<p>In this study, terrestrial laser scanning (TLS) is used to collect building data after the <i>M</i><sub>s</sub> 7.0 magnitude earthquake in Lushan, Sichuan, China in 2013 for analysis and research. The analysis focuses on extracting the tilt and deformation of masonry buildings that are difficult to identify through visual inspection in basically intact, slightly damaged and moderately damaged masonry buildings, to solve the problem of ambiguous identification of damage. A quantitative analysis of the determination indexes of the degree of earthquake damage was carried out, and the numerical characteristics parameters such as the curvature of the wall point cloud proximity, angle, contour of the fitted plane of the point cloud, verticality (flatness) of the wall, standard deviation of the profile and angle of the profile were established to determine the degree of earthquake damage to buildings based on LiDAR data. The development of quantitative determination indexes for the degree of earthquake damage of buildings in this study has important application value for LiDAR data in the identification and extraction of earthquake damage information and damage level determination.</p>

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Quantitative analysis of seismic damage information of masonry buildings based on terrestrial LiDAR data

  • Fan Yang,
  • Xiaoshan Wang,
  • Xiaodan Liu,
  • Zhiwei Fan,
  • Chao Wen,
  • Xiaoli Li,
  • Zhiqiang Li

摘要

In this study, terrestrial laser scanning (TLS) is used to collect building data after the Ms 7.0 magnitude earthquake in Lushan, Sichuan, China in 2013 for analysis and research. The analysis focuses on extracting the tilt and deformation of masonry buildings that are difficult to identify through visual inspection in basically intact, slightly damaged and moderately damaged masonry buildings, to solve the problem of ambiguous identification of damage. A quantitative analysis of the determination indexes of the degree of earthquake damage was carried out, and the numerical characteristics parameters such as the curvature of the wall point cloud proximity, angle, contour of the fitted plane of the point cloud, verticality (flatness) of the wall, standard deviation of the profile and angle of the profile were established to determine the degree of earthquake damage to buildings based on LiDAR data. The development of quantitative determination indexes for the degree of earthquake damage of buildings in this study has important application value for LiDAR data in the identification and extraction of earthquake damage information and damage level determination.