Emergency Identification and Influencing Factor Analysis of Coseismic Landslides and Building Damages Induced by the 2023 Ms 6.2 Jishishan (Gansu,China) Earthquake
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摘要:
2023⁃12⁃18,甘肃积石山县发生Ms 6.2地震,地震诱发了大量的同震滑坡,并导致建筑物不同程度损毁,造成了严重的人员伤亡和经济损失。及时获取同震滑坡易发性、应急识别同震滑坡并分析其影响因素以及定量评估建筑物损毁情况,对灾后的应急救援和恢复重建至关重要。基于支持向量机算法获取了积石山地震同震滑坡易发性空间分布,同时通过震前、震后的高分辨率光学卫星影像对同震滑坡进行了应急识别,并探讨了地震、地形地貌和人类活动等因素对同震滑坡的影响。此外,利用多时相合成孔径雷达干涉测量相干性变化方法获取了地震建筑物损毁代理图(building damage proxy map, BDPM)。结果表明,此次积石山Ms 6.2地震通过卫星遥感解译出同震滑坡共3 767处,总面积9.67 km²,多为黄土滑坡,主要分布在高程1 900~2 200 m、坡度20°~40°、坡向SE、距断层10 km和距水系2.2 km之内,黄土放大效应明显。研究团队震后第一时间开展野外考察,实地确认了59处同震滑坡,验证了遥感识别结果的准确性;BDPM结果表明,震区大河家镇和官亭镇建筑物损毁最为严重。上述研究成果为震后恢复重建和地震次生灾害评估提供了重要的数据支撑。
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关键词:
- 2023年积石山地震 /
- 黄土同震滑坡 /
- 地震建筑物损毁代理图 /
- 滑坡易发性 /
- 滑坡影响因子
Abstract:ObjectiveOn 18th December 2023, an Ms 6.2 earthquake struck Jishishan County, Gansu Province,China, which triggered a large number of coseismic landslides and caused varying degrees of buildings damage, leading to serious casualties and economic losses. Timely acquisition of the coseismic landslide susceptibility, emergency identification of coseismic landslides and building damage, as well as analysis of influencing factors related to coseismic landslides, are crucial for post-disaster emergency rescue and recovery efforts.
MethodsThe support vector machine algorithm was employed to acquire the spatial probability distribution of coseismic landslide susceptibility in the Jishishan earthquake. Emergency identification of coseismic landslides was conducted using high-resolution optical satellite imagery before and after the earthquake. Furthermore, a comprehensive analysis was undertaken by analyzing the impact of seismic, topographic, geomorphic, and human activity factors on coseismic landslides. Additionally, by using the multi-temporal interferometric synthetic aperture radar coherence change method, a building damage proxy map (BDPM) was generated to assess earthquake-induced structural damage.
ResultsThe Ms 6.2 Jishishan Earthquake triggered 3 767 coseismic landslides in the region with an area of 9.67 km². The majority of these landslides were composed of loess and were predominantly occurred in the region with an elevations range of 1 900-2 200 m, slope range of 20°-40°, southeast orientation, locating approximately 10 km from faults and 2.2 km from the river. The huge number of loess coseismic landslides reflects the evident amplification effect of loess. We conducted a field trip following the earthquake and confirmed 59 of those coseismic landslides, which verified the accuracy of the remote sensing identification results. In addition, BDPM results indicate that the towns of Dahejia and Guanting within the seismic zone experienced the most severe structural damage.
ConclusionsThese findings of this study provide crucial data support for post-earthquake rehabilitation and reconstruction as well as assessment of secondary seismic hazards.
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感谢中国资源卫星应用中心提供的高分1号卫星影像,长光卫星技术有限公司提供的吉林1号卫星影像,以及美国地质调查局提供的PGA数据,同时感谢欧洲空间局提供的Sentinel⁃1雷达影像、Sentinel⁃2光学影像和国家冰川冻土沙漠科学数据中心提供的12.5 m的DEM数据和历史存档滑坡数据。陈博,博士生,主要从事综合遥感的滑坡广域探测研究。bo.chen@chd.edu.cnhttp://ch.whu.edu.cn/cn/article/doi/10.13203/j.whugis20230497
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表 1 本文所使用的数据集
Table 1 Datasets Used in This paper
类型 影像名称 时间 空间分辨率 震前 高分一号 2023‐12‐18 2 m 吉林一号 2023‐12‐18 0.75 m Sentinel‐2 2023‐12‐18 10 m Sentinel‐1 SLC 2022‐12‐13—2023‐12‐14 4 m×20 m 震后 高分一号 2023‐12‐19 2 m 吉林一号 2023‐12‐19 0.75 m Sentinel‐2 2023‐12‐20 10 m Sentinel‐1 SLC 2023‐12‐26 4 m×20 m DEM ALOS 2006年 12.5 m 注: SLC(single look complex)即单视复数数据;ALOS(advanced land observing satellite)即先进陆地观测卫星。 -
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