Landslide Early Warning Method Based on Dynamic High Frequency Data of Ground-Based Radar Interferometry

被引：1
|
作者：
Qin, Hongnan [1 ]
Ma, Haitao [1 ]
Yu, Zhengxing [1 ]
Liu, Yuxi [2 ]
机构：
[1] China Academy of Safety Science &Technology, Beijing
[2] School of Civil Engineering, University of Science and Technology Liaoning, Anshan
来源：
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2024年 / 49卷 / 08期
关键词：
dynamic high frequency data; early warning; ground-based synthetic aperture radar; landslide;
D O I：
10.13203/j.whugis20220152
中图分类号：
学科分类号：
摘要：
Objectives: Mine slope instability is one of the main factors restricting the safety production of open-pit mines in China. Ground-based synthetic aperture radar interferometry technology has been gradually introduced into the application of slope safety monitoring and early warning prediction in open-pit mines. However, the high-frequency rolling update characteristics of ground radar interferometry data lead to large data error accumulation and unobvious curve mutation characteristics. Methods: Processing the original data by dislocation subtraction and velocity reciprocal method can effectively reduce the vibration of high-frequency data, improve the readability of critical sliding data. After data processing, it can highlight the trend characteristics of key deformation data. The research is based on the analysis of cumulative displacement curve, velocity curve and reciprocal velocity curve group treated with different periods. Results: It is found that there are three characteristic points in the curve group: Sudden deformation increase point, velocity increase point and stable vibration point. Through these characteristic points, the slope landslide disaster can be predicted. The trend of key deformation data can be highlighted by using the three feature points of deformation sudden increase point, velocity growth point and stable vibration point. Conclusions: Through the identification of three feature points, the possible landslide can be effectively identified in advance and the landslide time can be predicted, which provides a new technical path and solution for landslide early warning and prediction analysis based on ground-based interferometric radar. © 2024 Editorial Department of Geomatics and Information Science of Wuhan University. All rights reserved.
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页码：1330 / 1336
页数：6
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