Multisource InSAR analysis of post-failure deformation and risk evolution: A case study of the Guang'an Village landslide, Chongqing, China

Post-failure monitoring of large-scale landslides is crucial for detecting ongoing instability and assessing the risk of secondary slope movements. However, existing MTInSAR studies on post-failure landslides often focus primarily on the main sliding body, offering limited quantitative insight into potential failures in adjacent source and deposit zones—especially in low-coherence vegetated terrain. This study investigates the long-term post-failure deformation of the Guang'an Village landslide in Chongqing, China, by integrating multisource InSAR observations and DEM-based volumetric analysis. We processed 101 Sentinel-1A and 7 ALOS-2 SAR images using an enhanced StaMPS-SBAS workflow to derive continuous deformation time series from 2017 to 2021. A high-resolution DEM derived from TerraSAR-X/TanDEM-X (TSX/TDX) was employed to quantify elevation change and estimate displaced volume. Our results reveal that deformation extended well beyond the original slip surface. The highest line-of-sight velocity away from the satellite (LOS-away) occurred in potential source area 3 (PSA3) during Stage S3 (−125.3 mm/yr), whereas the maximum LOS velocity toward the satellite (LOS-toward) was observed in the source area (SA) during Stage S2 (63.9 mm/yr). Deformation persisted for nearly three years, with PSA3 exhibiting the most intense movement and a cumulative displacement of −331.2 mm. Rainfall was identified as the dominant driver of residual deformation, as evidenced by strong correlations in PSA3 and SA (r = 0.98). DEM differencing between TSX/TDX and SRTM yielded an estimated original displaced volume of ~6.26 × 10⁶ m³. Based on deformation-constrained indicators, we developed a locally calibrated volume–area model to estimate a potential secondary failure volume of ~1.37 × 10⁶ m³. These findings demonstrate the effectiveness of combining InSAR time-series analysis with volumetric modeling to assess residual landslide activity and support early warning of secondary failures.