Investigation of Slow-Moving Artificial Slope Failure with Multi-Temporal InSAR by Combining Persistent and Distributed Scatterers: A Case Study in Northern Taiwan

• Main Authors: Hongyu Liang, Xin Li, Lei Zhang, Rou-Fei Chen, Xiaoli Ding, Kuo-Long Chen, Chi-Shan Wang, Chia-Shin Chang, Chien-Yu Chi
• Format: Article
• Language: English
• Published: MDPI AG 2020-07-01
• Series: Remote Sensing
• Subjects: artificial slope; landslide hazards; multitemporal InSAR (MTInSAR); phase estimation
• Online Access: https://www.mdpi.com/2072-4292/12/15/2403

In Taiwan, landslides pose serious threats to local residents and infrastructures each year due to high mountain relief and distinct seasonal precipitation distribution. Interferometric synthetic aperture (InSAR) provides a powerful tool to map terrain motion and characterize the failure mechanism of unstable slopes. However, it is challenging for the conventional InSAR technique to obtain reliable landslide information in mountainous regions because of insufficient coherent measurements and signal confusion caused by vegetation coverage and rugged terrain. In this study, we adopt an optimized multi-temporal InSAR (MTInSAR) approach to analyze the surface displacement of an artificial side slope along Freeway No. 3, where a catastrophic landslide failure occurred on 25 April 2010, in northern Taiwan. To increase the spatial extent of the deformation signal, we integrate information from both persistent scatterers (PSs) and distributed scatterers (DSs). Topographic residual and height-dependent atmospheric delays are corrected by a component-based method and joint model estimation, respectively. The results reveal the existence of slope movement with a rate of about −30 mm/year prior to the landslide failure. Further analysis shows that the temporal behaviors of downslope movement are correlated with local precipitation. The study demonstrates the need to continuously monitor and verify the stability of artificial slopes to prevent and minimize the probability of a similar landslide occurrence in the future.