High-resolution gridded population datasets for Latin America and the Caribbean in 2010, 2015, and 2020.
Identifieur interne : 000030 ( PubMed/Curation ); précédent : 000029; suivant : 000031High-resolution gridded population datasets for Latin America and the Caribbean in 2010, 2015, and 2020.
Auteurs : Alessandro Sorichetta [Royaume-Uni] ; Graeme M. Hornby [Royaume-Uni] ; Forrest R. Stevens [États-Unis] ; Andrea E. Gaughan [États-Unis] ; Catherine Linard [Belgique] ; Andrew J. Tatem [Suède]Source :
- Scientific data ; 2015.
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Abstract
The Latin America and the Caribbean region is one of the most urbanized regions in the world, with a total population of around 630 million that is expected to increase by 25% by 2050. In this context, detailed and contemporary datasets accurately describing the distribution of residential population in the region are required for measuring the impacts of population growth, monitoring changes, supporting environmental and health applications, and planning interventions. To support these needs, an open access archive of high-resolution gridded population datasets was created through disaggregation of the most recent official population count data available for 28 countries located in the region. These datasets are described here along with the approach and methods used to create and validate them. For each country, population distribution datasets, having a resolution of 3 arc seconds (approximately 100 m at the equator), were produced for the population count year, as well as for 2010, 2015, and 2020. All these products are available both through the WorldPop Project website and the WorldPop Dataverse Repository.
DOI: 10.1038/sdata.2015.45
PubMed: 26347245
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Gaughan</name><affiliation wicri:level="1"><nlm:affiliation>Department of Geography and Geosciences, University of Louisville , Louisville, KY 40292, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Geography and Geosciences, University of Louisville , Louisville, KY 40292</wicri:regionArea></affiliation></author><author><name sortKey="Linard, Catherine" sort="Linard, Catherine" uniqKey="Linard C" first="Catherine" last="Linard">Catherine Linard</name><affiliation wicri:level="1"><nlm:affiliation>Lutte biologique et Ecologie spatiale (LUBIES), Université Libre de Bruxelles , CP 160/12, 50 Avenue F.D. Roosevelt, Bruxelles B-1050, Belgium ; Fonds National de la Recherche Scientifique , 5 rue d'Egmont, Bruxelles B-1000, Belgium.</nlm:affiliation><country xml:lang="fr">Belgique</country><wicri:regionArea>Lutte biologique et Ecologie spatiale (LUBIES), Université Libre de Bruxelles , CP 160/12, 50 Avenue F.D. 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In this context, detailed and contemporary datasets accurately describing the distribution of residential population in the region are required for measuring the impacts of population growth, monitoring changes, supporting environmental and health applications, and planning interventions. To support these needs, an open access archive of high-resolution gridded population datasets was created through disaggregation of the most recent official population count data available for 28 countries located in the region. These datasets are described here along with the approach and methods used to create and validate them. For each country, population distribution datasets, having a resolution of 3 arc seconds (approximately 100 m at the equator), were produced for the population count year, as well as for 2010, 2015, and 2020. All these products are available both through the WorldPop Project website and the WorldPop Dataverse Repository.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26347245</PMID><DateCreated><Year>2015</Year><Month>9</Month><Day>8</Day></DateCreated><DateCompleted><Year>2015</Year><Month>12</Month><Day>29</Day></DateCompleted><DateRevised><Year>2016</Year><Month>10</Month><Day>19</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><JournalIssue CitedMedium="Print"><Volume>2</Volume><PubDate><Year>2015</Year></PubDate></JournalIssue><Title>Scientific data</Title><ISOAbbreviation>Sci Data</ISOAbbreviation></Journal><ArticleTitle>High-resolution gridded population datasets for Latin America and the Caribbean in 2010, 2015, and 2020.</ArticleTitle><Pagination><MedlinePgn>150045</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1038/sdata.2015.45</ELocationID><Abstract><AbstractText>The Latin America and the Caribbean region is one of the most urbanized regions in the world, with a total population of around 630 million that is expected to increase by 25% by 2050. In this context, detailed and contemporary datasets accurately describing the distribution of residential population in the region are required for measuring the impacts of population growth, monitoring changes, supporting environmental and health applications, and planning interventions. To support these needs, an open access archive of high-resolution gridded population datasets was created through disaggregation of the most recent official population count data available for 28 countries located in the region. These datasets are described here along with the approach and methods used to create and validate them. For each country, population distribution datasets, having a resolution of 3 arc seconds (approximately 100 m at the equator), were produced for the population count year, as well as for 2010, 2015, and 2020. 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Roosevelt, Bruxelles B-1050, Belgium ; Fonds National de la Recherche Scientifique , 5 rue d'Egmont, Bruxelles B-1000, Belgium.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tatem</LastName><ForeName>Andrew J</ForeName><Initials>AJ</Initials><AffiliationInfo><Affiliation>Geography and Environment, University of Southampton, Highfield Campus , Southampton SO17 1BJ, UK ; Fogarty International Center, National Institutes of Health , 16 Center Drive, Bethesda, MD 20892, USA ; Flowminder Foundation , Roslagsgatan 17 SE-11355, Stockholm, Sweden.</Affiliation></AffiliationInfo></Author></AuthorList><Language>ENG</Language><DataBankList CompleteYN="Y"><DataBank><DataBankName>figshare</DataBankName><AccessionNumberList><AccessionNumber>10.6084/M9.FIGSHARE.1491490</AccessionNumber></AccessionNumberList></DataBank></DataBankList><GrantList CompleteYN="Y"><Grant><GrantID>U19 AI089674</GrantID><Acronym>AI</Acronym><Agency>NIAID NIH HHS</Agency><Country>United 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2011;6(6):e20578</RefSource><PMID Version="1">21687675</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2011 Apr 12;108(15):6312-7</RefSource><PMID Version="1">21444797</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2007;2(12):e1298</RefSource><PMID Version="1">18074022</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Biol Rev Camb Philos Soc. 2007 Nov;82(4):607-45</RefSource><PMID Version="1">17944620</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2013;8(2):e55882</RefSource><PMID Version="1">23418469</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 1998 Nov 24;95(24):14009-14</RefSource><PMID Version="1">9826643</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Int J Popul Geogr. 1997 Sep;3(3):203-25</RefSource><PMID Version="1">12348289</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2015;10(2):e0107042</RefSource><PMID Version="1">25689585</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2012;7(2):e31743</RefSource><PMID Version="1">22363717</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Adv Parasitol. 2006;62:119-56</RefSource><PMID Version="1">16647969</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName UI="D017691" MajorTopicYN="N" Type="Geographic">Caribbean Region</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004777" MajorTopicYN="N">Environment</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006285" MajorTopicYN="N">Health Planning</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007843" 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