Deciphering Landslide Formation and Evolution Processes: A Time Series Interferometric Synthetic Aperture Radar-Based Investigation

This study advances landslide monitoring methodologies through time-series Interferometric Synthetic Aperture Radar (InSAR) techniques, specifically implementing the Small Baseline Subset (SBAS) approach to overcome limitations of traditional differential InSAR. By generating robust displacement time series with enhanced temporal resolution and reduced noise interference, our implementation successfully revealed distinct spatio-temporal patterns of landslide movement with high precision. Integration with an existing landslide inventory enabled development of a quantitative classification framework categorizing landslides by deformation magnitude (low, moderate, and high). The framework revealed that while most active landslides exhibit low to moderate deformation rates, the small subset showing high deformation rates presents significantly larger cumulative displacements indicating greater hazard potential. This integrated approach establishes a robust methodology for landslide characterization, activity assessment, and hazard zonation that substantially improves upon traditional monitoring techniques and provides valuable decision support for disaster risk reduction strategies.