Best Practice for Integrating InSAR and GNSS Observations in High-Density GNSS Networks

Synthetic Aperture Radar Interferometry (InSAR) is widely used to monitor ground deformation, but its results are relative to a local satellite-based reference system. To enable consistent geodetic interpretation, InSAR velocities must be aligned to a terrestrial reference frame, typically using Global Navigation Satellite System (GNSS) data. This study aims to identify the most effective referencing strategy to align ascending and descending InSAR datasets to the European Terrestrial Reference Frame (ETRF), using a dense GNSS network in a subsidence-affected area of northern Italy. We tested several referencing approaches by varying: (i) the number and configuration of GNSS stations, (ii) the density of Persistent Scatterers (PS) used to calculate local InSAR velocities, and (iii) the modeling of InSAR-GNSS differences, using either a bias, a plane, or a second-order polynomial surface. Results show that the optimal referencing is achieved by modeling the differences with a planar surface, using all available GNSS stations, and computing InSAR velocities from PS within 100 m of each station. This approach minimized post-referencing residuals more effectively than other methods, including polynomial fitting. Following referencing, InSAR data from both geometries are merged to extract the vertical (Up) and horizontal (East) components of motion, demonstrating alignment with the GNSS-based reference system. These findings highlight how referencing performance depends on both the modeling strategy and GNSS-PS configuration, providing guidance for improving InSAR accuracy in geodetic applications.