A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR Data
Earthquake disasters can have a serious impact on people’s lives and property, with damage to buildings being one of the main causes of death and injury. A rapid assessment of the extent of building damage is essential for emergency response management, rescue operations, and reconstruction. Terrest...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/5542012 |
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| author | Fan Yang Xintao Wen Xiaoshan Wang Xiaoli Li Zhiqiang Li |
| author_facet | Fan Yang Xintao Wen Xiaoshan Wang Xiaoli Li Zhiqiang Li |
| author_sort | Fan Yang |
| collection | DOAJ |
| description | Earthquake disasters can have a serious impact on people’s lives and property, with damage to buildings being one of the main causes of death and injury. A rapid assessment of the extent of building damage is essential for emergency response management, rescue operations, and reconstruction. Terrestrial laser scanning technology can obtain high precision light detection and ranging (LiDAR) point cloud data of the target. The technology is widely used in various fields; however, the quantitative analysis of building seismic information is the focus and difficulty of ground-based LiDAR data analysis processing. This paper takes full advantage of the high-precision characteristics of ground-based LiDAR data. A triangular network vector model (TIN-shaped model) was created in conjunction with the alpha shapes algorithm, solving the problem of small, nonvisually identifiable postearthquake building damage feature extraction bias. The model measures the length, width, and depth of building cracks, extracts the amount of wall tilt deformation, and labels the deformation zone. The creation of this model can provide scientific basis and technical support for postearthquake emergency relief, assessment of damage to buildings, extraction of deformation characteristics of other structures (bridges, tunnels, dams, etc.), and seismic reinforcement of buildings. The research data in this paper were collected by the author’s research team in the first time after the 2013 Lushan earthquake and is one of the few sets of foundation of LiDAR data covering the full range of postearthquake building types in the region, with the data information mainly including different damage levels of different structural types of buildings. The modeling analysis of this data provides a scientific basis for establishing the earthquake damage matrix of buildings in the region. |
| format | Article |
| id | doaj-art-79cf4303e46d4c099f5e0bc099706f51 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-79cf4303e46d4c099f5e0bc099706f512025-02-03T06:07:44ZengWileyAdvances in Civil Engineering1687-80861687-80942021-01-01202110.1155/2021/55420125542012A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR DataFan Yang0Xintao Wen1Xiaoshan Wang2Xiaoli Li3Zhiqiang Li4Institute of Geology, China Earthquake Administration, Beijing 100029, ChinaChina Earthquake Networks Center, Beijing 100045, ChinaHebei Earthquake Agency, Shijiazhuang 050021, ChinaChina Earthquake Networks Center, Beijing 100045, ChinaChina Earthquake Networks Center, Beijing 100045, ChinaEarthquake disasters can have a serious impact on people’s lives and property, with damage to buildings being one of the main causes of death and injury. A rapid assessment of the extent of building damage is essential for emergency response management, rescue operations, and reconstruction. Terrestrial laser scanning technology can obtain high precision light detection and ranging (LiDAR) point cloud data of the target. The technology is widely used in various fields; however, the quantitative analysis of building seismic information is the focus and difficulty of ground-based LiDAR data analysis processing. This paper takes full advantage of the high-precision characteristics of ground-based LiDAR data. A triangular network vector model (TIN-shaped model) was created in conjunction with the alpha shapes algorithm, solving the problem of small, nonvisually identifiable postearthquake building damage feature extraction bias. The model measures the length, width, and depth of building cracks, extracts the amount of wall tilt deformation, and labels the deformation zone. The creation of this model can provide scientific basis and technical support for postearthquake emergency relief, assessment of damage to buildings, extraction of deformation characteristics of other structures (bridges, tunnels, dams, etc.), and seismic reinforcement of buildings. The research data in this paper were collected by the author’s research team in the first time after the 2013 Lushan earthquake and is one of the few sets of foundation of LiDAR data covering the full range of postearthquake building types in the region, with the data information mainly including different damage levels of different structural types of buildings. The modeling analysis of this data provides a scientific basis for establishing the earthquake damage matrix of buildings in the region.http://dx.doi.org/10.1155/2021/5542012 |
| spellingShingle | Fan Yang Xintao Wen Xiaoshan Wang Xiaoli Li Zhiqiang Li A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR Data Advances in Civil Engineering |
| title | A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR Data |
| title_full | A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR Data |
| title_fullStr | A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR Data |
| title_full_unstemmed | A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR Data |
| title_short | A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground-Based LiDAR Data |
| title_sort | model study of building seismic damage information extraction and analysis on ground based lidar data |
| url | http://dx.doi.org/10.1155/2021/5542012 |
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