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

Filipe Batista e Silva, Sérgio Freire, Marcello Schiavina, Konštantín Rosina, Mario Alberto Marín-Herrera, Lukasz Ziemba, Massimo Craglia, Eric Koomen () and Carlo Lavalle
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Sérgio Freire: European Commission, Joint Research Centre
Marcello Schiavina: European Commission, Joint Research Centre
Konštantín Rosina: European Commission, Joint Research Centre
Mario Alberto Marín-Herrera: European Commission, Joint Research Centre
Lukasz Ziemba: European Commission, Joint Research Centre
Massimo Craglia: European Commission, Joint Research Centre
Carlo Lavalle: European Commission, Joint Research Centre

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: Abstract 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 km2 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.

Date: 2020
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DOI: 10.1038/s41467-020-18344-5

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Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18344-5