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Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates / Franz Schug in Plos one, vol 16 n° 3 (March 2021)  

Public [article]  inPlos one > vol 16 n° 3 (March 2021) . - n° 0249044 Titre : Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates Type de document : Article/Communication Auteurs : Franz Schug, Auteur ; David Frantz, Auteur ; Sebastian van der Linden, Auteur ; Patrick Hostert, Auteur Année de publication : 2021 Article en page(s) : n° 0249044 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Allemagne [Termes IGN] bati [Termes IGN] densité du bâti [Termes IGN] estimation statistique [Termes IGN] figuration de la densité [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] population Résumé : (auteur) Gridded population data is widely used to map fine scale population patterns and dynamics to understand associated human-environmental processes for global change research, disaster risk assessment and other domains. This study mapped gridded population across Germany using weighting layers from building density, building height (both from previous studies) and building type datasets, all created from freely available, temporally and globally consistent Copernicus Sentinel-1 and Sentinel-2 data. We first produced and validated a nation-wide dataset of predominant residential and non-residential building types. We then examined the impact of different weighting layers from density, type and height on top-down dasymetric mapping quality across scales. We finally performed a nation-wide bottom-up population estimate based on the three datasets. We found that integrating building types into dasymetric mapping is helpful at fine scale, as population is not redistributed to non-residential areas. Building density improved the overall quality of population estimates at all scales compared to using a binary building layer. Most importantly, we found that the combined use of density and height, i.e. volume, considerably increased mapping quality in general and with regard to regional discrepancy by largely eliminating systematic underestimation in dense agglomerations and overestimation in rural areas. We also found that building density, type and volume, together with living floor area per capita, are suitable to produce accurate large-area bottom-up population estimates. Numéro de notice : A2021-305 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1371/journal.pone.0249044 Date de publication en ligne : 26/03/2021 En ligne : https://doi.org/10.1371/journal.pone.0249044 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97654 [article]