Automated land use identification using cell-phone records

Víctor Soto · Enrique Frı́as-Martı́nez

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Human Mobility and Location-Based Analysis Remote Sensing and Land Use Data Management and Algorithms

Abstract

Pervasive large-scale infrastructures generate datasets that contain human behavior info rmation. In this context, cell phones and cell phone networks, due to its pervasiveness, can be considered sensors of human behavior and one of the main elements that define our digital footprint. In this paper we present a technique for the automatic identification and classification of land uses from the information generated by a cell-phone network infrastructure. Our approach first computes the aggregated calling patterns of the antennas of the network and, after that, finds the optimum cluster distribution to automatically identify how citizens use the different geographic regions within a city. We present and validate our results using cell phone records collected for the city of Madrid.

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References

2005Reality mining: sensing complex social systems 2006Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis 2007Learning and inferring transportation routines 2008Uncovering individual and collective human dynamics from mobile phone records 2007Cellular Census: Explorations in Urban Data Collection 2009Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network 2005Location based services—new challenges for planning and public administration?

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