This visualization in the video above builds upon the thesis research of Jay Gordon. It was sponsored by the MIT Transit Research Group and Transport for London.
From the YouTube Description:
This visualization merges all 16 million daily transactions made on London’s Oyster card with vehicle-location data from the city’s 8,500 buses to infer the travel histories of that day’s 3.1 million Oyster users. After inferring the times and locations of each bus boarding and alighting, bus and rail transactions are combined to reconstruct each cardholder’s daily travel history.
Each pixel represents an approximately 100-square-meter section of Greater London, and the brightness of each of the three RGB color components indicates the number of riders in one of three categories. Green indicates the number of passengers in the transit system, whether on a bus or in one of several rail modes. Blue indicates the presence of riders prior to their first transaction of the day or after their last: it is assumed that the location of a rider’s first or last transaction approximates their place of residence. Red indicates cardholders who are between transit trips, whether transferring, engaging in activities, or traveling outside the transit system.
By matching Oyster transaction records to data from the iBus vehicle-location system, buses are shown to traverse the street network at their observed speeds, and their brightness reflects the number of passengers on board. Rail customers tap their cards when entering or exiting stations, but their waiting times and choices of line and transfer location are not known (in this version). Rail passengers are therefore shown traveling in straight lines at constant speeds, interpolated between their entry and exit taps.
Found via Reddit.