Implication of building inventory accuracy on physical and socio-economic resilience metrics for informed decision-making in natural hazards

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.