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Block-level vulnerability assessment reveals disproportionate impacts of natural hazards across the conterminous United States

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dc.contributor.authorYarveysi, Farnaz
dc.contributor.authorAlipour, Atieh
dc.contributor.authorMoftakhari, Hamed
dc.contributor.authorJafarzadegan, Keighobad
dc.contributor.authorMoradkhani, Hamid
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2023-09-28T19:28:52Z
dc.date.available2023-09-28T19:28:52Z
dc.date.issued2023
dc.description.abstractThe global increase in the frequency, intensity, and adverse impacts of natural hazards on societies and economies necessitates comprehensive vulnerability assessments at regional to national scales. Despite considerable research conducted on this subject, current vulnerability and risk assessments are implemented at relatively coarse resolution, and they are subject to significant uncertainty. Here, we develop a block-level Socio-Economic-Infrastructure Vulnerability (SEIV) index that helps characterize the spatial variation of vulnerability across the conterminous United States. The SEIV index provides vulnerability information at the block level, takes building count and the distance to emergency facilities into consideration in addition to common socioeconomic vulnerability measures and uses a machine-learning algorithm to calculate the relative weight of contributors to improve upon existing vulnerability indices in spatial resolution, comprehensiveness, and subjectivity reduction. Based on such fine resolution data of approximately 11 million blocks, we are able to analyze inequality within smaller political boundaries and find significant differences even between neighboring blocks. Introduces a precise, machine-learning-based Socio-Economic-Infrastructure Vulnerability index for natural hazards that uncovers stark variations in vulnerability at the block level emphasizing crucial information for risk-informed decision making.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationYarveysi, F., Alipour, A., Moftakhari, H., Jafarzadegan, K., & Moradkhani, H. (2023). Block-level vulnerability assessment reveals disproportionate impacts of natural hazards across the conterminous United States. In Nature Communications (Vol. 14, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1038/s41467-023-39853-z
dc.identifier.doi10.1038/s41467-023-39853-z
dc.identifier.orcidhttps://orcid.org/0000-0003-3170-8653
dc.identifier.orcidhttps://orcid.org/0000-0002-2889-999X
dc.identifier.urihttps://ir.ua.edu/handle/123456789/11309
dc.languageEnglish
dc.language.isoen_US
dc.publisherNature Portfolio
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSOCIAL VULNERABILITY
dc.subjectFLOOD RISK
dc.subjectDROUGHT RISK
dc.subjectMANAGEMENT
dc.subjectMultidisciplinary Sciences
dc.titleBlock-level vulnerability assessment reveals disproportionate impacts of natural hazards across the conterminous United Statesen_US
dc.typeArticle
dc.typetext

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