Print Email Facebook Twitter Investigating Surface Fractures and Materials Behavior of Cultural Heritage Buildings Based on the Attribute Information of Point Clouds Stored in the TLS Dataset Title Investigating Surface Fractures and Materials Behavior of Cultural Heritage Buildings Based on the Attribute Information of Point Clouds Stored in the TLS Dataset Author Alkadri, Miktha Farid (Universitas Indonesia) Alam, S. (TU Delft Applied Geology; Padjadjaran University) Santosa, Herry (Brawijaya University) Yudono, Adipandang (Brawijaya University) Beselly, S.M. (TU Delft Coastal Engineering; Brawijaya University; IHE Delft Institute for Water Education) Date 2022 Abstract To date, the potential development of 3D laser scanning has enabled the capture of high-quality and high-precision reality-based datasets for both research and industry. In particular, Terrestrial Laser Scanning (TLS) technology has played a key role in the documentation of cultural heritage. In the existing literature, the geometric properties of point clouds are still the main focus for 3D reconstruction, while the surface performance of the dataset is of less interest due to the partial and limited analysis performed by certain disciplines. As a consequence, geometric defects on surface datasets are often identified when visible through physical inspection. In response to that, this study presents an integrated approach for investigating the materials behavior of heritage building surfaces by making use of attribute point cloud information (i.e., XYZ, RGB, reflection intensity). To do so, fracture surface analysis and material properties are computed to identify vulnerable structures on the existing dataset. This is essential for architects or conservators so that they can assess and prepare preventive measures to minimize microclimatic impacts on the buildings. Subject point cloud datamaterial propertiesfracture surfacesheritage buildingsbuilding performance assessment To reference this document use: http://resolver.tudelft.nl/uuid:76529777-43f7-4324-a52d-6cb01f0639cf DOI https://doi.org/10.3390/rs14020410 ISSN 2072-4292 Source Remote Sensing, 14 (2), 1-24 Part of collection Institutional Repository Document type journal article Rights © 2022 Miktha Farid Alkadri, S. Alam, Herry Santosa, Adipandang Yudono, S.M. Beselly Files PDF remotesensing_14_00410_v2.pdf 5.75 MB Close viewer /islandora/object/uuid:76529777-43f7-4324-a52d-6cb01f0639cf/datastream/OBJ/view