View in EDS HTML Full Text PDF Full Text

Global high-resolution estimates of the UN Human Development Index using satellite imagery and machine learning.

Saved in:
Bibliographic Details
Title: Global high-resolution estimates of the UN Human Development Index using satellite imagery and machine learning.
Authors: Sherman L; Global Policy Laboratory, Stanford Doerr School of Sustainability, Stanford University, Stanford, CA, USA., Proctor J; Food and Resource Economics, Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, Canada. jon.proctor@ubc.ca., Druckenmiller H; Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA.; National Bureau of Economic Research, Cambridge, MA, USA., Tapia H; Human Development Report Office, United Nations Development Programme, New York, NY, USA., Hsiang S; Global Policy Laboratory, Stanford Doerr School of Sustainability, Stanford University, Stanford, CA, USA.; National Bureau of Economic Research, Cambridge, MA, USA.
Source: Nature communications [Nat Commun] 2026 Feb 17; Vol. 17 (1), pp. 1315. Date of Electronic Publication: 2026 Feb 17.
Publication Type: Journal Article
Journal Info: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41702909
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Global high-resolution estimates of the UN Human Development Index using satellite imagery and machine learning.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Sherman+L%22">Sherman L</searchLink>; Global Policy Laboratory, Stanford Doerr School of Sustainability, Stanford University, Stanford, CA, USA.<br /><searchLink fieldCode="AU" term="%22Proctor+J%22">Proctor J</searchLink>; Food and Resource Economics, Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, Canada. jon.proctor@ubc.ca.<br /><searchLink fieldCode="AU" term="%22Druckenmiller+H%22">Druckenmiller H</searchLink>; Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA.; National Bureau of Economic Research, Cambridge, MA, USA.<br /><searchLink fieldCode="AU" term="%22Tapia+H%22">Tapia H</searchLink>; Human Development Report Office, United Nations Development Programme, New York, NY, USA.<br /><searchLink fieldCode="AU" term="%22Hsiang+S%22">Hsiang S</searchLink>; Global Policy Laboratory, Stanford Doerr School of Sustainability, Stanford University, Stanford, CA, USA.; National Bureau of Economic Research, Cambridge, MA, USA.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101528555%22">Nature communications</searchLink> [Nat Commun] 2026 Feb 17; Vol. 17 (1), pp. 1315. <i>Date of Electronic Publication: </i>2026 Feb 17.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Pub%2E+Group%22">Nature Pub. Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101528555 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2041-1723 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220411723%22">20411723 </searchLink><i>NLM ISO Abbreviation: </i>Nat Commun <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41702909
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1038/s41467-026-68805-6
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 1315
    Titles:
      – TitleFull: Global high-resolution estimates of the UN Human Development Index using satellite imagery and machine learning.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Sherman L
      – PersonEntity:
          Name:
            NameFull: Proctor J
      – PersonEntity:
          Name:
            NameFull: Druckenmiller H
      – PersonEntity:
          Name:
            NameFull: Tapia H
      – PersonEntity:
          Name:
            NameFull: Hsiang S
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 17
              M: 02
              Text: 2026 Feb 17
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 2041-1723
          Numbering:
            – Type: volume
              Value: 17
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Nature communications
              Type: main
ResultId 1