The hidden image of the city: sensing community well-being from urban mobility

  • Authors:

  • Neal Lathia;Daniele Quercia;Jon Crowcroft

  • Affiliations:

  • The Computer Laboratory, University of Cambridge, UK;The Computer Laboratory, University of Cambridge, UK;The Computer Laboratory, University of Cambridge, UK

  • Venue:
  • Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
  • Year:
  • 2012

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Abstract

A key facet of urban design, planning, and monitoring is measuring communities' well-being. Historically, researchers have established a link between well-being and visibility of city neighbourhoods and have measured visibility via quantitative studies with willing participants, a process that is invariably manual and cumbersome. However, the influx of the world's population into urban centres now calls for methods that can easily be implemented, scaled, and analysed. We propose that one such method is offered by pervasive technology: we test whether urban mobility--as measured by public transport fare collection sensors--is a viable proxy for the visibility of a city's communities. We validate this hypothesis by examining the correlation between London urban flow of public transport and census-based indices of the well-being of London's census areas. We find that not only are the two correlated, but a number of insights into the flow between areas of varying social standing can be uncovered with readily available transport data. For example, we find that deprived areas tend to preferentially attract people living in other deprived areas, suggesting a segregation effect.