Applying Earth Observation Technologies to Economic Consequence Modeling: A Case Study of COVID-19 in Los Angeles County | CU Experts

Earth observation (EO) technologies can enhance economic consequence modeling of disasters by capturing fine-grained and real-time behavioral responses of businesses and the public. We investigate whether crowd-sourced interpretations of EO data can be used to illuminate key economic behavioral traits for computable general equilibrium modeling of supply-chain repercussions and resilience effects, using the COVID-19 in Los Angeles County as a case study. We also propose a dynamic adjustment approach to account for the changing character of EO through longer-term disasters in the economic modeling context. We find that despite limitations EO data can increase sectoral and temporal resolution, which leads to significant differences in direct and total impact results. These results have important implications for economic consequence modeling of disasters, as well as informing policymakers and emergency managers aiming to reduce disasters costs and improve economic resilience.

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