Integration of detailed household and housing unit characteristic data with critical infrastructure for post-hazard resilience modeling
Integration of detailed household and housing unit characteristic data with critical infrastructure for post-hazard resilience modeling
复制标题
将详细的家庭和住房单元特征数据与关键基础设施相集成，以进行灾后复原力建模
DOI：
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复制
发表时间：
2019
影响因子：
5.9
通讯作者：
W. Peacock
中科院分区：
文献类型：
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作者：
Nathanael Rosenheim;R. Guidotti;P. Gardoni;W. Peacock
摘要本文提出了一种方法，生成并链接具有不同特征(即大小、保有权状况、占用和空置)的家庭和住房单元的高分辨率空间数据到住宅建筑，而住宅建筑又与关键基础设施相关联。该方法利用了美国人口普查的实际人口数据，这些数据可能与住宅建筑中的住房单元库存有关。通过将高分辨率的家庭社会人口数据分配给与关键基础设施系统相关联的单户和多户住宅结构中的住房单元，工程-社会科学耦合建模成为可能。本文提出了一种将社会科学和工程数据联系起来的工作流程，以实现社区复原力的集成模型。该方法适用于俄勒冈州的海滨，这是一个常年人口超过6,000人的沿海社区。该应用程序突出了整合社会科学和工程数据的好处。好处包括促进耦合建模、考虑不确定性、可视化和模拟结果的空间探索。
ABSTRACT This paper presents a methodology that generates and links high-resolution spatial data on households and housing units with heterogeneous characteristics (i.e., size, tenure status, occupied, and vacant) to residential buildings which in turn are linked to critical infrastructure. The methodology utilizes areal demographic data from the US Census, which are probabilistically linked to an inventory of housing units located in residential buildings. By allocating high-resolution household socio-demographic data to housing units in single and multi-family residential structures themselves linked to critical infrastructure systems, coupled engineering-social science modeling is possible. This paper presents a workflow for linking social science and engineering data to enable integrated models for community resilience. The methodology is applied to Seaside, Oregon, a coastal community with a year-round population of over 6,000 persons. The application highlights the benefits of integrating social science and engineering data. Benefits include facilitating coupled modeling, accounting for uncertainty, visualization, and spatial exploration of modeled results.
影响因子：
2.7
作者：
Mitchell, Christine M.;Esnard, Ann-Margaret;Sapat, Alka
通讯作者：
Sapat, Alka
影响因子：
1.9
作者：
Fussell E;Harris E
通讯作者：
Harris E
DOI：
10.3768/rtipress.2009.mr.0010.0905
发表时间：
2009-05-01
期刊：
Methods report (RTI Press)
影响因子：
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作者：
Wheaton WD;Cajka JC;Chasteen BM;Wagener DK;Cooley PC;Ganapathi L;Roberts DJ;Allpress JL
通讯作者：
Allpress JL