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DOI:

10.11834/jrs.20210162

收稿日期:

2020-10-20

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雷达遥感滑坡隐患识别与形变监测
廖明生1,董杰2,李梦华1,3,敖萌1,张路1,史绪国4
1.武汉大学 测绘遥感信息工程国家重点实验室, 武汉 430079;2.武汉大学 遥感信息工程学院, 武汉 430079;3.昆明理工大学 国土资源工程学院, 昆明 650093;4.中国地质大学 地理与信息工程学院, 武汉 430074
摘要:

滑坡是全球发生最为频繁、造成损失最严重的自然灾害之一,滑坡表面形变测量对于滑坡的早期识别、监测和预警具有重要意义。雷达遥感具有非接触式大范围空间连续覆盖和高精度形变测量等优势,在滑坡地质灾害领域中取得了广泛的应用。本文概述武汉大学干涉雷达遥感团队近几年在利用雷达遥感监测滑坡形变方面的研究内容,包括:雷达遥感在滑坡形变监测中的可行性和适用性分析、大范围滑坡隐患识别、复杂山区滑坡形变测量、大梯度滑坡形变测量、滑坡三维形变提取等。

Radar remote sensing for potential landslides detection and deformation monitoring
Abstract:

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.

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