基于时间序列InSAR分析的西部山区滑坡灾害隐患早期识别——以四川丹巴为例

Early Detection of Landslide Hazards in Mountainous Areas of West China Using Time Series SAR Interferometry——A Case Study of Danba, Sichuan

滑坡是仅次于地震、发生最频繁、造成损失最严重的一种地质灾害,中国西部山区则是世界上滑坡灾害分布最密集的地区之一。广域范围内滑坡灾害隐患的早期识别是地质灾害防治工作中的一项关键任务,基于星载合成孔径雷达重复轨道观测的时间序列雷达干涉测量(interferometric synthetic aperture radar,In-SAR)技术在此领域具有巨大的应用潜力,但以永久散射体干涉测量为代表的传统时序InSAR方法在西部山区应用中往往受到植被覆盖等不利因素的影响,滑坡探测识别的可靠性较差。针对这一问题,以大渡河上游丹巴县为例,采用自主研发的相干散射体时序InSAR(coherent scatterer InSAR,CSI)方法,从历史存档的ALOS PALSAR和ENVISAT ASAR数据集中成功识别出了17处持续变形中的不稳定坡体,通过与外部观测数据比对和实地调查核实等手段验证了CSI方法探测结果的有效性和优势,并探讨了影响时序InSAR方法滑坡监测应用效果的主要因素及未来的优先研究方向。

As the most frequent and devastating geohazard next to earthquakes, landslides are widely distributed in mountainous areas of west China, which makes early detection of landslides a vital task for geologic disaster prevention. Although time series SAR interferometry(InSAR) based on repeat-pass satellite SAR observations has shown a great potential in landslide detection, its performance is usually limited by factors such as vegetation coverage, which leads to low reliability of detection results. Aiming at this problem, we carry out a case study by employing the coherent scatterer InSAR(CSI) method to successfully detect 17 unstable slopes in Danba County in the upper reach of Dadu River Basin from archived ALOS PALSAR and ENVISAT ASAR datasets. The effectiveness and advantage of the CSI method are demonstrated by comparisons with other observation data as well as validation against field survey. And, major impact factors for the performance of time series InSAR analysis in landslide investigations and future research topics of high priority are summarized.