Abstract
Hurricanes cause significant building damages, whose losses are aggregated by existing hurricane regional loss estimation frameworks, compromising model granularity and fidelity. The need to reduce mounting losses through targeted mitigation investments instead demands tools that enable site-specific, building-specific, and component-level loss estimations. Delivering such granularity in high-fidelity loss modeling creates new challenges in efficiently assembling and managing spatial and geometric data of thousands of constructed buildings. In response, this paper offers two interrelated contributions: (1) a conceptual data model that leverages open data for efficient integration and querying of component- to site-level information across the loss estimation workflow and (2) the implementation of this data model in Python to tractably generate building models within existing open-source loss modeling workflows. The accompanying case study and scenario-based verifications demonstrate how the data model meets stated design requirements in its generation of building models.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.