Extracting amenity demand and visitation profiles from mobile phone location data

Research Project, 2022

To offer sustainable transport alternatives to urban residents one must first understand the patterns of visitation (i.e. time of day, day of week, distance travelled, origin) to different types of amenities,
such as grocery stores. Traditional mobility data (e.g. Google profiles, household travel surveys) does not offer the temporal or spatial disaggregation required to capture these patterns. New location data sources, such as anonymized mobile phone location data, have the potential to fill this gap. However, there is a need to develop methods to analyse and to validate this new data source. The aim of this project is to use mobile phone application data to calculate the demand and visitation profiles of local amenities and test their representativeness, in the case of the Gothenburg region.

The project will report on the representativeness of mobile phone location data for obtaining amenity demand and visitation profiles, in the case of the Gothenburg region. Furthermore, it will provide methods (code) to process and analyse this new data source. Finally, it will offer visualisations of amenity demand and visitation profiles that can be used in urban digital twins, in particular within the Chalmers Digital Twin Cities Centre.