Time patterns, geospatial clustering and mobility statistics based on mobile phone network data

In our research we aim to gain insight in the geospatial activity of mobile phone users. Points op interest are the correlation between calling- and economic activity, population density based on the number of active mobile phones in an area and movement statistics. A derived research question is deducing a method to obtain a tessellation of cell serving areas from a cell plan and combining different tessellations.For our research we obtained a dataset from a telecommunication company containing records of all call-events on their network in the Netherlands for a time period of two weeks. Each record contains information about the time and serving antenna and an identification key of the phone. The dataset is large (containing over 600 million records) and the cell plan has over 20.000 geo-locations of antennas. We devised a method to transform this cell plan with use of the Voronoi algorithm into an appropriate tessellation needed for geo-spatial analysis.Results of our research are a geo-spatial animation from which it is clearly visible that high call intensity coincides with high population density. Also with use of k-means clustering we found useful patterns in the time series of the call activity providing insight into economic activity over time and space. Using the unique phone identification we obtained information of the movement of Dutch inhabitants.