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All-hazards dataset mined from the US National Incident Management System 1999–2020
This paper describes a dataset mined from the public archive (1999–2020) of the US National Incident Management System Incident Status Summary (ICS-209) forms (a total of 187,160 reports for 35,170 incidents, including 34,478 wildland fires). This system captures detailed daily/regular information o...
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/PMC9958120/ https://www.ncbi.nlm.nih.gov/pubmed/36828905 http://dx.doi.org/10.1038/s41597-023-01955-0 |
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author | St. Denis, Lise A. Short, Karen C. McConnell, Kathryn Cook, Maxwell C. Mietkiewicz, Nathan P. Buckland, Mollie Balch, Jennifer K. |
author_facet | St. Denis, Lise A. Short, Karen C. McConnell, Kathryn Cook, Maxwell C. Mietkiewicz, Nathan P. Buckland, Mollie Balch, Jennifer K. |
author_sort | St. Denis, Lise A. |
collection | PubMed |
description | This paper describes a dataset mined from the public archive (1999–2020) of the US National Incident Management System Incident Status Summary (ICS-209) forms (a total of 187,160 reports for 35,170 incidents, including 34,478 wildland fires). This system captures detailed daily/regular information on incident development and response, including social and economic impacts. Most (98.4%) reports are wildland fire-related, with other incident types including hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use for research due to multiple record formats, inconsistent data entry, and no clean pathway from individual reports to high-level incident analysis. Here, we describe the open-source, reproducible methods used to produce a science-grade version of the data, including formal connections made to other published wildland fire data products. Among other applications, this integrated and spatially augmented dataset enables exploration of the daily progression of the most costly, damaging, and deadly environmental-hazard events in recent US history. |
format | Online Article Text |
id | pubmed-9958120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99581202023-02-26 All-hazards dataset mined from the US National Incident Management System 1999–2020 St. Denis, Lise A. Short, Karen C. McConnell, Kathryn Cook, Maxwell C. Mietkiewicz, Nathan P. Buckland, Mollie Balch, Jennifer K. Sci Data Data Descriptor This paper describes a dataset mined from the public archive (1999–2020) of the US National Incident Management System Incident Status Summary (ICS-209) forms (a total of 187,160 reports for 35,170 incidents, including 34,478 wildland fires). This system captures detailed daily/regular information on incident development and response, including social and economic impacts. Most (98.4%) reports are wildland fire-related, with other incident types including hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use for research due to multiple record formats, inconsistent data entry, and no clean pathway from individual reports to high-level incident analysis. Here, we describe the open-source, reproducible methods used to produce a science-grade version of the data, including formal connections made to other published wildland fire data products. Among other applications, this integrated and spatially augmented dataset enables exploration of the daily progression of the most costly, damaging, and deadly environmental-hazard events in recent US history. Nature Publishing Group UK 2023-02-24 /pmc/articles/PMC9958120/ /pubmed/36828905 http://dx.doi.org/10.1038/s41597-023-01955-0 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 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 St. Denis, Lise A. Short, Karen C. McConnell, Kathryn Cook, Maxwell C. Mietkiewicz, Nathan P. Buckland, Mollie Balch, Jennifer K. All-hazards dataset mined from the US National Incident Management System 1999–2020 |
title | All-hazards dataset mined from the US National Incident Management System 1999–2020 |
title_full | All-hazards dataset mined from the US National Incident Management System 1999–2020 |
title_fullStr | All-hazards dataset mined from the US National Incident Management System 1999–2020 |
title_full_unstemmed | All-hazards dataset mined from the US National Incident Management System 1999–2020 |
title_short | All-hazards dataset mined from the US National Incident Management System 1999–2020 |
title_sort | all-hazards dataset mined from the us national incident management system 1999–2020 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9958120/ https://www.ncbi.nlm.nih.gov/pubmed/36828905 http://dx.doi.org/10.1038/s41597-023-01955-0 |
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