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High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100
We present a novel, global 30 arc seconds (∼1 km at the equator) population projection dataset covering each year from 2010 to 2100 that is consistent with both country level population and gridded urban fractions from the Coupled Model Intercomparison Project 6 (CMIP6). While IPCC population projec...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762352/ https://www.ncbi.nlm.nih.gov/pubmed/35071702 http://dx.doi.org/10.1016/j.dib.2022.107804 |
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author | Olén, Niklas Boke Lehsten, Veiko |
author_facet | Olén, Niklas Boke Lehsten, Veiko |
author_sort | Olén, Niklas Boke |
collection | PubMed |
description | We present a novel, global 30 arc seconds (∼1 km at the equator) population projection dataset covering each year from 2010 to 2100 that is consistent with both country level population and gridded urban fractions from the Coupled Model Intercomparison Project 6 (CMIP6). While IPCC population projections until 2100 are available at country level for Socio-Economic Pathways (SSPs), land cover (including the urban fraction) is only available for Representative Concentration Pathways (RCPs). To perform simulations of e.g., future supply and demand for agricultural products, fine scale projections of population density are needed for combinations of SSPs and RCPs. Therefore, we generated a 30 arc seconds dataset consistent with both SSPs and RCPs within the framework of the IPCC. This data set is useful in applications where spatially explicit projections of aspects of global change are investigated at a fine spatial scale. For example, if a link function between night-time lights and population density is found based on current satellite images and recent population density data, a projection of night-time light lights can be generated by using this link function with our projected population density. Such a projection can for example be used to evaluate the potential for future light pollution. |
format | Online Article Text |
id | pubmed-8762352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-87623522022-01-20 High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100 Olén, Niklas Boke Lehsten, Veiko Data Brief Data Article We present a novel, global 30 arc seconds (∼1 km at the equator) population projection dataset covering each year from 2010 to 2100 that is consistent with both country level population and gridded urban fractions from the Coupled Model Intercomparison Project 6 (CMIP6). While IPCC population projections until 2100 are available at country level for Socio-Economic Pathways (SSPs), land cover (including the urban fraction) is only available for Representative Concentration Pathways (RCPs). To perform simulations of e.g., future supply and demand for agricultural products, fine scale projections of population density are needed for combinations of SSPs and RCPs. Therefore, we generated a 30 arc seconds dataset consistent with both SSPs and RCPs within the framework of the IPCC. This data set is useful in applications where spatially explicit projections of aspects of global change are investigated at a fine spatial scale. For example, if a link function between night-time lights and population density is found based on current satellite images and recent population density data, a projection of night-time light lights can be generated by using this link function with our projected population density. Such a projection can for example be used to evaluate the potential for future light pollution. Elsevier 2022-01-06 /pmc/articles/PMC8762352/ /pubmed/35071702 http://dx.doi.org/10.1016/j.dib.2022.107804 Text en © 2022 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Olén, Niklas Boke Lehsten, Veiko High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100 |
title | High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100 |
title_full | High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100 |
title_fullStr | High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100 |
title_full_unstemmed | High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100 |
title_short | High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100 |
title_sort | high-resolution global population projections dataset developed with cmip6 rcp and ssp scenarios for year 2010–2100 |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762352/ https://www.ncbi.nlm.nih.gov/pubmed/35071702 http://dx.doi.org/10.1016/j.dib.2022.107804 |
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