A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland

被引:30
作者
Bergroth, Claudia [1 ,2 ]
Jarv, Olle [2 ,3 ,4 ]
Tenkanen, Henrikki [2 ,5 ,6 ]
Manninen, Matti [2 ,7 ]
Toivonen, Tuuli [2 ,3 ,4 ]
机构
[1] City Helsinki, Unit Urban Res & Stat, Siltasaarenkatu 18-20A, FI-00530 Helsinki, Finland
[2] Univ Helsinki, Dept Geosci & Geog, Digital Geog Lab, Gustaf Hallstromin Katu 2, FI-00014 Helsinki, Finland
[3] Univ Helsinki, Helsinki Inst Sustainabil Sci HELSUS, Yliopistonkatu 3, FI-00014 Helsinki, Finland
[4] Univ Helsinki, Helsinki Inst Urban & Reg Studies Urbaria, Yliopistonkatu 3, FI-00014 Helsinki, Finland
[5] Aalto Univ, Dept Built Environm, Otakaari 4, FI-00076 Espoo, Finland
[6] UCL, Ctr Adv Spatial Anal, 90 Tottenham Court Rd, London, England
[7] Elisa Corp, Helsinki, Finland
关键词
POSITIONING DATA; ACCESSIBILITY; IMPACT; MODEL;
D O I
10.1038/s41597-021-01113-4
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
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页数:19
相关论文
共 51 条
  • [1] 3GPP, 2018, 32410 3GPP TS
  • [2] Evaluating passive mobile positioning data for tourism surveys:: An Estonian case study
    Ahas, Rein
    Aasa, Anto
    Roose, Antti
    Mark, Uelar
    Silm, Siiri
    [J]. TOURISM MANAGEMENT, 2008, 29 (03) : 469 - 486
  • [3] Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones
    Ahas, Rein
    Silm, Siiri
    Jarv, Olle
    Saluveer, Erki
    Tiru, Margus
    [J]. JOURNAL OF URBAN TECHNOLOGY, 2010, 17 (01) : 3 - 27
  • [4] A spatio-temporal population model to support risk assessment and damage analysis for decision-making
    Ahola, Terhi
    Virrantaus, Kirsi
    Krisp, Jukka Matthias
    Hunter, Gary J.
    [J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2007, 21 (08) : 935 - 953
  • [5] Origin-destination trips by purpose and time of day inferred from mobile phone data
    Alexander, Lauren
    Jiang, Shan
    Murga, Mikel
    Gonzalez, Marta C.
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2015, 58 : 240 - 250
  • [6] [Anonymous], 2018, ICT facts and figures, 2016
  • [7] Bergroth C., 2021, 24 HOUR DYNAMIC POPU, DOI [10.5281/zenodo.4726996, DOI 10.5281/ZENODO.4726996]
  • [8] Bergroth C, 2019, UNCOVERING POPULATIO
  • [9] Bhaduri B, 2007, GEOJOURNAL, V69, P103, DOI 10.1007/s10708-007-9105-9
  • [10] Urban Sensing Using Mobile Phone Network Data: A Survey of Research
    Calabrese, Francesco
    Ferrari, Laura
    Blondel, Vincent D.
    [J]. ACM COMPUTING SURVEYS, 2015, 47 (02)