Computational Approaches for Urban Environments

Volume 13 of the series Geotechnologies and the Environment pp 363-387


Towards a Comparative Science of Cities: Using Mobile Traffic Records in New York, London, and Hong Kong

  • Sebastian GrauwinAffiliated withSenseable City Lab, Massachusetts Institute of Technology Email author 
  • , Stanislav SobolevskyAffiliated withSenseable City Lab, Massachusetts Institute of Technology
  • , Simon MoritzAffiliated withEricsson Research
  • , István GódorAffiliated withEricsson Research
  • , Carlo RattiAffiliated withSenseable City Lab, Massachusetts Institute of Technology

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This chapter examines the possibility to analyze and compare human activities in an urban environment based on the detection of mobile phone usage patterns. Thanks to an unprecedented collection of counter data recording the number of calls, SMS, and data transfers resolved both in time and space, we confirm the connection between temporal activity profile and land usage in three global cities: New York, London, and Hong Kong. By comparing whole cities’ typical patterns, we provide insights on how cultural, technological, and economical factors shape human dynamics. At a more local scale, we use clustering analysis to identify locations with similar patterns within a city. Our research reveals a universal structure of cities, with core financial centers all sharing similar activity patterns and commercial or residential areas with more city-specific patterns. These findings hint that as the economy becomes more global, common patterns emerge in business areas of different cities across the globe, while the impact of local conditions still remains recognizable on the level of routine people activity.


Big data City Science Cellphone networks Urban analysis Urban planning