Bridging Heritage Knowledge and Digital Models: An HBIM Integration Framework
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| Опубликовано в:: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences vol. X-M-2-2025 (2025), p. 365-373 |
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| Главный автор: | |
| Другие авторы: | , , |
| Опубликовано: |
Copernicus GmbH
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| Предметы: | |
| Online-ссылка: | Citation/Abstract Full Text - PDF |
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| Краткий обзор: | Architectural heritage conservation demands the integration of precise physical documentation and interpretative design knowledge, yet current HBIM approaches remain fragmented: ‘scan-to-BIM’ prioritizes geometric accuracy at the expense of semantic richness, while “rule-based reconstruction” emphasizes idealized logic over as-built evidence. To bridge this gap, this study introduces the KSQI paradigm (Knowledge-Semantics-Quantities-Image), a novel framework that systematically connects domain expertise with digital modelling to balance spatial accuracy and architectural semantics. The research develops an as-recognized modelling or semantic-driven modelling through (1) a conservation cycle-guided information indexing system for semantic-driven knowledge integration, (2) a data-model decoupling workflow that teams from different disciplines maintain their working habits, handling data and models separately, then recoupling data-model by BIM team, and (3) a pattern book tooling solution including check forms for hierarchical investigation, algorithm modelling generator. By linking physical attributes (quantities/images) with design logic (semantics/knowledge), KSQI enhances information management, supports iterative knowledge updates, and facilitates informed conservation decisions. Case studies demonstrate its effectiveness in encoding both as-built conditions and historical, traditional design/construction principles, reinforcing the ‘H’ (history/heritage knowledge) in HBIM. This framework advances heritage documentation toward the smart metric survey, ensuring models serve as dynamic, semantically rich assets for conservation, research, dissemination, and digital twin applications. |
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| ISSN: | 2194-9042 2194-9050 |
| DOI: | 10.5194/isprs-annals-X-M-2-2025-365-2025 |
| Источник: | Engineering Database |