Land subsidence estimation on coastal land using improved combined scaterers interferometry with optimization (icops) approach for insar time series

Land subsidence is a global concern that can result in infrastructure damage and property devaluation. We proposed the improved combined scatterers interferometry with optimized point scatterers (ICOPS) method for analyzing land surface deformation using InSAR time-series data. The method combined persistent scatterers (PS) and distributed scatterers (DS) to enhance spatial coverage. The distributed scatterers were generated using a spatial homogeneity evaluation based on a likelihood ratio test with coherence evaluation to maintain the quality of pixels. A key aspect of this research involved post-processing optimization using machine learning and statistical approaches. Support vector regression (SVR) was applied to determine the optimal measurement points based on time-series characteristics. Optimization hotspot analysis minimized interference from uncorrelated points, resulting in a clustered deformation map. The study demonstrated the ICOPS methods in measuring land subsidence, revealing that the coastal reclamation land in the Bugok Industrial Zone, Dangjin, South Korea experienced a significant mean deformation rate of approximately 2-5 cm/year from 2017 to 2019. Overall, the ICOPS method is a valuable tool for analyzing coastal reclamation land in South Korea, providing enhanced accuracy and reliability, and offering valuable insights into dynamic processes for monitoring and managing such areas.