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QIN Hongnan, MA Haitao, YU Zhengxing, LIU Yuxi. Landslide Early Warning Method Based on Dynamic High Frequency Data of Ground-based Radar Interferometry[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20220152
Citation: QIN Hongnan, MA Haitao, YU Zhengxing, LIU Yuxi. Landslide Early Warning Method Based on Dynamic High Frequency Data of Ground-based Radar Interferometry[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20220152

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

doi: 10.13203/j.whugis20220152
Funds:

National Key R&D Program of China (2021YFC3001900).

  • Received Date: 2022-06-25
  • Objectives: Mine slope instability is one of the main factors restricting the safety production of open-pit mines in China. Methods: Ground-based SAR(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. 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. It is found that there are three characteristic points in the curve group:sudden deformation increase point, velocity increase point and stable vibration point. Results: Through these characteristic points, the slope landslide disaster can be predicted and 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.
  • [1] Antonello G, Casagli N, Farina P, et al.Ground-Based SAR Interferometry for Monitoring Mass Movements[J].Landslides, 2004, 1(1):21-28
    [2] Yanping Wang, Weixian Tan, Wen Hong, et al.Ground-Based SAR for Man-Made Structure Deformation Monitoring[C].The 1st International Work-shop Spatial Information Technologies for Monitoring the Deformation of Large-Scale Man-Made Li-near Features, Hong Kong, China,2010
    [3] Antonello G, Tarchi D, Casagli N, et al.SAR interferometry from satellite and groundbased system for monitoring deformations on the Stromboli volcano[C]//IGARSS 2004.2004 IEEE International Geoscience and Remote Sensing Symposium.Anchorage, AK, USA.2004
    [4] Luzi G, Pieraccini M, Mecatti D, et al.Ground-Based Radar Interferometry for Landslides Monitoring:Atmospheric and Instrumental Decorrelation Sources on Experimental Data[J].IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(11):2454-2466
    [5] Zhang H, Yang X L, Yang F, et al.ThreeDimensional Slope Imaging Method for Ground-Based Real-Aperture Radar[J].Sensors (Basel, Switzerland), 2021, 21(10):3511
    [6] Deng Y K, Hu C, Tian W M, et al.3-D Deformation Measurement Based on Three GB-MIMO Radar Systems:Experimental Verification and Accuracy Analysis[J].IEEE Geoscience and Remote Sensing Letters, 2021, 18(12):2092-2096
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Landslide Early Warning Method Based on Dynamic High Frequency Data of Ground-based Radar Interferometry

doi: 10.13203/j.whugis20220152
Funds:

National Key R&D Program of China (2021YFC3001900).

Abstract: Objectives: Mine slope instability is one of the main factors restricting the safety production of open-pit mines in China. Methods: Ground-based SAR(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. 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. It is found that there are three characteristic points in the curve group:sudden deformation increase point, velocity increase point and stable vibration point. Results: Through these characteristic points, the slope landslide disaster can be predicted and 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.

QIN Hongnan, MA Haitao, YU Zhengxing, LIU Yuxi. Landslide Early Warning Method Based on Dynamic High Frequency Data of Ground-based Radar Interferometry[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20220152
Citation: QIN Hongnan, MA Haitao, YU Zhengxing, LIU Yuxi. Landslide Early Warning Method Based on Dynamic High Frequency Data of Ground-based Radar Interferometry[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20220152
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