Abstract

The data and information available at the community-scale are directly linked to the ability to make a resilience-informed decision in natural hazards. This paper develops a systematic approach to quantify the implication of building inventory accuracy on resilience metrics for informed decision-making across engineering, economic and sociological dimensions at the community level. The method of approach consists of: (1) data and information availability, (2) community model development, (3) spatial hazard analysis, (4) physical damage and functionality analysis, and (5) socio-economic impact analysis. This process begins by generating a series of increasingly diminished data quality cases, i.e., increasing the apparent lack of knowledge about the building’s structural attributes within a community and developing computational models for each case. Then, damage and functionality analysis are performed to obtain building-level damage estimates, which are then fed into a computable general equilibrium model as well as a population dislocation model to compute a series of physical, economic, and socio-demographics resilience metrics. The estimated metrics are used to quantify the effects of diminishing data availability on physical and socio-economic metrics within the community. The proposed methodology is demonstrated using the illustrative example of the Memphis Metropolitan Statistical Area (MMSA) in Tennessee, USA.

抽象的

在社区范围内可获得的数据和信息直接与在自然灾害中做出适应能力强的决策有关。本文开发了一种系统化的方法，可以量化建筑库存准确性对弹性指标的影响，以便在社区层面跨工程，经济和社会学各个维度进行明智的决策。该方法包括：（1）数据和信息可用性，（2）社区模型开发，（3）空间危害分析，（4）物理破坏和功能分析以及（5）社会经济影响分析。此过程首先生成一系列数据质量日益下降的案例，即，增加社区中对建筑物的结构属性的明显缺乏了解，并为每种案例开发计算模型。然后，进行破坏和功能分析以获得建筑物级别的破坏估计，然后将其输入到可计算的一般均衡模型以及人口错位模型中，以计算一系列的物理，经济和社会人口统计学弹性指标。估计的指标用于量化减少数据可用性对社区内物理和社会经济指标的影响。使用美国田纳西州孟菲斯都市统计区（MMSA）的说明性示例演示了所建议的方法。以及社会人口弹性指标。估计的指标用于量化减少数据可用性对社区内物理和社会经济指标的影响。使用美国田纳西州孟菲斯都市统计区（MMSA）的说明性示例演示了所建议的方法。以及社会人口弹性指标。估计的指标用于量化减少数据可用性对社区内物理和社会经济指标的影响。使用美国田纳西州孟菲斯都市统计区（MMSA）的说明性示例演示了所建议的方法。