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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...

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Autores principales: St. Denis, Lise A., Short, Karen C., McConnell, Kathryn, Cook, Maxwell C., Mietkiewicz, Nathan P., Buckland, Mollie, Balch, Jennifer K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
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.
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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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