4.8 Article

Seismic multi-hazard and impact estimation via causal inference from satellite imagery

Journal

NATURE COMMUNICATIONS
Volume 13, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-022-35418-8

Keywords

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Funding

  1. USGS Earthquake Hazards Program [G22AP00032]
  2. Research Foundations at Stony Brook University
  3. Stanford Knight-Hennessy Scholars Program
  4. USGS IPA

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The rapid seismic multi-hazard and impact estimation system presented in this study utilizes advanced statistical causal inference and remote sensing techniques to provide accurate and high-resolution estimations of multiple hazards and building damage on a regional scale. The evaluation results demonstrate that incorporating causal dependencies significantly improves the estimation accuracy compared to existing systems. This system establishes a new way to extract and utilize the complex interactions of multiple hazards and impacts for effective disaster responses and advancing understanding of seismic geological processes.
Rapid post-earthquake reconnaissance is important for emergency responses and rehabilitation by providing accurate and timely information about secondary hazards and impacts, including landslide, liquefaction, and building damage. Despite the extensive collection of geospatial data and satellite images, existing physics-based and data-driven methods suffer from low estimation performance due to the complex and event-specific causal dependencies underlying the cascading processes of earthquake-triggered hazards and impacts. Herein, we present a rapid seismic multi-hazard and impact estimation system that leverages advanced statistical causal inference and remote sensing techniques. The unique feature of this system is that it provides accurate and high-resolution estimations on a regional scale by jointly inferring multiple hazards and building damage from satellite images through modeling their causal dependencies. We evaluate our system on multiple seismic events from diverse countries around the globe. Our results corroborate that incorporating causal dependencies significantly improves large-scale estimation accuracy for multiple hazards and impacts compared to existing systems. The results also reveal quantitative causal mechanisms among earthquake-triggered multi-hazard and impact for multiple seismic events. Our system establishes a new way to extract and utilize the complex interactions of multiple hazards and impacts for effective disaster responses and advancing understanding of seismic geological processes.

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