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A wildfire vulnerability index for buildings
Recent wildfire events (e.g. Mediterranean region, USA, and Australia) showed that this hazard poses a serious threat for wildland–urban interface (WUI) areas around the globe. Furthermore, recent events in regions where wildfire does not constitute a frequent hazard (e.g. Siberia, Scandinavia) indi...
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/PMC9013349/ https://www.ncbi.nlm.nih.gov/pubmed/35430626 http://dx.doi.org/10.1038/s41598-022-10479-3 |
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author | Papathoma-Köhle, M. Schlögl, M. Garlichs, C. Diakakis, M. Mavroulis, S. Fuchs, S. |
author_facet | Papathoma-Köhle, M. Schlögl, M. Garlichs, C. Diakakis, M. Mavroulis, S. Fuchs, S. |
author_sort | Papathoma-Köhle, M. |
collection | PubMed |
description | Recent wildfire events (e.g. Mediterranean region, USA, and Australia) showed that this hazard poses a serious threat for wildland–urban interface (WUI) areas around the globe. Furthermore, recent events in regions where wildfire does not constitute a frequent hazard (e.g. Siberia, Scandinavia) indicated that the spatial pattern of wildfire risk might have significantly changed. To prepare for upcoming extreme events, it is critical for decision-makers to have a thorough understanding of the vulnerability of the built environment to wildfire. Building quality and design standards are important not only because building loss is costly but also because robust buildings may offer shelter when evacuation is not possible. However, studies aiming at the analysis of wildfire vulnerability for the built environment are limited. This paper presents an innovative solution for the vulnerability assessment to wildfires, making use of an all-relevant feature selection algorithm established on statistical relationships to develop a physical vulnerability index for buildings subject to wildfire. Data from a recent and systematically documented wildfire event in Greece (Mati, 2018) are used to select and weight the relevant indicators using a permutation-based automated feature selection based on random forests. Building characteristics including the structural type, the roof type, material and shape, the inclination of the ground, the surrounding vegetation, the material of the shutters and the ground covering were selected and formed into the index. The index may be used in other places in Europe and beyond, especially where no empirical data are available supporting decision-making and risk reduction of an emerging hazard amplified by climate change. |
format | Online Article Text |
id | pubmed-9013349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90133492022-04-18 A wildfire vulnerability index for buildings Papathoma-Köhle, M. Schlögl, M. Garlichs, C. Diakakis, M. Mavroulis, S. Fuchs, S. Sci Rep Article Recent wildfire events (e.g. Mediterranean region, USA, and Australia) showed that this hazard poses a serious threat for wildland–urban interface (WUI) areas around the globe. Furthermore, recent events in regions where wildfire does not constitute a frequent hazard (e.g. Siberia, Scandinavia) indicated that the spatial pattern of wildfire risk might have significantly changed. To prepare for upcoming extreme events, it is critical for decision-makers to have a thorough understanding of the vulnerability of the built environment to wildfire. Building quality and design standards are important not only because building loss is costly but also because robust buildings may offer shelter when evacuation is not possible. However, studies aiming at the analysis of wildfire vulnerability for the built environment are limited. This paper presents an innovative solution for the vulnerability assessment to wildfires, making use of an all-relevant feature selection algorithm established on statistical relationships to develop a physical vulnerability index for buildings subject to wildfire. Data from a recent and systematically documented wildfire event in Greece (Mati, 2018) are used to select and weight the relevant indicators using a permutation-based automated feature selection based on random forests. Building characteristics including the structural type, the roof type, material and shape, the inclination of the ground, the surrounding vegetation, the material of the shutters and the ground covering were selected and formed into the index. The index may be used in other places in Europe and beyond, especially where no empirical data are available supporting decision-making and risk reduction of an emerging hazard amplified by climate change. Nature Publishing Group UK 2022-04-16 /pmc/articles/PMC9013349/ /pubmed/35430626 http://dx.doi.org/10.1038/s41598-022-10479-3 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 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 | Article Papathoma-Köhle, M. Schlögl, M. Garlichs, C. Diakakis, M. Mavroulis, S. Fuchs, S. A wildfire vulnerability index for buildings |
title | A wildfire vulnerability index for buildings |
title_full | A wildfire vulnerability index for buildings |
title_fullStr | A wildfire vulnerability index for buildings |
title_full_unstemmed | A wildfire vulnerability index for buildings |
title_short | A wildfire vulnerability index for buildings |
title_sort | wildfire vulnerability index for buildings |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013349/ https://www.ncbi.nlm.nih.gov/pubmed/35430626 http://dx.doi.org/10.1038/s41598-022-10479-3 |
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