蔡杰华, 张路, 董杰, 董秀军, 廖明生, 许强. 九寨沟震后滑坡隐患雷达遥感早期识别与形变监测[J]. 武汉大学学报 ( 信息科学版), 2020, 45(11): 1707-1716. DOI: 10.13203/j.whugis20200263
引用本文: 蔡杰华, 张路, 董杰, 董秀军, 廖明生, 许强. 九寨沟震后滑坡隐患雷达遥感早期识别与形变监测[J]. 武汉大学学报 ( 信息科学版), 2020, 45(11): 1707-1716. DOI: 10.13203/j.whugis20200263
CAI Jiehua, ZHANG Lu, DONG Jie, DONG Xiujun, LIAO Mingsheng, XU Qiang. Detection and Monitoring of Post-Earthquake Landslides in Jiuzhaigou Using Radar Remote Sensing[J]. Geomatics and Information Science of Wuhan University, 2020, 45(11): 1707-1716. DOI: 10.13203/j.whugis20200263
Citation: CAI Jiehua, ZHANG Lu, DONG Jie, DONG Xiujun, LIAO Mingsheng, XU Qiang. Detection and Monitoring of Post-Earthquake Landslides in Jiuzhaigou Using Radar Remote Sensing[J]. Geomatics and Information Science of Wuhan University, 2020, 45(11): 1707-1716. DOI: 10.13203/j.whugis20200263

九寨沟震后滑坡隐患雷达遥感早期识别与形变监测

Detection and Monitoring of Post-Earthquake Landslides in Jiuzhaigou Using Radar Remote Sensing

  • 摘要: 2017-08-08,中国四川省九寨沟县发生Ms 7.0级地震,此次地震震级大、震源浅、烈度高,造成了严重的人员伤亡与财产损失,并引发了大量山体崩塌、滑坡等次生灾害。利用合成孔径雷达干涉测量(synthetic aperture radar interferometry,InSAR)技术对九寨沟地区开展潜在滑坡隐患早期识别与探测研究。首先,通过常规差分干涉测量(differential InSAR,DInSAR)技术处理分析6景先进陆地观测卫星(advanced land observing satellite, ALOS)-2 L波段相控合成孔径雷达(phased array type L-band synthetic aperture radar, PALSAR)-2升轨数据,对研究区域进行了灾害隐患快速普查;然后,利用时间序列InSAR技术处理112景哨兵1号(Sentinel-1)升降轨数据,对重点区域进行精细详查分析。研究结果发现,在九寨沟地区共探测出13处滑坡隐患,其中7处毗邻居民区;进一步对重点滑坡隐患进行时序变形监测,发现多处滑坡自震后长期处于持续线性形变中,对当地人民生命财产安全构成潜在威胁。实地调查结果验证了基于InSAR技术的滑坡隐患早期识别与探测方法的可靠性,研究结果可为九寨沟地区防灾减灾提供重要的决策依据。

     

    Abstract:
      Objectives  On 8th August 2017, a catastrophic earthquake of Ms 7.0 struck the County of Jiuzhaigou in Sichuan Province, China. Because of its high magnitude and shallow epicenter, the earthquake caused grave casualties and property losses. Furthermore, the earthquake triggered numerous secondary mountain disasters such as rockfall and landslide. We use the synthetic aperture radar interferometry (InSAR) technique to detect post-earthquake landslides in Jiuzhaigou area.
      Methods  Firstly, we carry out a quick detection across wide area using differential InSAR (DInSAR) technique with 6 ALOS-2 PALSAR-2 ascending images. DInSAR technique can observe the subtle deformation of landslide surface during the period between two SAR observations, so the active deforming landslides can be efficiently distinguished from stable areas. Nevertheless, the performance of DInSAR is often limited by temporal and spatial decorrelations induced by dense vegetation coverage, etc. To retrieve the temporal evolution of these landslides, detailed monitoring of specific landslides is carried out using time-series InSAR technique with 112 Sentinel-1 ascending and descending images. Time-series InSAR technique can overcome the limitation of traditional DInSAR technique in spatial-temporal decorrelation, and improve the deformation measurement accuracy. Therefore, the combination of DInSAR and time-series InSAR is adopted to accurately monitor single landslide, and efficiently detect landslides in Jiuzhaigou area.
      Results  The results show that there are 13 landslides that can be detected by InSAR analyses in Jiuzhaigou area, including 7 landslides close to residential areas. The time series displacements retrieved indicate that several landslides have long-term linear deformations after the 2017 earthquake. These landslides severely threaten people's life and property and need to be monitored regularly. Finally, the reliability of detection results based on InSAR technology is verified by a field survey.
      Conclusions  The results can provide key supports for the geohazard mitigation and prevention in the Jiuzhaigou scenic area. We indicate that a strategy which combines DInSAR technique with time-series InSAR can efficiently and accurately detect and monitor landslides over a wide area.

     

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