Extracting spatiotemporal commuting patterns from public transit data

•With accelerated migration rates, cities are transforming considerably and trying to keep up with the changing mobility needs of its citizens.•Transport demand analysis heavily relies on census information or modelling based on complete trajectories of individuals; data that gets quickly outdated.•We propose the use of tractable and privacy-preserving data to develop a framework for transportation demand analysis over time.•We apply our framework to the Greater London region consisting of over 4 million traces of mobility.•We find that individual demand profiles can be easily extracted from such simple data for a day’s mobility, which also reveals the structure of urban areas.•This evaluation of a transit system reveals a lot of information about the efficiency, mixed-use and potential of developing urban areas for safety and sustainable growth.