Validation of an Augmented Parcel Approach for Hurricane Regional Loss Assessments
Abstract
While simulation environments for the study of community resilience are rapidly advancing, they remain constrained by the completeness of inventory data. This paper presents an augmented parcel approach leveraging various sources of open data, machine learning modules, and time-evolving rulesets to support Hazus-compatible risk assessments on a wide class of buildings under hurricane wind and flood hazards. These techniques are implemented within the open-source regional hurricane loss assessment workflow of the Natural Hazards Engineering Research Infrastructure (NHERI) SimCenter. Illustrative examples demonstrate building inventory generation in both data-rich and data-scarce environments. The study’s validations of computer vision–based modules underscore the importance of training on “in the wild” images labeled with explicit knowledge of the region and representative of architectural nuances such as carports. Validations further reveal the challenges of simplifying complex contemporary roof geometries to the simplified shapes adopted in Hazus and the criticality of accurate year built data, given the augmented parcel approach’s reliance on time-evolving code-based rulesets. Published field observations collected in Lake Charles, Louisiana, following the landfall of Hurricane Laura, demonstrate that the use of an augmented parcel inventory within the SimCenter’s workflow for Hazus-compatible loss assessments yields damage states consistent with ground-truth observations for minor to moderate damage states. Simulations of extreme damage states (characterized by fewer ground-truth observations) bias toward minor damage for undamaged structures and plateau at moderate damage even for severely damaged and collapsed buildings. This trend persists when considering uncertainty in hazard intensity, as well as the low rates of shutter compliance. Root causes of inconsistencies revealed in this validation exercise will require further processing of street-level panoramic images to generate more samples of severely damaged and collapsed buildings as well as post-2007 construction.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies. Specifically, inputs (inventories, rulesets, and hazard data), outputs (results), and supporting documentation for Lake Charles are available in DesignSafe (https://doi.org/10.17603/ds2-83ca-r890). The pair of inventories and rulesets for Atlantic County are also available in DesignSafe (https://doi.org/10.17603/ds2-jpj2-zx14). See https://doi.org/10.5281/zenodo.5033626 to download the R2D application used to execute the regional simulations described herein. Full documentation for each of the inventories and R2D is available at https://nheri-simcenter.github.io/R2D-Documentation/index.html.
Acknowledgments
This material is based upon work supported by the National Science Foundation under Grant Nos. CMMI 1612843 and 2131111. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The authors acknowledge the larger collaborations with Sascha Hornauer, Wael Elhaddad, Greg Deierlein, and Andrew Kennedy on the regional testbeds for the NHERI SimCenter. The authors appreciate the special access to ZTRAX data provided by the University of California at Los Angeles (UCLA) and the group of Professor Ertugrul Taciroglu, access to NJDEP data and other inventory information by the New Jersey Department of Community Affairs (NJ DCA) and the office of Keith Henderson, and the assistance of Rachel Hamburger of the University of Notre Dame in assembling the literature review.
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Information & Authors
Information
Published In
Natural Hazards Review
Volume 24 • Issue 3 • August 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Mar 20, 2022
Accepted: Jan 31, 2023
Published online: Apr 18, 2023
Published in print: Aug 1, 2023
Discussion open until: Sep 18, 2023
ASCE Technical Topics:
- Buildings
- Computer vision and image processing
- Disaster risk management
- Disasters and hazards
- Engineering fundamentals
- Freight transportation
- Hurricanes, typhoons, and cyclones
- Information management
- Infrastructure
- Infrastructure resilience
- Inventories
- Logistics
- Methodology (by type)
- Natural disasters
- Research methods (by type)
- Structural engineering
- Structures (by type)
- Transportation engineering
- Validation
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