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High resolution global gridded data for use in population studies
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 layer...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5283062/ https://www.ncbi.nlm.nih.gov/pubmed/28140386 http://dx.doi.org/10.1038/sdata.2017.1 |
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author | Lloyd, Christopher T. Sorichetta, Alessandro Tatem, Andrew J. |
author_facet | Lloyd, Christopher T. Sorichetta, Alessandro Tatem, Andrew J. |
author_sort | Lloyd, Christopher T. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5283062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52830622017-02-02 High resolution global gridded data for use in population studies Lloyd, Christopher T. Sorichetta, Alessandro Tatem, Andrew J. Sci Data Data Descriptor 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. Nature Publishing Group 2017-01-31 /pmc/articles/PMC5283062/ /pubmed/28140386 http://dx.doi.org/10.1038/sdata.2017.1 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse. |
spellingShingle | Data Descriptor Lloyd, Christopher T. Sorichetta, Alessandro Tatem, Andrew J. High resolution global gridded data for use in population studies |
title | High resolution global gridded data for use in population studies |
title_full | High resolution global gridded data for use in population studies |
title_fullStr | High resolution global gridded data for use in population studies |
title_full_unstemmed | High resolution global gridded data for use in population studies |
title_short | High resolution global gridded data for use in population studies |
title_sort | high resolution global gridded data for use in population studies |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5283062/ https://www.ncbi.nlm.nih.gov/pubmed/28140386 http://dx.doi.org/10.1038/sdata.2017.1 |
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