Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas
Establishing a database of building exposures is an important basic work in earthquake insurance research. How to efficiently, accurately, and scientifically construct the risk exposure database of buildings has become a hot topic these days. Based on multi-source data, a system for extracting seism...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/11/6501 |
| _version_ | 1797597975084531712 |
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| author | Pan Zhang Xiaojun Li Qiumei He |
| author_facet | Pan Zhang Xiaojun Li Qiumei He |
| author_sort | Pan Zhang |
| collection | DOAJ |
| description | Establishing a database of building exposures is an important basic work in earthquake insurance research. How to efficiently, accurately, and scientifically construct the risk exposure database of buildings has become a hot topic these days. Based on multi-source data, a system for extracting seismic information from urban buildings was constructed in the Tangshan urban area, and a perfect earthquake insurance risk database was established in this study. In the extraction system, the U-net identification method, spatial overlay and kernel density estimation method, Kriging interpolation method, statistical analysis, and multi-temporal land cover data analysis were used, respectively, to extract the information of footprint areas, use function, story number, structure type, and construction age of the urban buildings. The extraction results are stratified and randomly sampled, and the confusion matrix is introduced to verify the extraction effect. The results show that the building covers an area of about 50 million square meters in the urban area of Tangshan City. With the training and validation of the U-net model, the global accuracy of the building footprint areas recognition model is 71%. By comparing the results of manually determined real data with the extraction results of this study for a sample of 660 buildings, it was found that the overall accuracy rates of the extraction results of building function, story number, structure type, and construction age were 88.62%, 86.65%, 86.49%, and 85.58%, respectively, and kappa coefficients were all over 0.8. These indicate that the information on buildings extracted by the method of this study is accurate and reliable. This study can provide data and methods for the establishment of the exposure database of earthquake insurance and provide strong data support for pre-earthquake disaster prevention, post-earthquake emergency rescue, and disaster loss assessment. |
| first_indexed | 2024-03-11T03:11:49Z |
| format | Article |
| id | doaj.art-c537c276e3c74763ad1fa8e167a31525 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T03:11:49Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-c537c276e3c74763ad1fa8e167a315252023-11-18T07:32:59ZengMDPI AGApplied Sciences2076-34172023-05-011311650110.3390/app13116501Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban AreasPan Zhang0Xiaojun Li1Qiumei He2Institute of Geophysics, China Earthquake Administration, Beijing 100081, ChinaKey Laboratory of Urban Security and Disaster Engineering of China Ministry of Education, Beijing University of Technology, Beijing 100124, ChinaInstitute of Geophysics, China Earthquake Administration, Beijing 100081, ChinaEstablishing a database of building exposures is an important basic work in earthquake insurance research. How to efficiently, accurately, and scientifically construct the risk exposure database of buildings has become a hot topic these days. Based on multi-source data, a system for extracting seismic information from urban buildings was constructed in the Tangshan urban area, and a perfect earthquake insurance risk database was established in this study. In the extraction system, the U-net identification method, spatial overlay and kernel density estimation method, Kriging interpolation method, statistical analysis, and multi-temporal land cover data analysis were used, respectively, to extract the information of footprint areas, use function, story number, structure type, and construction age of the urban buildings. The extraction results are stratified and randomly sampled, and the confusion matrix is introduced to verify the extraction effect. The results show that the building covers an area of about 50 million square meters in the urban area of Tangshan City. With the training and validation of the U-net model, the global accuracy of the building footprint areas recognition model is 71%. By comparing the results of manually determined real data with the extraction results of this study for a sample of 660 buildings, it was found that the overall accuracy rates of the extraction results of building function, story number, structure type, and construction age were 88.62%, 86.65%, 86.49%, and 85.58%, respectively, and kappa coefficients were all over 0.8. These indicate that the information on buildings extracted by the method of this study is accurate and reliable. This study can provide data and methods for the establishment of the exposure database of earthquake insurance and provide strong data support for pre-earthquake disaster prevention, post-earthquake emergency rescue, and disaster loss assessment.https://www.mdpi.com/2076-3417/13/11/6501buildingsfootprint areasuse functionstory numberstructureconstruction age |
| spellingShingle | Pan Zhang Xiaojun Li Qiumei He Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas Applied Sciences buildings footprint areas use function story number structure construction age |
| title | Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas |
| title_full | Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas |
| title_fullStr | Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas |
| title_full_unstemmed | Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas |
| title_short | Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas |
| title_sort | extraction of building information based on multi source spatiotemporal data for earthquake insurance in urban areas |
| topic | buildings footprint areas use function story number structure construction age |
| url | https://www.mdpi.com/2076-3417/13/11/6501 |
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