ORIGINAL RESEARCH article
Front. Built Environ.
Sec. Coastal and Offshore Engineering
Volume 11 - 2025 | doi: 10.3389/fbuil.2025.1546616
This article is part of the Research TopicNHERI 2015-2025: A Decade of Discovery in Natural Hazards EngineeringView all 8 articles
A Unified Framework for Post-disaster Hazard and Structural Assessment Data Collection Across Hazards and Infrastructure Typologies
Provisionally accepted- 1University of Hawaii at Manoa, Honolulu, United States
- 2University of Notre Dame, Notre Dame, Indiana, United States
- 3Auburn University, Auburn, Alabama, United States
- 4University of California, Berkeley, Berkeley, California, United States
- 5University of Florida, Gainesville, Florida, United States
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Post-disaster field observations of the built environment are critical for advancing fundamental research that links hazard data to structural performance, cascading community impacts, and the development of effective mitigation strategies. Yet, data collection remain fragmented across hazard types and infrastructure systems due to varying objectives, methodologies, protocols, and standards among investigators and organizations. To address this, a Unified Assessment Framework has been developed for standardized post-disaster hazard and structural assessment data and metadata collection across multiple natural hazards (earthquake, windstorm, coastal events) and infrastructure typologies. The framework encompasses a tiered performance assessment structure with increasing rigor and fidelity levels: Basic Assessment (BA), Load Path Assessment (LPA), and Detailed Component Assessment (DCA). The framework has been implemented as an open-access mobile application, the Structural Extreme Events Reconnaissance (StEER) Network’s StEER Unified App, hosted on Fulcrum data collection platform . Along with unification of data fields, preliminary mapping rules were developed to map out existing hazard-specific damage rating scales (e.g., wind, surge, wave, rainwater ingress) to the European Macroseismic Scale (EMS-98) compatible unified damage scale, enabling consolidation of global damage ratings into a common data field, facilitating the unification of multiple hazards within a single app. In the mapping of damage ratings, overarching level definitions were retained (e.g., slight, moderate, severe damage) while customizing the specific descriptors to reflect hazard-specific damage mechanisms. Two use cases are presented to demonstrate the application of this framework through the StEER Unified App: a supervised pilot after the 2022 Hurricane Ian, Florida and an unsupervised deployment for the 2023 Turkey earthquake sequence. These deployments illustrate the framework’s flexibility and scalability, validate the feasibility of standardized assessments, and offer insights into how data quality is influenced by assessor pre-deployment training and assessment tier—particularly for complex tasks such as load path evaluation. This work advances the field by providing a scalable, standardized, and hazard-agnostic approach to structural field reconnaissance. The open-access framework and app support real-time deployments and enable integration of legacy datasets into a unified platform—laying the foundation for longitudinal analyses, cross-hazard comparisons, and expanded data reuse in the Natural Hazards Engineering community.
Keywords: Damage rating, Earthquakes, Hurricanes, Reconnaissance, Steer, Structural assessment, Tsunamis, Tornadoes
Received: 17 Dec 2024; Accepted: 14 May 2025.
Copyright: © 2025 Alam, Kijewski-Correa, Roueche, Mosalam, Prevatt and Robertson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mohammad Alam, University of Hawaii at Manoa, Honolulu, United States
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