Uncovering temporal changes in Europe’s population density patterns using a data fusion approach

The knowledge of the spatial and temporal distribution of human population is vital for the study of cities, disaster risk management or planning of infrastructure. However, information on the distribution of population is often based on place-of-residence statistics from official sources, thus igno...

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Bibliographic Details
Published in:Nature communications 2020-09, Vol.11 (1), p.4631-4631, Article 4631
Main Authors: Batista e Silva, Filipe, Freire, Sérgio, Schiavina, Marcello, Rosina, Konštantín, Marín-Herrera, Mario Alberto, Ziemba, Lukasz, Craglia, Massimo, Koomen, Eric, Lavalle, Carlo
Format: Article
Language:English
Subjects:
639/705/1046
704/844
706/2808
City centres
Data integration
Disaster management
Emergency preparedness
Human populations
Humanities and Social Sciences
Mobility
multidisciplinary
Multilayers
Population (statistical)
Population density
Population distribution
Population statistics
Risk management
Science
Science (multidisciplinary)
Spatial data
Statistics
Temporal distribution
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Summary:The knowledge of the spatial and temporal distribution of human population is vital for the study of cities, disaster risk management or planning of infrastructure. However, information on the distribution of population is often based on place-of-residence statistics from official sources, thus ignoring the changing population densities resulting from human mobility. Existing assessments of spatio-temporal population are limited in their detail and geographical coverage, and the promising mobile-phone records are hindered by issues concerning availability and consistency. Here, we present a multi-layered dasymetric approach that combines official statistics with geospatial data from emerging sources to produce and validate a European Union-wide dataset of population grids taking into account intraday and monthly population variations at 1 km 2 resolution. The results reproduce and systematically quantify known insights concerning the spatio-temporal population density structure of large European cities, whose daytime population we estimate to be, on average, 1.9 times higher than night time in city centers. Official data on the distribution of human population often ignores the changing spatio-temporal densities resulting from mobility. Here, authors apply an approach combining official statistics and geospatial data to assess intraday and monthly population variations at continental scale at 1 km 2 resolution.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-020-18344-5