Consensus clustering for urban land use analysis using cell phone network data

Pervasive large-scale infrastructures, such as cell phone networks, have the ability to capture individual digital footprints, and as a result, generate datasets that provide a new vision on human dynamics. In this context, cell phones and cell phone networks, due to its ubiquity, can be considered one of the main sensors of human behavior. The information collected by these networks can be used to understand the dynamics of urban environments with a detail not available up to now. One of the areas that can benefit from this information is urban planning. In this paper, we present a technique for the automatic identification of land uses from the information gathered by a cell-phone network. Our approach first computes the aggregated calling patterns of the antennas and, after that, finds clusters that identify how individuals use each geographic region. Given the inherent diversity of human activities in urban landscapes, we use consensus clustering to identify land uses, characterizing only those geographical areas with well defined behaviors. We present and validate our results using cell phone records and official land use data collected for Madrid.