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A spatially-explicit harmonized global dataset of critical infrastructure
Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are...
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/PMC8975875/ https://www.ncbi.nlm.nih.gov/pubmed/35365664 http://dx.doi.org/10.1038/s41597-022-01218-4 |
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author | Nirandjan, Sadhana Koks, Elco E. Ward, Philip J. Aerts, Jeroen C. J. H. |
author_facet | Nirandjan, Sadhana Koks, Elco E. Ward, Philip J. Aerts, Jeroen C. J. H. |
author_sort | Nirandjan, Sadhana |
collection | PubMed |
description | Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world’s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10 and 0.25 × 0.25 degrees. The dataset can be applied to explore the current landscape of CI, identify CI hotspots, and as exposure input for large-scale risk assessments. |
format | Online Article Text |
id | pubmed-8975875 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89758752022-04-20 A spatially-explicit harmonized global dataset of critical infrastructure Nirandjan, Sadhana Koks, Elco E. Ward, Philip J. Aerts, Jeroen C. J. H. Sci Data Data Descriptor Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world’s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10 and 0.25 × 0.25 degrees. The dataset can be applied to explore the current landscape of CI, identify CI hotspots, and as exposure input for large-scale risk assessments. Nature Publishing Group UK 2022-04-01 /pmc/articles/PMC8975875/ /pubmed/35365664 http://dx.doi.org/10.1038/s41597-022-01218-4 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 | Data Descriptor Nirandjan, Sadhana Koks, Elco E. Ward, Philip J. Aerts, Jeroen C. J. H. A spatially-explicit harmonized global dataset of critical infrastructure |
title | A spatially-explicit harmonized global dataset of critical infrastructure |
title_full | A spatially-explicit harmonized global dataset of critical infrastructure |
title_fullStr | A spatially-explicit harmonized global dataset of critical infrastructure |
title_full_unstemmed | A spatially-explicit harmonized global dataset of critical infrastructure |
title_short | A spatially-explicit harmonized global dataset of critical infrastructure |
title_sort | spatially-explicit harmonized global dataset of critical infrastructure |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8975875/ https://www.ncbi.nlm.nih.gov/pubmed/35365664 http://dx.doi.org/10.1038/s41597-022-01218-4 |
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