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Deriving flow patterns from GPS in-app mobile phone data

Mavrogeni, mikaella; Longley, paul; Van Dijk, Justin; (2024) Deriving flow patterns from GPS in-app mobile phone data. In: Proceedings of the 32nd Conference of GIS Research UK (GISRUK). GISRUK: Leeds, UK. Green open access

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Abstract

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.

Type: Proceedings paper
Title: Deriving flow patterns from GPS in-app mobile phone data
Event: 32nd Annual Geographical Information Science Research UK (GISRUK)
Location: Leeds, UK
Open access status: An open access version is available from UCL Discovery
DOI: 10.5281/zenodo.10897763
Publisher version: https://doi.org/10.5281/zenodo.10897763
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography
URI: https://discovery.ucl.ac.uk/id/eprint/10193191
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