Deriving flow patterns from GPS in-app mobile phone data

GPS location data can reveal information about individuals’ everyday lives, something that conventional data sources like census data cannot do. However, one major limitation of GPS location data is that almost always the location will be recorded with a level of error, known as positional uncertainty. This paper works around the above limitation by aggregating the data at the MSOA level and performing origin-destination analysis. Origin-destination matrices are created to investigate interaction flows and reveal insights on MSOA level connections. We discuss how the analysis can benefit policymakers and public transport providers.