Classification of Seismaesthesia Information and Seismic Intensity Assessment by Multi-Model Coupling
文献类型：期刊论文
| 作者 | Lv, Qingzhou4,6; Liu, Wanzeng2,4; Li, Ran2,4; Yang, Hui3; Tao, Yuan3,4; Wang, Mengjiao1 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2023-02-01 |
| 卷号 | 12期号:2页码:46 |
| 关键词 | multi-model coupling natural language processing BERT-TextCNN model social media data seismic intensity assessment |
| DOI | 10.3390/ijgi12020046 |
| 文献子类 | Article |
| 英文摘要 | Earthquake disaster assessment is one of the most critical aspects in reducing earthquake disaster losses. However, traditional seismic intensity assessment methods are not effective in disaster-stricken areas with insufficient observation data. Social media data contain a large amount of disaster information with the advantages of timeliness and multiple temporal-spatial scales, opening up a new channel for seismic intensity assessment. Based on the earthquake disaster information on the microblog platform obtained by the network technique, a multi-model coupled seismic intensity assessment method is proposed, which is based on the BERT-TextCNN model, constrained by the seismaesthesia intensity attenuation model, and supplemented by the method of ellipse-fitting inverse distance interpolation. Taking four earthquakes in Sichuan Province as examples, the earthquake intensity was evaluated in the affected areas from the perspective of seismaesthesia. The results show that (1) the microblog data contain a large amount of earthquake information, which can help identify the approximate scope of the disaster area; (2) the influences of the subjectivity and uneven spatial distribution of microblog data on the seismic intensity assessment can be reduced by using the seismaesthesia intensity attenuation model and the method of ellipse-fitting inverse distance interpolation; and (3) the accuracy of seismic intensity assessment based on the coupled model is 70.81%. Thus, the model has higher accuracy and universality. It can be used to assess seismic intensity in multiple regions and assist in the formulation of earthquake relief plans. |
| WOS研究方向 | Computer Science ; Physical Geography ; Remote Sensing |
| WOS记录号 | WOS:000938636300001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200765]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 作者单位 | 1.China Univ Min & Technol, Sch Resources & Geosci, Xuzhou 221116, Peoples R China 2.Kunming Univ Sci & Technol, Fac Land Resources Engn, Kunming 650093, Peoples R China 3.Minist Nat Resources China, Key Lab Spatiotemporal Informat &Intelligent Serv, Beijing 100830, Peoples R China 4.Hubei Luojia Lab, Wuhan 430079, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 6.Natl Geomatics Ctr China, Beijing 100830, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lv, Qingzhou,Liu, Wanzeng,Li, Ran,et al. Classification of Seismaesthesia Information and Seismic Intensity Assessment by Multi-Model Coupling[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2023,12(2):46. |
| APA | Lv, Qingzhou,Liu, Wanzeng,Li, Ran,Yang, Hui,Tao, Yuan,&Wang, Mengjiao.(2023).Classification of Seismaesthesia Information and Seismic Intensity Assessment by Multi-Model Coupling.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,12(2),46. |
| MLA | Lv, Qingzhou,et al."Classification of Seismaesthesia Information and Seismic Intensity Assessment by Multi-Model Coupling".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 12.2(2023):46. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。