Comparative Analysis of PS-InSAR and NSBAS Methods for Land Subsidence Monitoring in Urban Coastal Areas

Abstract: This study investigates the performance and accuracy of two Synthetic Aperture Radar (SAR) processing methodologies for monitoring land subsidence in North Jakarta, employing the Persistent Scatterer Interferometry SAR (PS-InSAR) and New Small Baseline Subset (NSBAS) techniques. Sentinel-1A imagery was processed to compare the outputs of these approaches in terms of spatial coverage, statistical precision, and computational efficiency. Validation was conducted using the Monte Carlo sampling method and field data from the Balai Konservasi Air Tanah (BKAT). The results indicate that PS-InSAR achieves denser spatial coverage and higher confidence levels, with an average deviation of 7 mm/year and accuracy exceeding 90%. In contrast, NSBAS exhibits advantages in processing efficiency and broader mapping capabilities but generates a higher proportion of data gaps, particularly in urban coastal regions. These findings emphasize the critical role of methodological selection in SAR-based land subsidence assessments and the implications of algorithmic differences on the reliability of subsidence models. The study provides valuable insights for researchers and practitioners in selecting appropriate SAR processing techniques for urban deformation analysis. Keywords: Synthetic Aperture Radar, Sentinel-1 A, land subsidence, North Jakarta.