Detection and Characterization of Active Slope Deformations with Sentinel-1 InSAR Analyses in the Southwest Area of Shanxi, China

Abstract

A catastrophic landslide happened on 15 March 2019 in Xiangning County of Shanxi Province, causing 20 fatalities. Such an event makes us realize the significance of loess slope instability detection. Therefore, it is essential to identify the potential active landslides, monitor their displacements, and sort out dominant controlling factors. Synthetic Aperture Radar (SAR) Interferometry (InSAR) has been recognized as an effective tool for geological hazard mapping with wide coverage and high precision. In this study, the time series InSAR analysis method was applied to map the unstable areas in Xiangning County, as well as surrounding areas from C-band Sentinel-1 datasets acquired from March 2017 to 2019. A total number of 597 unstable sites covering 41.7 km2 were identified, among which approximately 70% are located in the mountainous areas which are prone to landslides. In particular, the freezing and thawing cycles might be the primary triggering factor for the failure of the Xiangning landslide. Furthermore, the nonlinear displacements of the active loess slopes within this region were found to be correlated significantly with precipitation. Therefore, a climate-driven displacement model was employed to explore the quantitative relationship between rainfall and nonlinear displacements.

Detection and characterization of active landslides with multisource SAR data and remote sensing in western Guizhou, China

“…Researchers have widely recognized the outstanding advantages of interferometric SAR (InSAR) in the eld of landslide investigation and displacement monitoring. (Yao et al 2017;Shi et al 2020;Liu et al 2021). However, in practice, the interference and incoherence caused by long temporal and spatial baselines, vegetation cover, and atmospheric delay all limit the use of differential InSAR (D-InSAR) technology.…”

Three-dimensional and long-term landslide displacement estimation by fusing C- and L-band SAR observations: A case study in Gongjue County, Tibet, China

“…However, most related studies (Hu et al, 2016;Shi et al, 2020;Wasowski et al, 2020) have characterized such landslide displacements only in the one-dimensional line-of-sight (LOS) direction, owing to the limitations of the SAR imaging geometry and single SAR platform. As a consequence, several challenges have arisen for detailed landslide investigations for the following reasons: (1) it is impossible to map landslide movement orthogonal to the LOS direction (Eriksen et al, 2017), thus causing the omissions of that direction for landslide detection; (2) it is difficult to analyze the dynamics and mechanisms of landslide displacement in complex situations (Samsonov et al, 2020); (3) it is inaccurate to map the boundary of landslides and to invert the depth and volume of unstable slopes.…”

Kinematic Behavior Analysis of the Wadi Landslide From Time-Series Sentinel-1 Data

“…During the observation period, the > REPLACE THIS LINE WITH YOUR MANUSCRIPT ID NUMBER (DOUBLE-CLICK HERE TO EDIT) < accelerating and decelerating periods of seasonal deformation in the five zones occurred at slightly different times. The seasonal rainfall that infiltrates into slopes will periodically change the pore water pressure and shear strength of the slopes as well as increase the slope weights [55]. The local structures, materials and different depth of slope that affect the infiltration of rainfall might cause this difference.…”