Application of Time Series Insar Technique for Deformation  Monitoring of Large-Scale Landslides in Mountainous Areas of  Western China

Qu, Tianshu; Lü, Ping; Liu, C.; Wan, Hong

doi:10.5194/isprs-archives-xli-b1-89-2016

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…The study of landslide deformation is mainly divided into the following aspects: the deformation rate of the landslide is analyzed, and the evident deformation zone on the landslide is determined by analyzing time series [6][7][8][9]; the deformation rate of the landslide is monitored and the evolution of phase transition is analyzed [10][11][12]. Previous studies have used InSAR in combination with other technologies to monitor slope deformation, slope hazard characteristics, and potential landslide bodies [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

InSAR monitoring and evaluation study on the safety and stability of high-altitude limestone dumps

Dong

Yuan

JIANG

et al. 2023

Preprint

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The conventional method of monitoring the stability and safety of slopes at high-altitude dumps is associated with a high financial investment and poses a risk for personnel involved in the deployment of monitoring instruments. In order to mitigate the challenges posed by conventional monitoring methods, including high investment and potential risks to personnel, we employed Synthetic Aperture Radar Interferometry (InSAR) technology for the evaluation of slope stability at a high-altitude dumps in Sangri County, Shannan, Tibet. The utilization of Synthetic Aperture Radar Differential Interferometry (D-InSAR) technology was employed to observe the deformation of the dumps over the course of the rainy season, spanning from 2019 to 2022. A four-year (Nov 2018 to Oct 2022) deformation rate assessment of the dumps was performed utilizing the Small Baseline Subset⁃Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology. The accuracy of InSAR monitoring in high-altitude slope areas was verified through correction with the results obtained from GNSS RTK monitoring. The state of stability and safety of the slope at the dumps was evaluated based on the results obtained from deformation monitoring. The D-InSAR monitoring results indicated that when the rainfall surpassed 300 mm, the slope deformation of the dumps exhibited a maximum displacement of 20 mm, necessitating intervention. The results of SBAS-InSAR monitoring indicate that the slope of the dumps underwent substantial deformation changes during the rainy season, yet remained stable during the dry periods. However, the results of our SBAS-InSAR monitoring indicate that the deformation and displacement curves of the dumps did not correspond entirely with changes in rainfall, and exhibited a hysteresis phenomenon in terms of deformation magnitude. The application of InSAR technology allows for the comprehensive and dynamic monitoring of the slopes at high-altitude dumps, offering reliable long-term assessments of safety and stability and ensuring secure and stable operations.

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Section: Introductionmentioning

confidence: 99%

InSAR monitoring and evaluation study on the safety and stability of high-altitude limestone dumps

Dong

Yuan

JIANG

et al. 2023

Preprint

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“…Some scholars have analyzed the influencing factors of landslides in various areas based on the results of MT-InSAR and found that rainfall is the main factor affecting the occurrence of landslides, whereas river distribution, fault zone distribution, slope, and slope direction are also important factors [25][26][27][28]. Some scholars have detected and identified landslides in large areas based on MT-InSAR results and verified the effectiveness of MT-InSAR in landslide identification combined with measured data [29,30]. Some scholars have uses In-SAR to predict landslides, including early detection of unstable landslides, spatiotemporal prediction of large-scale landslides, risk assessment of landslide collapse, etc.…”

Section: Introductionmentioning

confidence: 99%

Landslide Identification and Gradation Method Based on Statistical Analysis and Spatial Cluster Analysis

et al. 2022

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As a type of earth observation technology, interferometric synthetic aperture radar (InSAR) is increasingly widely used in the field of geological disaster detection. However, the application of InSAR in low-coherence areas, such as alpine canyon areas and vegetation coverage areas, is subject to considerable limitations. How to accurately identify landslides from InSAR measurement data in these areas remains the subject of several challenges and shortcomings. Based on statistical analysis and spatial cluster analysis, in this paper, we propose an automatic landslide identification and gradation method suitable for low-coherence areas. The proposed method combines the small baseline subset InSAR (SBAS-InSAR) method and the interferogram stacking (stacking-InSAR) method to obtain a deformation map in the study area, using statistical analysis and spatial cluster analysis to extract deformation regions and landslide polygons to propose a landslide screening model (LSM) based on multivariate features to screen landslides and reduce the interference of noise in landslide identification, in addition to proposing a landslide gradation model (LGM) based on signum function to grade the identified landslides and provide support to distinguish landslides with different deformation degrees. The method was applied to landslide identification in the upper section of the Jinsha River basin, and 47 potential landslides were identified, including 15 high-risk landslides and 13 landslides endangering villages. The experimental results show that the proposed method can identify landslides accurately and hierarchically in low-coherence areas, providing support for geological hazard investigation agencies and local departments.

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Joint monitoring of CO2-ECBM based on multiple geophysical methods: A case study of Shizhuang Town, Shanxi Province, China

Yang

Zheng

et al. 2022

International Journal of Greenhouse Gas Control

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Application of Time Series Insar Technique for Deformation Monitoring of Large-Scale Landslides in Mountainous Areas of Western China

Cited by 4 publications

References 12 publications

InSAR monitoring and evaluation study on the safety and stability of high-altitude limestone dumps

InSAR monitoring and evaluation study on the safety and stability of high-altitude limestone dumps

Landslide Identification and Gradation Method Based on Statistical Analysis and Spatial Cluster Analysis

Joint monitoring of CO2-ECBM based on multiple geophysical methods: A case study of Shizhuang Town, Shanxi Province, China

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