A New Model for the Digital Preservation and Utilization of Historic Buildings: Optimization of a Scene-Adaptive HBIM and VR Integrated Application Process

Abstract. This study proposes a scene-adaptive integration process combining Historic Building Information Modeling (HBIM) and Virtual Reality (VR) for the digital preservation and communication of historic buildings. Addressing limitations in conventional workflows, the methodology emphasizes modular flexibility, semantic structuring, and stakeholder-responsive interaction. It is applied to two contrasting heritage sites—the Former Ota Family Residence in Japan and the Battiferro Watergate Guardhouse in Italy—highlighting the system’s adaptability to varying cultural, material, and technical conditions. Through comparative analysis, the Ota case demonstrated superior balance in modeling efficiency, semantic depth, and immersive engagement, while Battiferro prioritized streamlined technical workflows with less interpretive richness. Evaluation metrics covering data acquisition, integration fidelity, and VR usability validated the proposed framework’s effectiveness in enhancing both scientific documentation and public outreach. The findings confirm that scene-adaptive processes can significantly improve relevance, efficiency, and user resonance in heritage visualization. Future research should expand empirical testing across architectural types and integrate emerging technologies to support wider applicability and long-term sustainability.

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Publication Details

Journal
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Published
2025-10-02
DOI
https://doi.org/10.5194/isprs-archives-xlviii-m-9-2025-911-2025
Primary Topic
Bacterial Identification and Susceptibility Testing
Type
article
Field-Weighted Citation Impact
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article

A New Model for the Digital Preservation and Utilization of Historic Buildings: Optimization of a Scene-Adaptive HBIM and VR Integrated Application Process

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Bacterial Identification and Susceptibility Testing
article

A New Model for the Digital Preservation and Utilization of Historic Buildings: Optimization of a Scene-Adaptive HBIM and VR Integrated Application Process

article en

Abstract

Abstract. This study proposes a scene-adaptive integration process combining Historic Building Information Modeling (HBIM) and Virtual Reality (VR) for the digital preservation and communication of historic buildings. Addressing limitations in conventional workflows, the methodology emphasizes modular flexibility, semantic structuring, and stakeholder-responsive interaction. It is applied to two contrasting heritage sites—the Former Ota Family Residence in Japan and the Battiferro Watergate Guardhouse in Italy—highlighting the system’s adaptability to varying cultural, material, and technical conditions. Through comparative analysis, the Ota case demonstrated superior balance in modeling efficiency, semantic depth, and immersive engagement, while Battiferro prioritized streamlined technical workflows with less interpretive richness. Evaluation metrics covering data acquisition, integration fidelity, and VR usability validated the proposed framework’s effectiveness in enhancing both scientific documentation and public outreach. The findings confirm that scene-adaptive processes can significantly improve relevance, efficiency, and user resonance in heritage visualization. Future research should expand empirical testing across architectural types and integrate emerging technologies to support wider applicability and long-term sustainability.

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesVol. XLVIII-M-9-2025
University of Tsukuba (JP), Southeast University (BD), Southeast University (CN), Politecnico di Milano (IT)
Openalex Percentile: Top 41%
Bacterial Identification and Susceptibility Testing
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