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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
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%.
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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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