River embankments are designed to defend against floods over coastal and riparian areas. It is important to early detect unexpected damages on embankments before they exacerbate. To continuously monitor the stability of the embankments and efficiently recognize such potential damages, this study takes SAR (Synthetic Aperture Radar) derived deformation as an indicator of the embankment instability, and customizes a multi-temporal InSAR (Interferometric SAR) approach-small baseline subset. Specifically, during InSAR processing, we apply a two-step amplitude difference dispersion threshold method to extract InSAR measurement points, thus improving the point density within the embankment. We applied this method to the Kangshan Embankment (KE) using 147 Sentinel-1 acquired between 2017 and 2021. We categorized KE into Waterside Slope (WS), Embankment Top (ET), and Landside Slope (LS) using InSAR height estimation. Given the dominance of downslope movement, we developed a projection matrix from InSAR-derived deformation in the satellite line-of-sight direction onto WS and LS. The study shows that KE was generally stable during the five-year period, while WS, ET, and LS experienced different deformation processes. For instance, seasonal variation was observed from the deformation time series, especially between every April and November. We applied the principal component analysis to the time-series displacement and analyzed the results in conjunction with the rainfall data of Kangshan Township. It showed that deformation due to rainfall equals 80.93%, 81.30%, and 82.46% of the total deformation for WS, ET, and LS, respectively, indicating that rainfall is one of the environmental driving factors affecting the deformations. We conclude that the proposed methodology is suited for systematic embankment monitoring and identifies major driving forces.
Xiong et al. (2025) studied this question.