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    Resilience as Property Value Rebound: Analysis of Expanded Datasets from Hurricanes Ike and Irma

    Source: Natural Hazards Review:;2023:;Volume ( 024 ):;issue: 004::page 04023043-1
    Author:
    Alexander Laun
    ,
    Thomas Mazzuchi
    ,
    Shahram Sarkani
    ,
    Tori Tomiczek
    DOI: 10.1061/NHREFO.NHENG-1392
    Publisher: ASCE
    Abstract: For residential structures in America’s coastal communities, resilience is an essential system quality. Such resilience is best conceptualized as a given system’s ability to anticipate, respond to, recover from, and adapt to disruption. Practically, the quantification of parcel-scale resilience requires detailed temporal data and the ability to assess various indicators of system performance variability. This paper considers expanded datasets related to wave and storm surge damage for two catastrophic disruptions: Hurricane Ike in Galveston County, Texas, and Hurricane Irma in Monroe County, Florida. Data mining suggests that appraised property values for single-family residences may be used to characterize a given parcel’s post-disruption economic response and rebound behavior. Such rebound varies, and the authors offer four potential indicators of such variability for future study: the severity of the initial disruption, a parcel’s location, a parcel’s construction, and a given property’s flood insurance coverage. In general, following a hurricane, recorded property values appear to serve as another feasible measure of a given disaster-affected system’s resilient performance. Ultimately, these findings not only offer another mechanism by which community leaders can effectively manage resilience but also suggest that FEMA must continue to improve the National Flood Insurance Program.
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      Resilience as Property Value Rebound: Analysis of Expanded Datasets from Hurricanes Ike and Irma

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    contributor authorAlexander Laun
    contributor authorThomas Mazzuchi
    contributor authorShahram Sarkani
    contributor authorTori Tomiczek
    date accessioned2024-04-27T20:57:12Z
    date available2024-04-27T20:57:12Z
    date issued2023/11/01
    identifier other10.1061-NHREFO.NHENG-1392.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296324
    description abstractFor residential structures in America’s coastal communities, resilience is an essential system quality. Such resilience is best conceptualized as a given system’s ability to anticipate, respond to, recover from, and adapt to disruption. Practically, the quantification of parcel-scale resilience requires detailed temporal data and the ability to assess various indicators of system performance variability. This paper considers expanded datasets related to wave and storm surge damage for two catastrophic disruptions: Hurricane Ike in Galveston County, Texas, and Hurricane Irma in Monroe County, Florida. Data mining suggests that appraised property values for single-family residences may be used to characterize a given parcel’s post-disruption economic response and rebound behavior. Such rebound varies, and the authors offer four potential indicators of such variability for future study: the severity of the initial disruption, a parcel’s location, a parcel’s construction, and a given property’s flood insurance coverage. In general, following a hurricane, recorded property values appear to serve as another feasible measure of a given disaster-affected system’s resilient performance. Ultimately, these findings not only offer another mechanism by which community leaders can effectively manage resilience but also suggest that FEMA must continue to improve the National Flood Insurance Program.
    publisherASCE
    titleResilience as Property Value Rebound: Analysis of Expanded Datasets from Hurricanes Ike and Irma
    typeJournal Article
    journal volume24
    journal issue4
    journal titleNatural Hazards Review
    identifier doi10.1061/NHREFO.NHENG-1392
    journal fristpage04023043-1
    journal lastpage04023043-16
    page16
    treeNatural Hazards Review:;2023:;Volume ( 024 ):;issue: 004
    contenttypeFulltext
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