Deformation analysis of Sela landslide in the upper reaches of Jinsha River based on MSBAS technology
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摘要:
金沙江缝合带是滑坡灾害的高发区，且具有较大的堵江威胁。以堵江风险较高的色拉滑坡为研究对象，选取高时间分辨率的升降轨Sentinel-1A/B数据，利用MSBAS InSAR技术对该滑坡展开地表形变监测研究。文章在利用不同轨道的Sentinel-1A/B获取色拉滑坡2018—2020年间的二维动态形变时间序列的基础上，分析了典型特征点形变时间序列特征。结果表明，在2018年1月—2020年4月色拉滑坡东西向累积形变最高达到165 mm，垂直向累积形变达−102 mm，滑坡体形变加速的时间点被成功地捕获。最后，分析了该滑坡的形变趋势，通过现场调查结果验证了所获得滑坡监测结果的准确性。
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关键词:
- 多维短基线集技术 /
- 相位堆叠InSAR技术 /
- 色拉滑坡 /
- 滑坡识别 /
- 二维分解
Abstract:The Jinshajiang suture zone is a high-incidence area of landslide disasters and has a greater threat of river jamming. In this paper, the Sela landslide with high risk of blocking rivers was taken as the research object, and the Sentinel-1A/B images were selected and processed by MSBAS InSAR technology to obtain the surface deformation of the landslide. We used the Sentinel-1A/B images from different orbits to obtain the two-dimensional dynamic deformation of the Sela landslide from 2018 to 2020. Deformation time series characteristics of typical points are analyzed. The results show that the cumulative deformation in the east-west direction of Sala landslide reached a maximum of 165 mm, and the cumulative deformation in the vertical direction reached −102 mm from January 2018 to April 2020. We studied the deformation trend of the landslide, and the accuracy of the landslide monitoring results was verified by the field survey results.
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Key words:
- MSBAS /
- stacking InSAR /
- Sela landslide /
- landslide identification /
- two dimensional decomposition
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表 1 研究区SAR数据集主要参数
Table 1. Main parameters of the SAR data sets used in this study
轨道方向 升轨 降轨 轨道号 99 33 入射角 33.8° 39.3° 方位角 −10.4° −170.0° 成像模式 IW宽幅模式 IW宽幅模式 极化方式 VV VV 影像数量 66 64 影像时间间隔ΔT 12 12 影像时间范围 2018年1月—2020年4月 2018年1月—2020年4月 
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表 2 形变参考区内的形变速率标准差
Table 2. Standard deviation of deformation rate in deformation reference area
/(mm·a−1) SAR数据 平均值 标准差 东西向 −0.489 2.115 垂直向 1.499 1.574
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