reference : High resolution global gridded data for use in population studies

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reftype Journal Article
Abstract Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end the WorldPop Project has produced an open access archive of 3 and 30 arc-second resolution gridded data. Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include transport networks, landcover, nightlights, precipitation, travel time to major cities, and waterways. Datasets and production methodology are here described. The archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website.
Accession Number 28140386
Author Lloyd, C. T.; Sorichetta, A.; Tatem, A. J.
Author Address WorldPop, Geography and Environment, University of Southampton, Highfield Campus, Southampton SO17 1BJ, UK. Flowminder Foundation, Roslagsgatan 17, Stockholm SE-11355, Sweden.
DOI 10.1038/sdata.2017.1
Date Jan 31
ISSN 2052-4463 (Electronic) 2052-4463 (Linking)
Journal Sci Data
Keywords Databases, Factual; Datasets as Topic; Humans; *Population Dynamics
Notes Lloyd, Christopher T Sorichetta, Alessandro Tatem, Andrew J eng U19 AI089674/AI/NIAID NIH HHS/ Wellcome Trust/United Kingdom Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't England 2017/02/01 06:00 Sci Data. 2017 Jan 31;4:170001. doi: 10.1038/sdata.2017.1.
PMCID PMC5283062
Pages 170001
Title High resolution global gridded data for use in population studies
Volume 4
Year 2017
Bibliographic identifiers
_record_number 46
_uuid c572e893-0f28-4ed7-b331-f2e736e9730e