” link or going directly to the animation page and then clicking “Start Animation”

By default, a different colour/shape scheme is used – the circles grow or shrink and become redder or duller, as the docks fill up or empty respectively. You can change the colours used with the drop-down, as normal.

The circles are being redrawn by your browser for each frame of the animation, and speeds vary greatly on your browser. Each frame represents 10 minutes of real time. The redrawing is intensive and might occasionally lock up your computer!

On my reasonably fast computer, the maximum frame rate I can get is:

  • Chrome or Safari: 7 frames a second
  • Firefox: 3 frames a second
  • Internet Explorer 8: 2 frames a second (zoomed in)

If Internet Explorer is zoomed out to match the default zooms in the other browsers, the rate drops to 1 frame every 8 seconds…

The distinctive weekday commuting patterns are easy to spot, with the morning rush into the centre, followed by the evening rush back out to the edges and the station terminals. Distribution vehicles movements can be inferred, particularly during the wee small hours when there is little other activity.

London data in MapTube

I have uploaded a number of spatially-referenced, recent datasets from the London Data Store, to MapTube. Here are some of the more interesting looking ones.

(1) Data from the London Ambulance Survey (LASS) – here comparing the numbers of ambulance callouts to assaults with knife injuries vs gun injuries for each London ward in the last 24 months to May – please note the category scales across the two maps areas are different, so cannot be compared directly. Darker, redder values are higher. Click a picture to see the interactive map and legend, and download the source data.

Knives:

Guns:

(2) The Active People Survey – an interesting difference between the boroughs for volunteering rates compared with participation rates. Darker, redder boroughs indicate higher proportions of those surveyed in that borough say they volunteer or participate in active sports.

Volunteering:

Participation:

Volunteering much better in the outer London boroughs right around the centre, while participation is concentrated in the south-west.

(3) Houses in council tax bands A, B and C (the lowest rates) vs those in F, G & H (the highest rates), at output area level – very detailed! Not necessarily a proxy for affluence. Again, darker, redder areas have a greater proportion of houses and other dwellings in these bands.

A, B and C (Lowest council tax rate bands):

F, G and H (Highest council tax rate bands):

OpenStreetMap – The Quality Issue

This was the title of a presentation I gave today at the 46th Society of Cartographers Summer School (Lanyrd), which was in Manchester.

The abstract was:

OpenStreetMap is coming of age, but as it starts to be used more in the mainstream, the age-old questions of quality and completeness are coming to the fore. A range of data sources have been used to build up the map in the UK, from GPS traces to aerial imagery, historic mapping, NaPTAN and the OS Open Data release, each with their own benefits and limitations. This talk looks at a number of studies and tools developed to quantify, compare and address accuracy and coverage of the project in the UK, in an attempt to answer the key questions – is it complete yet and just how good is it?

The presentation makes references to two animations, which are the Milton Keynes Mapping Party traces and the US TIGER import sequence.

A Month of Bike Docks in London

The TfL cycle hire scheme has been up and running for around six weeks, and I’ve been collecting data from the TfL map for around a month – let’s have a look at it.

Here’s a graph, in ‘calendar’ format, showing how the number of bikes available to hire fluctuates each day. As use increases, fewer bikes are available to use and the line dips. Most weekdays have three narrow dips, a medium-sized one representing the morning rush hour, a small one at lunch and a large one for the evening rush hour. Weekends have a single broad dip, lasting throughout the late morning and afternoon. The Sunday dip starts slightly later than the Saturday one (maybe people have longer lie-ins on Sunday?) but apart from that the weekend pattern is broadly similar.

A more useful indicator of wherever you are going to have problems finding free or docks or bikes, is to measure how uneven the distribution of bikes is. The distribution imbalance graph describes how many bikes would need to be moved in order for every docking station to have the same proportion of bikes and spaces. A high value indicates a very skewed distribution, e.g. most central docks full and most peripheral ones empty. A low value indicates a more even flow.

The TfL distribution teams presumably work to even out the distribution except in key commuter hubs, i.e. around stations. You can see this with a gradual dip in the graph during the spell between morning and evening rush hours. There are also short-lived sharper dips at the beginning of the two main rush hours as full docks start to empty before the destination ones become completely full. Weekends generally have a more even distribution, which also changes less abruptly. An “ideal” usage of the scheme would probably have a constant and low value for the distribution imbalance.

Finally, here’s a graph which also includes rain data from the CASA weather station here in central London Aidan Slingsby’s weather station which is based just north of the hire zone. The data is a little suspect – particularly as it didn’t record any last night and I got soaked on the way home. However, apart from the last week or so, I think it is a good indication of when it was raining. The higher the blue bar, the heavier the rain.

As you would expect, rain during the three main weekday cycle usage times, or during the weekend day, tends to diminish the number of bikes being used and so increase the number available, causing the dips in red to decrease in size or disappear altogether.

Here’s one further version of the above graph, with a narrative for key cycle-related events happening in central London during the last month, which may or may not explain changes in the pattern compared to the same day of the week elsewhere in the month.