Reports Outline Information Technology Study Results from China Earthquake Administration (Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas): Information Technology

2023 JUN 12 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Researchers detail new data in information technology. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “Establishing a database of building exposures is an important basic work in earthquake insurance research.”

Financial supporters for this research include The National Natural Science Foundation of China; 111 Project.

Our news editors obtained a quote from the research from China Earthquake Administration: “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%.”

According to the news editors, the research concluded: “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.”

For more information on this research see: Extraction of Building Information Based on Multi-Source Spatiotemporal Data for Earthquake Insurance in Urban Areas. Applied Sciences, 2023,13(11). (Applied Sciences - http://www.mdpi.com/journal/applsci). The publisher for Applied Sciences is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/app13116501.

Our news journalists report that additional information may be obtained by contacting Pan Zhang, Institute of Geophysics, China Earthquake Administration, Beijing 100081, People’s Republic of China. Additional authors for this research include Xiaojun Li, Qiumei He.

ORCID is an identifier for authors and includes bibliographic information. The following is ORCID information for the author of this research: Xiaojun Li (http://orcid.org/0000-0002-7526-0558).

(Our reports deliver fact-based news of research and discoveries from around the world.)