Assessing mobile phone data as proxy census commuting data for transport geography research: a critical review and case study

Census commuting datasets underpin much research on spatial patterns of journey-to-work but fewer Censuses now collect such data. Major post-Covid changes to working practices call for mid-2020s commuting data, making any Census 2020/1 commuting datasets less relevant. Detailed geographical research needs commuting flow matrices at a local scale, and sample surveys cannot provide Census-like granular datasets. Declining Census data availability has stimulated growing interest in ‘big’ data, and data from mobile phones in particular. This paper provides a case study of using mobile phone data as a proxy for Census commuting data to define labour market areas. The case study is of Spain and exemplifies issues that can arise in any transport geography research using mobile phone data. The paper first itemises numerous ‘mismatches’ between such data and most Census commuting datasets. A critical problem for commuting studies is that many mobile owners/users are not workers, but commercial and confidentiality concerns prevent the release of metadata, and so non-workers cannot be excluded from this form of ‘commuting’ data. In this work we demonstrate a method to filter out most non-working flows to better approximate actual commuting flows. Our results suggest that mobile phone data, with appropriate transformations, may be a useful substitute for Census commuting data flows. However having data from both sources for the same territory and period remains vital to fully validate this conclusion.