Keywords: InSAR, Hybrid PS-SBAS, railway monitoring, bridge transition zone, railway track geometry, turnouts, railway track settlement, long-term monitoring, descriptive modelling, data analytics.

Railway transition zones are prone to differential settlements that degrade track geometry and operational safety. Traditional monitoring relies on periodic inspections with insufficient temporal coverage for early detection of problematic settlement trends. This study presents a systematic approach integrating Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) and Small Baseline Subset (SBAS) techniques for enhanced differential settlement detection and analysis. A hybrid PS-SBAS processing sequence leverages PS-InSAR's high spatial resolution and SBAS's broader coverage, optimized for railway environments with variable coherence. The methodology incorporates advanced noise reduction, atmospheric correction, and robust time-series post-processing, addressing phase unwrapping errors and outlier displacements. Applied to a 1.6 km Lisbon–Porto railway segment, the approach demonstrates strong correlation with conventional track inspection data, particularly in transition zones including bridge approaches and switches. Results show the hybrid method provides denser, more reliable displacement measurements, capturing long-term settlement patterns and identifying differential settlement hotspots. Findings support satellite-based InSAR as a complementary tool for railway infrastructure monitoring, offering valuable insights for maintenance planning and risk management in resilient transport systems.

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