V.4 Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis

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Carlo Ratti

Riccardo Maria Pulselli

Sarah Williams

The prevalence of cell phone use in Milan creates a way to estimate population movement in the city. Maps created from this data allow us to answer questions about where people congregate, for how long, and at what time of day. They show how people interact with the physical environment of the city. The research team of geographer and urban designer Sarah Williams, and architects Carlo Ratti and Riccardo Maria Pulselli developed a partnership with Vodafone, one of the largest European cell phone companies, to map this activity. Raw cell phone data for 2004-2005 is mapped here for Milan and illustrates urban dynamics that have never been accessible to policy experts at this level of detail. The hourly population estimates provide infrastructure planners with a way to infer urban density, thus helping them create better plans for public transport or roadway restrictions. City managers can use this real-time activity data to help create plans during emergency events. Urban designers can identify “good” spaces as it illustrates where people like to congregate. The triangulation techniques established to create these maps can be used to infer population data for developing countries where citizens use cell phones on a daily basis.


References:

Ratti, Carlo, Sarah Williams, Dennis Frenchman, and Riccardo M. Pulselli. 2006. “Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis.” Environment and Planning B: Planning and Design 33: 727-748.

Williams, Sarah, Carlo Ratti and Riccardo Maria Pulselli. 2006. Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis. Courtesy of MIT SENSEable City Laboratory. In “5th Iteration (2009): Science Maps for Science Policy-Makers,” Places & Spaces: Mapping Science, edited by Katy Börner and Elisha F. Hardy. http://scimaps.org.

Acknowledgements: This exhibit is supported by the National Science Foundation under Grant No. IIS-0238261, CHE-0524661, IIS-0534909 and IIS-0715303, the James S. McDonnell Foundation; Thomson Reuters; the Cyberinfrastructure for Network Science Center, University Information Technology Services, and the School of Library and Information Science, all three at Indiana University. Some of the data used to generate the science maps is from the Web of Science by Thomson Reuters and Scopus by Elsevier. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.