Abstract Landslides and resultant barrier lakes are significant threats to human lives and infrastructures. Three-dimensional (3D) surface displacements can give vital clues to the exploration of internal structure of landslides, but they are difficult to be retrieved from spaceborne Synthetic Aperture Radar (SAR) observations due to the intrinsic limitation of SAR imaging geometry. Meanwhile, studies on predicting slope failure based on SAR-measured displacements are rarely seen. Here, we used SAR pixel offset tracking to investigate the Baige landslide before the collapse on 10 October 2018. 3D surface displacements retrieved by combining satellite SAR and optical observations revealed heterogeneous spatial patterns within the landslide complex. We observed linear secondary creep and accelerating tertiary creep prior to the failure from multi-sensor SAR data. The possibility of forecasting the failure was demonstrated by applying an inverse velocity method to the time-series displacements measured by Sentinel-1 during the tertiary creep, which is valuable for risk evaluation and disaster early warning.

中文翻译：

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从时间序列 SAR 观测中反演白格滑坡历史地表位移，用于倒塌事件的回顾性分析

摘要 滑坡和由此产生的堰塞湖是对人类生命和基础设施的重大威胁。三维 (3D) 表面位移可以为滑坡内部结构的探索提供重要线索，但由于 SAR 成像几何的内在限制，它们很难从星载合成孔径雷达 (SAR) 观测中检索出来。同时，基于 SAR 测量位移预测边坡破坏的研究很少见。在这里，我们使用 SAR 像素偏移跟踪来调查 2018 年 10 月 10 日崩塌前的白格滑坡。通过结合卫星 SAR 和光学观测获得的 3D 表面位移揭示了滑坡复合体中的异质空间模式。我们在多传感器 SAR 数据失效之前观察到线性二次蠕变和加速三次蠕变。通过将反速度方法应用于 Sentinel-1 在三次蠕变期间测量的时间序列位移，证明了预测故障的可能性，这对于风险评估和灾害预警很有价值。