Mitigating Residual Errors in Decadal InSAR Time-Series: An SBAS Analysis of Surface Deformation in Oran, Algeria

Interferometric Synthetic Aperture Radar (InSAR) time-series analysis is an indispensable tool for monitoring surface deformation and mitigating regional geohazards. In this study, we apply the Small Baseline Subset (SBAS) technique via the open-source MintPy framework to analyze complex ground displacement in the Oran region of Algeria, utilizing a decade-long Sentinel-1 dataset (March 2015–April 2025). Because extracting sub-centimeter deformation signals is inherently complicated by phase delays, we systematically implemented a rigorous geodetic processing chain. Our methodology prioritized the sequential application of corrections, including ERA5-based tropospheric mitigation, ionospheric adjustments, Digital Elevation Model (DEM) error rectifications, Solid Earth Tide (SET) adjustments, and phase ramp corrections to eliminate large-scale spatial biases. The most discriminating contribution of this research, however, is the meticulous integration of tectonic plate motion corrections. By leveraging established geophysical models (GSRM and MORVEL) anchored in the ITRF2014 reference frame, we precisely projected these movements into the satellite's line of sight (LOS) to filter out global plate kinematics. This transformation induced a radical shift in the observed residual velocity field, changing the prevailing signal from a sensor-receding motion to a sensor-approaching motion. Ultimately, this framework enabled the mapping of local crustal deformations—specifically categorizing zones of subsidence, uplift, and stability—with millimetric precision. These high-fidelity results validate the robustness of the SBAS approach, providing fundamental insights into regional geological processes and offering essential support for the proactive management of natural and anthropogenic risks.