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Radar remote sensing for potential landslides detection and deformation monitoring

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

  • Email：liao@whu.edu.cn
  • Introduction：廖明生,1962年生, 男, 教授, 研究方向为雷达干涉测量、极化干涉测量技术及其在地形测绘、地质灾害监测和基础设施安全等领域的应用。E-mail: liao@whu.edu.cn
LIAO Mingsheng1,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

  • Email：dongjie@whu.edu.cn
  • Introduction：董杰，1988年生，男，特聘副研究员，研究方向为时间序列InSAR算法及其在地表形变监测中的应用。E-mail:dongjie@whu.edu.cn
DONG Jie2*,  
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

    Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China

LI Menghua13,  
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

AO Meng1,  
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

ZHANG Lu1,  
  • Affiliation：

    School of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, China

SHI Xuguo4

resumen

Landslides are one of the most frequent natural disasters around the world. The surface deformation measurement is important for early identification, monitoring and early warning of landslides. Radar remote sensing has the advantages of large-scale non-contact high-precision deformation measurement, which has been widely used in the field of landslide geological disasters. This paper summarizes the recent research results of the InSAR group in Wuhan University in landslide deformation monitoring using radar remote sensing. The researches include the feasibility and applicability of radar remote sensing in landslide deformation monitoring, large-scale identification of potential landslides, measurement of landslide deformation in complex mountainous areas, measurement of landslides with large deformation gradients, 3D deformation extraction of landslide, etc.The landslides have varying movement velocities. The phase-based InSAR method is only suitable to monitor very slow-moving landslides, while the amplitude-based offset tracking mothed can measure relatively large landslide movements. The potential active landslides across wide areas can be identified through inspecting the InSAR deformation rates. We took the Three Gorges Reservoir Region and Danba County as examples to demonstrate the effectiveness of InSAR landslide identification. Once the landslides are found out, we apply satellite InSAR to conduct fine monitoring of some important landslides. The Coherent Scatterers InSAR (CSInSAR) combines persistent scatterers and distributed scatterers to efficiently increase measurements points to ensure robust InSAR deformation results in complex mountainous regions. Meanwhile, we proposed two methods to correct the tropospheric atmospheric delays for time series InSAR analysis when studying single landslide. One is the Iterative Linear Model (ILM) as an improved version of the traditional Linear Model. The other is to fuse tropospheric delays predicted by several global weather models (FDWM) with different temporal intervals and spatial resolutions.The amplitude-based offset tracking method is applied to measure fast landslide movements. Particularly, a new Time-Series Point-like Target Offset Tracking (TS-PTOT) method is proposed to retrieve time-series surface displacements at point-like targets from SAR image pairs properly combined with large temporal baselines and small spatial baselines. We took the Shuping landslide, Guobu landslide, and Huangnibazi landslide as examples to prove the ability of offset tracking method for monitoring fast moving landslides. In addition, three-Dimensional (3D) displacement field, which can render the real movement of the slope surface, is of great significance to the analysis of deformation characteristics and deformation mechanism of a landslide. We took the Guobu landslide and the Jiaju landslide as examples to present the 3D displacements extraction from multiple observations.

palabra clave

remote sensing;landslide monitoring;time series InSAR;pixel offset tracking;3D deformation

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