SNAPxtra: An Open-Source Python Workflow for Automated Multi-Temporal InSAR Deformation Monitoring with SNAP

Interferometric Synthetic Aperture Radar (InSAR) is a satellite–based remote sensing technique capable of measuring surface displacement. However, InSAR measurements can be affected by temporal decorrelation, baseline geometry, and surface characteristics. Persistent scatterer (PS) and small baseline subset (SBAS) are two widely used multi-temporal InSAR techniques for addressing these limitations. Processing SAR acquisitions to derive deformation maps and displacement time series requires a series of complex steps. Many existing open-source and commercial software packages support PS or SBAS, while some support both methods, each with its own challenges and limitations. In this study, we presnet SNAPxtra, a Python-based InSAR automatic workflow to generate PS and SBAS interferometric stacks. These can be exported in the format required for time-series analysis in LiCSBAS and StaMPS. SNAPxtra has automated master selection, multi-swath and multi-frame processing, polygon-based masking, trial processing, and network generation features within an integrated workflow. The reproducibility and adaptability of SNAPxtra are demonstrated through case studies in Quetta (Pakistan), Surat (India), and Fort Worth (USA) as case studies using both PS and SBAS methods.