Early Detection of Landslide Hazards in Mountainous Areas of West China Using Time Series SAR Interferometry-A Case Study of Danba, Sichuan
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摘要: 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，InSAR）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。Abstract: 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.
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Keywords:
- landslide /
- D-InSAR /
- time series InSAR /
- deformation measurement /
- early detection
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致谢: 本研究中使用的ALOS PALSAR和ALOS-2 PALSAR-2数据由日本宇航局ALOS RA项目(1247, 1440, 3248)提供，ENVISAT ASAR数据由中欧合作“龙”计划项目(32278)提供。
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图 1 研究区域：大渡河上游四川丹巴县境内
Figure 1. Sudy Area: Danba County of Sichuan Province in the Upper Reach of Dadu River
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图 2 丹巴县境内雷达视线方向平均形变速率图
Figure 2. Mean Velocity of Surface Displacements Along Radar Line-of-Sight Directions Within Danba Area
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图 3 雷达坐标系下经过滤波的PALSAR-2差分干涉图
Figure 3. Filtered Differential Interferograms of PALSAR-2 in Radar Coordinate Systems
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图 4 聂呷复合滑坡，包括扎客滑坡、甲居滑坡、聂呷坪滑坡、聂拉村滑坡和高顶滑坡
Figure 4. 4 Niexia Complex Landslide is Comprised of Five Landslides, Including Zhake, Jiaju, Niexiaping, Nielacun and Gaoding
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图 6 PALSAR与GPS观测形变速率散点图
Figure 6. Scatter Plot of Displacement Velocities Measured by PALSAR and GPS
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图 7 代表性GPS站点InSAR与GPS测量累积形变序列图
Figure 7. Cumulative Displacements at Typical GPS Stations Measured by InSAR and GPS
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图 8 3种时序InSAR分析方法得到的甲居滑坡平均形变速率图
Figure 8. Mean Displacement Velocities of Jiaju Landslide Derived by Three Time Series InSAR Methods
表 1 丹巴实验区星载SAR数据基本参数
Table 1 Basic Parameters of Satellite SAR Datasets over Danba Area
参数 SAR传感器 PALSAR ASAR PALSAR-2 轨道方向 升轨 升轨 升轨/降轨 雷达波长/cm 23 5.6 23 空间分辨率/m 10 20 10 重访周期/d 46 35 14 视角/(°) 34 38 32/36 影像数量 19 9 2/2 时间覆盖范围 2006-12-2011-01 2007-08-2008-06 2015-12-18和2016-12-16/
2016-06-09和2017-06-08垂直基线分布范围/m -1 478~2 354 -326~60 91/124 
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表 2 时序InSAR分析滑坡探测识别结果
Table 2 Summary of Landslide Detection Results by Time Series InSAR Analysis
滑坡名称 坡向/(°) 坡度/(°) 面积/
km2MP点密度/
(MPs·km-2)最大LOS形变速率/(mm·a-1) 可探测数据集 梭坡滑坡 220 20~30 1.1 3 659 80 A, P1, P2D 聂呷复合滑坡 110 15~30 42.5 10 898 -120 A, P1, P2A, P2D 五里牌滑坡 40 25~35 0.1 15 227 -44 P1, P2A 格宗滑坡 60 25~35 5.1 13 586 -101 A, P1, P2A 泽公滑坡 50 15~30 7.5 12 577 -63 A, P1, P2A 白呷山滑坡 10 10~30 7.6 12 896 -35 A, P1, P2A 红军桥滑坡 170 30~40 0.7 3 356 -16 P1, P2D 东风滑坡 310 15~30 0.1 3 253 25 P1, P2D 中路滑坡 300 15~35 9.1 4 574 -54 P1, P2D 岳扎滑坡 100 20~30 1.3 5 820 -56 P1, P2A 麻索寨滑坡 180 35~45 0.7 4 348 -42 P1, P2A 齐支滑坡 80 25~35 3.4 12 610 -68 P1, P2A 木纳山滑坡 120 25~40 4.8 6 259 -78 P1, P2A 注：①A、P1、P2A和P2D分别代表ASAR、PALSAR、升轨PALSAR-2和降轨PALSAR-2数据；②聂呷复合滑坡由5个局部滑坡(甲居、高顶、聂拉村、聂呷坪、扎客)组成；③形变速率负值表示滑坡位移远离卫星方向；④坡向以正北方向为零度，顺时针记录
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