Global high-resolution estimates of the UN Human Development Index using satellite imagery and machine learning.
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| Title: | Global high-resolution estimates of the UN Human Development Index using satellite imagery and machine learning. |
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| 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 |
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| ISSN: | 2041-1723 |
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| DOI: | 10.1038/s41467-026-68805-6 |
