Identifying Potential Landslides in Low-Coherence Areas Using SBAS-InSAR: A Case Study of Ninghai County, China

The southeastern coastal regions of China are characterized by typical hilly terrain with abundant rainfall throughout the year, leading to frequent geological hazards. To investigate the measurement accuracy of surface deformation and the effectiveness of error correction methods using the small baselines subset–interferometry synthetic aperture radar (SBAS-InSAR) method in identifying potential geological hazards in such areas, this study processes and analyzes 129 SAR images covering Ninghai County, China. By processing coherence coefficients using the Stacking technique, errors introduced by low-coherence images during phase unwrapping are mitigated. Subsequently, interferograms with high coherence are selected for time-series deformation analysis based on the statistical parameters of coherence coefficients. The results indicate that, after mitigating errors from low-coherence images, applying the SBAS-InSAR method to only high-coherence SAR datasets provides reliable surface deformation results. Additionally, when combined with field geological survey data, this method successfully identified landslide boundaries and potential landslides not accurately detected in previous geological surveys. This study demonstrates that using the SBAS-InSAR method and selecting high-coherence SAR images based on interferogram coherence statistical parameters significantly improves measurement accuracy and effectively identifies potential geological hazards.