Abstract

In this article, we present temporally dynamic population distribution data from the Helsinki Metropolitan Area, Finland, at the level of 250 m by 250 m statistical grid cells. An hourly population distribution dataset is provided for regular workdays (Mon – Thu), Saturdays and Sundays. The data are based on aggregated mobile phone data collected by the biggest mobile network operator in Finland. Mobile phone data are assigned to statistical grid cells using an advanced dasymetric interpolation method based on ancillary data about land cover, buildings and a time use survey. The dataset is validated by comparing population register data from Statistics Finland for night hours and a daytime workplace registry. The resulting 24-hour population data can be used to reveal the temporal dynamics of the city, and examine population variations relevant to spatial accessibility analyses, crisis management, planning and beyond.

Measurement(s)

population distribution

Technology Type(s)

mobile phone • digital curation

Factor Type(s)

geographic location • hour of the day • day of the week

Sample Characteristic - Environment

city

Sample Characteristic - Location

Capital Region • Helsinki

Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.17168978

Details

Title
A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland
Author
Bergroth Claudia 1 ; Järv Olle 2   VIAFID ORCID Logo  ; Tenkanen Henrikki 3 ; Manninen Matti 4 ; Toivonen Tuuli 2   VIAFID ORCID Logo 

1  Unit of Urban Research and Statistics, City of Helsinki, Helsinki, Finland; University of Helsinki, Digital Geography Lab, Department of Geosciences and Geography, Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071) 
2  University of Helsinki, Digital Geography Lab, Department of Geosciences and Geography, Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071); University of Helsinki, Helsinki Institute of Sustainability Science (HELSUS) and Helsinki Institute of Urban and Regional Studies (Urbaria), Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071) 
3  University of Helsinki, Digital Geography Lab, Department of Geosciences and Geography, Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071); Aalto University, Department of Built Environment, Espoo, Finland (GRID:grid.5373.2) (ISNI:0000000108389418); University College London, Centre for Advanced Spatial Analysis, London, United Kingdom (GRID:grid.83440.3b) (ISNI:0000000121901201) 
4  University of Helsinki, Digital Geography Lab, Department of Geosciences and Geography, Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071); Elisa Corporation, Helsinki, Finland (GRID:grid.7737.4) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-021-01113-4
ProQuest document ID
2625419155
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.