This animation visualizes the number of riders in the London Underground over two weeks in 2010. Each dot corresponds to one station. Dot size corresponds to the number of riders passing through each station. Big dots for busy stations. Small dots for less busy stations. Dot color represents the lines serving each station. White dots are for stations where three or more lines intersect. Each dot pulsates twice in a day. Once during the morning commute. And again during the evening commute.
If you like this, please watch my animation of weekday vs. weekend commuting patterns in the NYC subway.
This animation does not pretend to be scientific. This is the representation of movement – a way to visualize the rhythmic pulsing of people through the London Underground as analogous to the breathing human body. The passage of red blood cells through the body’s veins is analogous to the movement of people through trains. The red blood cells bring oxygen and remove waste from the cells. Each semi-autonomous cell (with nucleus, membrane, etc.) is analogous to a workplace or home (with kitchen, walls, etc). Much like the cars and trains that move people and distribute their wealth from places of work to places of leisure, the red blood cells are the vehicles that link the heart and lungs (i.e. Central London) to the rest of the body (i.e. the London Metropolitan Region). This analogy of human form to city plan is a longstanding theme in urban studies.
No algorithm or dataset could capture the true complexity of London’s rhythmic breathing during the daily commute. Stations like King’s Cross St. Pancras, Waterloo, and Victoria rank among the busiest because they are multimodal transfer points between long distance trains, taxis, cars, and buses. So, although this animation visualizes these busiest stations with the largest dot size, this does not necessarily mean more people work or live in the vicinity of these stations. Admittedly, aspects of dot size are determined by immeasurable external factors – namely transfers from other transport modes to the London Underground.
This animation is based off of open-access data collected in November 2010. According to transport for London: “Passenger counts collect information about passenger numbers entering and exiting London Underground stations, largely based on the Underground ticketing system gate data.” Excluding London Overground, the Docklands Light Railways, National Rail, and other transport providers, there are 265 London Underground stations surveyed in this data set. For data collection purposes, stations where two or more lines intersect are counted as a single data entry. This is because at complex interchanges of multiple lines (e.g. Paddington), it is difficult to track which of the lines (e.g. Bakerloo, Circle, District, Hammersmith & City) a passenger is boarding. To complicate matters, passengers are often granted free transfers between lines at interchanges.
Every fifteen minutes, the numbers of passengers are counted from gate entry data, that is, four times per hour. This yields 96 time intervals over each 24 hour period. Multiplying the number of time intervals (96) by the number of stations (265), we get the number of data points represented in this animation: 25,440. Each of the stations was also assigned its corresponding latitude and longitude coordinate, so as to appear on the map in its appropriate spatial location. In the data analysis software (Tableau), we assigned each station:
- A spatial location → derived from latitude and longitude coordinates coordinates
- A color → according to the lines extant in 2010: Bakerloo, Central, Circle, District, Hammersmith & City, Jubilee, Metropolitan, Northern, Piccadilly, Victoria, Waterloo & City.
- A size → scaled to reflect the passenger count in each 15 minute interval. The smallest dot corresponds to the rate of: zero passengers per 15-minute interval. The largest dot corresponds to the rate of about 7,500 passengers per 15-minute interval. This is the range applied to dot size: 0<X<7,500 where X represents “passengers/time.”
- A time of day → each time interval represents one frame in the animation. We exported each frame from Tableau, conducted slight edits to background map opacity and texture, and then stitched the frames back together again – to create a flip book of sorts. With a rate of 12 frames per 1 second, or 96 frames per 8 seconds, a single day with 25,440 data points is compressed into 8 seconds of animation. This 8 second sequence is then looped.
By syncing the audio volume and background color with the data and time of day, the animation becomes more visually legible. The audio volume rises and falls to mirror the growth and contraction of each colored dot. The background color also shifts from black to gray to mirror the time of day. This was achieved by manually adjusting the background opacity in Adobe Illustrator from 100% to 50% for each of the 96 frames – as modeled with a cosine formula. The visualization was created in Tableau with post-production audiovisual editing in Final Cut Pro.
The eight second sequence played on a loop as a .gif file.
Lat Long Coordinates for Stations: Bell, Chris. “London Stations.” doogal.co.uk. doogal.co.uk/london_stations.php (retrieved 21 April 2019).
Ridership Statistics: “Our Open Data.” Transport for London. tfl.gov.uk/info-for/open-data-users/our-open-data (retrieved 21 April 2019). To access data, scroll down to the section entitled “Network Statistics,” then click where it reads “London Underground passenger counts data.”
“List of Busiest London Underground Stations.” Wikipedia. en.wikipedia.org/wiki/List_of_busiest_London_Underground_stations (retrieved 21 April 2019).
“London Connections Map.” Transport for London. tfl.gov.uk/corporate/publications-and-reports/london-connections-map (retrieved 21 April 2019).
Audio effects for animation: “Heartbeat.” Freesound. https://freesound.org/search/?q=heartbeat (retrieved 23 April 2019).