Experiences of TLS, terrestrial and UAV photogrammetry in Cultural Heritage environment for restoration and maintenance purposes of Royal Racconigi castle, Italy

Costantino, Domenica; Rossi, Gabriele; Pepe, Massimiliano; Leserri, Massimo

doi:10.21014/tc4-arc-2022.083

Proceedings of the 2022 IMEKO TC4 International Conference on Metrology for Archaeology and Cultural Heritage 2023

DOI: 10.21014/tc4-arc-2022.083

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Experiences of TLS, terrestrial and UAV photogrammetry in Cultural Heritage environment for restoration and maintenance purposes of Royal Racconigi castle, Italy

Domenica Costantino¹,

Gabriele Rossi²,

Massimiliano Pepe³

et al.

Abstract: The aim of the work is to describe experiences in the field of the survey of cultural heritage with the use of Terrestrial Laser Scanner and terrestrial and UAV photogrammetry. In particular, using the latest technologies, the work describes a methodology and survey techniques capable of producing 2D and 3D models suitable for subsequent restoration or maintenance work. The case study taken into consideration concern the Royal Racconigi Castle (Italy).

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2024

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Using deep learning for enrichment of heritage BIM: Al Radwan house in historic Jeddah as a case study

Miky,

Alshawabkeh,

Baik

2024

Herit Sci

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Building information modeling (BIM) can greatly improve the management and planning of historic building conservation projects. However, implementing BIM in the heritage has many challenges, including issues with modeling irregular features, surveying data occlusions, and a lack of predefined libraries of parametric objects. Indeed, surface features can be manually distinguished and segmented depending on the level of human involvement during data scanning and BIM processing. This requires a significant amount of time and resources, as well as the risk of making too subjective decisions. To address these bottlenecks and improve BIM digitization of building geometry, a novel deep learning based scan-to-HBIM workflow is used during the recording of the historic building in historic Jeddah, Saudi Arabia, a UNESCO World Heritage site. The proposed workflow enables access to laser scanner and unmanned aerial vehicle imagery data to create a complete integrated survey using high-resolution imagery acquired independently at the best position and time for proper radiometric information to depict the surface features. By employing deep learning with orthophotos, the method significantly improves the interpretation of spatial weathering forms and façade degradation. Additionally, an HBIM library for Saudi Hijazi architectural elements is created, and the vector data derived from deep learning-based segmentation are accurately mapped onto the HBIM geometry with relevant statistical parameters. The findings give stakeholders an effective tool for identifying the types, nature, and spatial extent of façade degradation to investigate and monitor the structure.

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Using deep learning for enrichment of heritage BIM: Al Radwan house in historic Jeddah as a case study

Miky,

Alshawabkeh,

Baik

2024

Herit Sci

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Experiences of TLS, terrestrial and UAV photogrammetry in Cultural Heritage environment for restoration and maintenance purposes of Royal Racconigi castle, Italy

Cited by 1 publication

References 14 publications

Using deep learning for enrichment of heritage BIM: Al Radwan house in historic Jeddah as a case study

Using deep learning for enrichment of heritage BIM: Al Radwan house in historic Jeddah as a case study

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