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      Investigating Surface Fractures and Materials Behavior of Cultural Heritage Buildings Based on the Attribute Information of Point Clouds Stored in the TLS Dataset

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      Remote Sensing
      MDPI AG

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          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.

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          Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

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            Climate change impacts on cultural heritage: A literature review

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              Practical issues for using solar-reflective materials to mitigate urban heat islands

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                Author and article information

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                Journal
                Remote Sensing
                Remote Sensing
                MDPI AG
                2072-4292
                January 2022
                January 17 2022
                : 14
                : 2
                : 410
                Article
                10.3390/rs14020410
                f750ebb8-7ce4-4d2c-bdcf-a99bd1e1f0f5
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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