Abstract
ABSTRACTMulti-temporal, globally consistent, high-resolution human population datasets provide consistent and comparable population distributions in support of mapping sub-national heterogeneities in health, wealth, and resource access, and monitoring change in these over time. The production of more reliable and spatially detailed population datasets is increasingly necessary due to the importance of improving metrics at sub-national and multi-temporal scales. This is in support of measurement and monitoring of UN Sustainable Development Goals and related agendas. In response to these agendas, a method has been developed to assemble and harmonise a unique, open access, archive of geospatial datasets. Datasets are provided as global, annual time series, where pertinent at the timescale of population analyses and where data is available, for use in the construction of population distribution layers. The archive includes sub-national census-based population estimates, matched to a geospatial layer denoting administrative unit boundaries, and a number of co-registered gridded geospatial factors that correlate strongly with population presence and density. Here, we describe these harmonised datasets and their limitations, along with the production workflow. Further, we demonstrate applications of the archive by producing multi-temporal gridded population outputs for Africa and using these to derive health and development metrics. The geospatial archive is available at https://doi.org/10.5258/SOTON/WP00650.
Highlights
Human population mapping is fundamental in support of a broad range of applications by governments, non-governmental organisations, and private businesses
The time-invariant geospatialgeospatial layers produced as potential input grids for modelling population distribution are: Viewfinder Panoramas (SRTM based) topography for year 2000; a slope layer derived from the topography; pixel area (m2), and coastline; OpenStreetMap (OSM) highway, highway intersection, and waterway locations (OSMF and Contributors, 2016); and WorldClim average global temperature (°C) and precipitation for 1970–2000 (Fick & Hijmans, 2017)
For 2012 to 2016 we use VIIRS Cloud Mask (VCM) version 1 nighttime lights Day/Night Band (DNB) monthly composite time series (US NOAA, 2017) light intensity data, which is provided as inter-calibrated tiled raster layers with near global coverage between latitudes 75 degrees North and 65 degrees South
Summary
Human population mapping is fundamental in support of a broad range of applications by governments, non-governmental organisations, and private businesses. A larger number of covariates may be utilised in modelling in order to more effectively disaggregate census population counts within administrative units, and to better statistically describe population distribution (Lloyd, Sorichetta, & Tatem, 2017) – an approach used to produce the Landscan population datasets (ORNL 2010; Bhaduri, Bright, Coleman, & Urban, 2007; Dobson, Bright, Coleman, Durfee, & Worley, 2000). The newly assembled and harmonised layers, discussed here, mark a significant improvement by the inclusion of subnational census-based population estimates and by the utilisation of associated administrative boundaries These are the same input data as previously used in the production of the GPWv4 gridded datasets (CIESIN, 2016a, 2016b; Doxsey-Whitfield et al, 2015). We use the workflow described by Gaughan et al (2016) to compare population outputs for Africa at several time periods and demonstrate the potential usefulness of these high spatial resolution data in health and development metric applications
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