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.
Preview |
Text
GISRUK_2024_Mavrogeni.pdf - Published Version Download (1MB) | Preview |
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 |
Archive Staff Only
 |
View Item |
