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, Carlo Lavalle

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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.

Original languageEnglish
Article number4631
Pages (from-to)1-11
Number of pages11
JournalNature Communications
Volume11
Issue number1
DOIs
Publication statusPublished - 15 Sep 2020

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