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United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response
The Federal Emergency Management Agency (FEMA) divides the United States (US) into ten standard regions to promote local partnerships and priorities. These divisions, while longstanding, do not adequately address known hazard risk as reflected in past federal disaster declarations. From FEMA’s incep...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9838517/ https://www.ncbi.nlm.nih.gov/pubmed/36685108 http://dx.doi.org/10.1007/s11069-023-05817-1 |
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author | Margus, Colton Hertelendy, Attila Tao, Yudong Coltey, Erik Chen, Shu-Ching Luis, Steven Shyu, Mei-Ling Ciottone, Gregory R. |
author_facet | Margus, Colton Hertelendy, Attila Tao, Yudong Coltey, Erik Chen, Shu-Ching Luis, Steven Shyu, Mei-Ling Ciottone, Gregory R. |
author_sort | Margus, Colton |
collection | PubMed |
description | The Federal Emergency Management Agency (FEMA) divides the United States (US) into ten standard regions to promote local partnerships and priorities. These divisions, while longstanding, do not adequately address known hazard risk as reflected in past federal disaster declarations. From FEMA’s inception in 1979 until 2020, the OpenFEMA dataset reports 4127 natural disaster incidents declared by 53 distinct state-level jurisdictions, listed by disaster location, type, and year. An unsupervised spectral clustering (SC) algorithm was applied to group these jurisdictions into regions based on affinity scores assigned to each pair of jurisdictions accounting for both geographic proximity and historical disaster exposures. Reassigning jurisdictions to ten regions using the proposed SC algorithm resulted in an adjusted Rand index (ARI) of 0.43 when compared with the existing FEMA regional structure, indicating little similarity between the current FEMA regions and the clustering results. Reassigning instead into six regions substantially improved cluster quality with a maximized silhouette score of 0.42, compared to a score of 0.34 for ten regions. In clustering US jurisdictions not only by geographic proximity but also by the myriad hazards faced in relation to one another, this study demonstrates a novel method for FEMA regional allocation and design that may ultimately improve FEMA disaster specialization and response. |
format | Online Article Text |
id | pubmed-9838517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-98385172023-01-17 United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response Margus, Colton Hertelendy, Attila Tao, Yudong Coltey, Erik Chen, Shu-Ching Luis, Steven Shyu, Mei-Ling Ciottone, Gregory R. Nat Hazards (Dordr) Original Paper The Federal Emergency Management Agency (FEMA) divides the United States (US) into ten standard regions to promote local partnerships and priorities. These divisions, while longstanding, do not adequately address known hazard risk as reflected in past federal disaster declarations. From FEMA’s inception in 1979 until 2020, the OpenFEMA dataset reports 4127 natural disaster incidents declared by 53 distinct state-level jurisdictions, listed by disaster location, type, and year. An unsupervised spectral clustering (SC) algorithm was applied to group these jurisdictions into regions based on affinity scores assigned to each pair of jurisdictions accounting for both geographic proximity and historical disaster exposures. Reassigning jurisdictions to ten regions using the proposed SC algorithm resulted in an adjusted Rand index (ARI) of 0.43 when compared with the existing FEMA regional structure, indicating little similarity between the current FEMA regions and the clustering results. Reassigning instead into six regions substantially improved cluster quality with a maximized silhouette score of 0.42, compared to a score of 0.34 for ten regions. In clustering US jurisdictions not only by geographic proximity but also by the myriad hazards faced in relation to one another, this study demonstrates a novel method for FEMA regional allocation and design that may ultimately improve FEMA disaster specialization and response. Springer Netherlands 2023-01-12 2023 /pmc/articles/PMC9838517/ /pubmed/36685108 http://dx.doi.org/10.1007/s11069-023-05817-1 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Margus, Colton Hertelendy, Attila Tao, Yudong Coltey, Erik Chen, Shu-Ching Luis, Steven Shyu, Mei-Ling Ciottone, Gregory R. United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response |
title | United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response |
title_full | United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response |
title_fullStr | United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response |
title_full_unstemmed | United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response |
title_short | United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response |
title_sort | united states federal emergency management agency regional clustering by disaster exposure: a new paradigm for disaster response |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9838517/ https://www.ncbi.nlm.nih.gov/pubmed/36685108 http://dx.doi.org/10.1007/s11069-023-05817-1 |
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