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Estimating global economic well-being with unlit settlements
It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development – with unlit areas typically being disregarded. Here we combine s...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9072384/ https://www.ncbi.nlm.nih.gov/pubmed/35513376 http://dx.doi.org/10.1038/s41467-022-30099-9 |
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author | McCallum, Ian Kyba, Christopher Conrad Maximillian Bayas, Juan Carlos Laso Moltchanova, Elena Cooper, Matt Cuaresma, Jesus Crespo Pachauri, Shonali See, Linda Danylo, Olga Moorthy, Inian Lesiv, Myroslava Baugh, Kimberly Elvidge, Christopher D. Hofer, Martin Fritz, Steffen |
author_facet | McCallum, Ian Kyba, Christopher Conrad Maximillian Bayas, Juan Carlos Laso Moltchanova, Elena Cooper, Matt Cuaresma, Jesus Crespo Pachauri, Shonali See, Linda Danylo, Olga Moorthy, Inian Lesiv, Myroslava Baugh, Kimberly Elvidge, Christopher D. Hofer, Martin Fritz, Steffen |
author_sort | McCallum, Ian |
collection | PubMed |
description | It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development – with unlit areas typically being disregarded. Here we combine satellite nighttime lights and the world settlement footprint for the year 2015 to show that 19% of the total settlement footprint of the planet had no detectable artificial radiance associated with it. The majority of unlit settlement footprints are found in Africa (39%), rising to 65% if we consider only rural settlement areas, along with numerous countries in the Middle East and Asia. Significant areas of unlit settlements are also located in some developed countries. For 49 countries spread across Africa, Asia and the Americas we are able to predict and map the wealth class obtained from ~2,400,000 geo-located households based upon the percent of unlit settlements, with an overall accuracy of 87%. |
format | Online Article Text |
id | pubmed-9072384 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90723842022-05-07 Estimating global economic well-being with unlit settlements McCallum, Ian Kyba, Christopher Conrad Maximillian Bayas, Juan Carlos Laso Moltchanova, Elena Cooper, Matt Cuaresma, Jesus Crespo Pachauri, Shonali See, Linda Danylo, Olga Moorthy, Inian Lesiv, Myroslava Baugh, Kimberly Elvidge, Christopher D. Hofer, Martin Fritz, Steffen Nat Commun Article It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development – with unlit areas typically being disregarded. Here we combine satellite nighttime lights and the world settlement footprint for the year 2015 to show that 19% of the total settlement footprint of the planet had no detectable artificial radiance associated with it. The majority of unlit settlement footprints are found in Africa (39%), rising to 65% if we consider only rural settlement areas, along with numerous countries in the Middle East and Asia. Significant areas of unlit settlements are also located in some developed countries. For 49 countries spread across Africa, Asia and the Americas we are able to predict and map the wealth class obtained from ~2,400,000 geo-located households based upon the percent of unlit settlements, with an overall accuracy of 87%. Nature Publishing Group UK 2022-05-05 /pmc/articles/PMC9072384/ /pubmed/35513376 http://dx.doi.org/10.1038/s41467-022-30099-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article McCallum, Ian Kyba, Christopher Conrad Maximillian Bayas, Juan Carlos Laso Moltchanova, Elena Cooper, Matt Cuaresma, Jesus Crespo Pachauri, Shonali See, Linda Danylo, Olga Moorthy, Inian Lesiv, Myroslava Baugh, Kimberly Elvidge, Christopher D. Hofer, Martin Fritz, Steffen Estimating global economic well-being with unlit settlements |
title | Estimating global economic well-being with unlit settlements |
title_full | Estimating global economic well-being with unlit settlements |
title_fullStr | Estimating global economic well-being with unlit settlements |
title_full_unstemmed | Estimating global economic well-being with unlit settlements |
title_short | Estimating global economic well-being with unlit settlements |
title_sort | estimating global economic well-being with unlit settlements |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9072384/ https://www.ncbi.nlm.nih.gov/pubmed/35513376 http://dx.doi.org/10.1038/s41467-022-30099-9 |
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