Journal of Earthquake Engineering

Data-driven Regional Seismic Resilience

Enhancing seismic resilience at the regional scale requires timely assessment of earthquake-induced structural damage and effective planning for the recovery of critical infrastructure. Advances in structural health monitoring, remote sensing, robotic inspection, and data-driven structural modeling offer opportunities to better understand post-earthquake structural conditions and inform repair and restoration decisions. However, many studies remain focused on individual structures, isolated technical problems, or single points in time, limiting their direct contribution to regional resilience assessment and recovery planning.

This special issue focuses on structural engineering approaches that connect observations and assessments of structural conditions with regional infrastructure performance and recovery. It welcomes integration across data modalities, analytical methods, spatial and temporal scales, and assessment and decision-making processes. The central interest is how these connections advance understanding of the distribution and evolution of structural damage across a region and support infrastructure functionality assessment, repair prioritization, and recovery planning.

Contributions should address a clearly defined regional seismic resilience problem grounded in structural engineering, with this focus reflected in the research objectives, approach, and evaluation. They should explicitly establish how the proposed integration advances regional assessment, planning, or recovery. Through this focus, the special issue aims to clarify emerging approaches, current limitations, and research gaps in translating advances in structural assessment and modeling into regional seismic resilience enhancement.

Subject areas include, but are not limited to:

• remote sensing and robotic inspection approaches addressing regional post-earthquake structural assessment challenges, including inspection coverage, deployment prioritization, and coordinated assessment across distributed structures;
• post-earthquake data assimilation and information fusion across modalities or scales to estimate structural damage across regional infrastructure networks or inform restoration priorities;
• integration of information across spatial and temporal scales to link component- and structure-level conditions with regional infrastructure functionality and evolving recovery needs;
• data-driven modeling, simulation, and prediction of the spatial distribution and temporal evolution of structural damage states across regional critical infrastructure networks;
• regional recovery planning, repair and restoration prioritization, and resource allocation that integrate structural condition and performance assessments with infrastructure functionality estimates and recovery constraints;
• regional case studies examining how integration of structural observations, models, and decision-support approaches informs seismic resilience assessment, recovery planning, and resilience enhancement.