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A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals
Effectively supporting the United Nations’ Sustainable Development Goals requires reliable, substantial, and timely data. For solar panel installation monitoring, where accurate reporting is crucial in tracking green energy production and sustainable energy access, official and regulated documentati...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10509230/ https://www.ncbi.nlm.nih.gov/pubmed/37726296 http://dx.doi.org/10.1038/s41597-023-02539-8 |
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author | Clark, Cecilia N. Pacifici, Fabio |
author_facet | Clark, Cecilia N. Pacifici, Fabio |
author_sort | Clark, Cecilia N. |
collection | PubMed |
description | Effectively supporting the United Nations’ Sustainable Development Goals requires reliable, substantial, and timely data. For solar panel installation monitoring, where accurate reporting is crucial in tracking green energy production and sustainable energy access, official and regulated documentation remains inconsistent. Reports of solar panel installations have been supplemented with object detection models developed and used on openly available aerial imagery, a type of imagery collected by aircraft or drones and limited by cost, extent, and geographic location. We address these limitations by providing a solar panel dataset derived from 31 cm resolution satellite imagery to support rapid and accurate detection at regional and international scales. We also include complementary satellite imagery at 15.5 cm resolution with the aim of further improving solar panel detection accuracy. The dataset of 2,542 annotated solar panels may be used independently to develop detection models uniquely applicable to satellite imagery or in conjunction with existing solar panel aerial imagery datasets to support generalized detection models. |
format | Online Article Text |
id | pubmed-10509230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105092302023-09-21 A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals Clark, Cecilia N. Pacifici, Fabio Sci Data Data Descriptor Effectively supporting the United Nations’ Sustainable Development Goals requires reliable, substantial, and timely data. For solar panel installation monitoring, where accurate reporting is crucial in tracking green energy production and sustainable energy access, official and regulated documentation remains inconsistent. Reports of solar panel installations have been supplemented with object detection models developed and used on openly available aerial imagery, a type of imagery collected by aircraft or drones and limited by cost, extent, and geographic location. We address these limitations by providing a solar panel dataset derived from 31 cm resolution satellite imagery to support rapid and accurate detection at regional and international scales. We also include complementary satellite imagery at 15.5 cm resolution with the aim of further improving solar panel detection accuracy. The dataset of 2,542 annotated solar panels may be used independently to develop detection models uniquely applicable to satellite imagery or in conjunction with existing solar panel aerial imagery datasets to support generalized detection models. Nature Publishing Group UK 2023-09-20 /pmc/articles/PMC10509230/ /pubmed/37726296 http://dx.doi.org/10.1038/s41597-023-02539-8 Text en © The Author(s) 2023 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Clark, Cecilia N. Pacifici, Fabio A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals |
title | A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals |
title_full | A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals |
title_fullStr | A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals |
title_full_unstemmed | A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals |
title_short | A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals |
title_sort | solar panel dataset of very high resolution satellite imagery to support the sustainable development goals |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10509230/ https://www.ncbi.nlm.nih.gov/pubmed/37726296 http://dx.doi.org/10.1038/s41597-023-02539-8 |
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