While 3.0 billion people lived on Earth in 1960, this is anticipated to reach approximately 10.0 billion by 2060. Within the last decades, global population increased rapidly. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. We acknowledge support by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin. įunding: FS, DF and PH have received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Data used in this study are publicly available and referenced in the paper: Building density and height: 10.5281/zenodo.4066294 Building types: 10.5281/zenodo.4601219 Gridded population maps: 10.5281/zenodo.4601292 Currently, selected mapping results can already be interactively explored here for a visual impression. Received: NovemAccepted: MaPublished: March 26, 2021Ĭopyright: © 2021 Schug et al.

PLoS ONE 16(3):Įditor: Krishna Prasad Vadrevu, University of Maryland at College Park, UNITED STATES 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.Ĭitation: Schug F, Frantz D, van der Linden S, Hostert P (2021) Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates. 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. Most importantly, we found that the combined use of density and height, i.e.

Building density improved the overall quality of population estimates at all scales compared to using a binary building layer. We found that integrating building types into dasymetric mapping is helpful at fine scale, as population is not redistributed to non-residential areas. We finally performed a nation-wide bottom-up population estimate based on the three datasets. We then examined the impact of different weighting layers from density, type and height on top-down dasymetric mapping quality across scales. We first produced and validated a nation-wide dataset of predominant residential and non-residential building types. 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. See Iowa precinct result maps published by The Times in 20.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. These are only estimates, and they may not be informed by reports from election officials.

The Times publishes its own estimates for the number of remaining votes, based on historic turnout data and reporting from results providers. The classification of areas as urban, rural or suburban is derived from research by Jed Kolko.Ĭhris Christie dropped out of the presidential race last week, but the Iowa Republican Party will still tabulate any votes he receives in the caucuses.Įlection results are from The Associated Press. Areas with more college graduates are precincts where more than 40 percent of the population has a college education areas with fewer college graduates are precincts where less than 15 percent of the population graduated college. Higher income areas are precincts where the median household income is $100,000 or more lower income areas are where the median household income is less than $50,000.

Us population density high res map