Identification and Dynamic Deformation Monitoring of Active Landslides in Jishishan Earthquake Area (Gansu, China) Using InSAR Technology
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摘要:
2023-12-18,甘肃省临夏回族自治州积石山县发生Ms 6.2地震,造成150余人遇难及大量建筑物倒塌,并诱发了同震滑坡灾害。此外,地震还将加速活动滑坡的形变,严重威胁人民生命财产和基础设施的安全,亟需开展震区活动滑坡快速识别与动态形变监测研究。基于此,提出了一种基于合成孔径雷达干涉测量(interferometric synthetic aperture radar,InSAR)技术的地震区活动滑坡自动化识别与动态形变监测框架。采用2017年3月至2023年12月的升轨与降轨Sentinel-1影像,反演获得InSAR相位梯度速率、年平均形变速率及时间序列,建立了DeepLabv3深度学习滑坡自动化识别方法,快速绘制研究区域的活动滑坡编目图,并开展滑坡空间分布特征研究;并采用序贯InSAR技术实现了新获得的合成孔径雷达影像的快速处理,进行滑坡形变的动态监测,及时捕获地震造成的滑坡形变加速信号。研究结果表明,在积石山震中70 km范围内分布有2 021个不同尺度的潜在活动滑坡,集中在6个高密度分布区,主要分布在距断层22 km、距河流28 km、距道路10 km范围内和高程3 400 m以下、坡度为15°~35°的区域,且主要沿着正北向、东北及正东向分布;本次地震造成积石山县及黄河沿线部分区域的滑坡形变出现显著加速,降低了斜坡的稳定性,现场调查验证了动态形变监测结果的可靠性。所提方法可为类似地震事件的活动滑坡快速调查及动态监测提供重要技术指导,研究成果可为震后灾区重建及次生滑坡灾害风险评估提供科学数据支撑。
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关键词:
- 积石山地震 /
- 滑坡识别 /
- 动态形变监测 /
- 序贯InSAR技术 /
- Sentinel-1影像
Abstract:ObjectivesOn December 18, 2023, an Ms 6.2 earthquake occurred in Jishishan County, Gansu Province, China. The earthquake caused more than 150 deaths and extensive collapse of buildings, and triggered a mass of coseismic landslides. In addition, the earthquake will also accelerate the deformation of active landslides, seriously threatening the safety of people's lives and property and infrastructure. Therefore, it is imperative to carry out research on the rapid identification and dynamic deformation monitoring of active landslides in earthquake-affected areas.
MethodsWe propose a novel framework for the automatic identification and dynamic deformation monitoring of active landslides in earthquake areas based on interferometric synthetic aperture radar (InSAR) technology. First, the InSAR phase-gradient rate, deformation rate and time series are calculated by utilizing both the ascending and descending Sentinel-1 synthetic aperture radar (SAR) images acquired during March 2017 to December 2023; and then, an approach for the automatic identification of active landslides is established using DeepLabV3 deep learning algorithm. As a result, the inventory map of active landslides in the study area was produced using the proposed method, and the spatial distribution characteristics of the landslides were investigated. Second, newly acquired SAR images were rapidly processed using the sequential InSAR method, thus achieving the dynamic deformation monitoring of landslides and the timely capture of earthquake-induced acceleration deformation signal.
ResultsThe InSAR results revealed that there are 2 021 active landslides with varying dimensions within a 70 km radius of the epicenter, and six regions exhibited particularly dense landslide distributions. The spatial distribution of the mapped landslides exhibited a clustering pattern: primarily within 22 km of faults, 28 km of rivers, and 10 km of roads. Additionally, they were predominantly located at elevations below 3 400 m and on slopes ranging 15°-35°, and also mainly distributed along the north, north-east, and east directions.
ConclusionThe deformation of some detected landslides within Jishishan County and along the Yellow River were significantly accelerated as a result of the earthquake event, thus reducing the stability of the slope. The reliability of the InSAR-derived results was verified through the field geological investigation. The proposed method offers significant technical value for the rapid investigation and dynamic monitoring of active landslides in similar seismic events, and the research findings provide scientific data support for post-earthquake reconstruction and secondary landslide disaster risk assessment.
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感谢欧洲空间局提供的Sentinel⁃1 SAR影像及30 m空间分辨率的DEM数据;以及甘肃省地矿局第三地质矿产勘查院协助野外调查验证。http://ch.whu.edu.cn/cn/article/doi/10.13203/j.whugis20240054
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图 6 研究区域2017年3月至2023年12月升轨(a, c)与2018年3月至2023年12月降轨(b, d) Sentinel⁃1影像地表形变速率及累积形变
注:负值(红色)表示远离SAR卫星视线方向的地表形变,正值(蓝色)表示靠近卫星视线方向的地表形变。
Figure 6. Deformation Rate and Cumulative Deformation of the Study Area Calculated with Ascending(March 2017 to December 2023) (a, c) and Descending(March 2018 to December 2023) (b, d) Sentinel-1 Images
表 1 升轨与降轨Sentinel-1影像基本参数
Table 1 Basic Parameters of the Ascending and Descending Sentinel-1 Images
统计项 Sentinel⁃1升轨 Sentinel⁃1降轨 方位角/(°) -13.16 -166.93 入射角/(°) 39.48 33.75 距离向与方位向分辨率/m 2.33×13.97 2.33×13.97 多视空间分辨率/m 15 15 时间跨度 2017⁃03⁃20—2023⁃12⁃26 2018⁃03⁃27—2023⁃12⁃26 影像数量/景 184 157 -
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