Assessing small-scale surface deformation zones using GNSS-based imaging: a case-study for Europe

Summary Dense GNSS station networks and highly accurate 3D velocities offer the potential to image small-scale surface deformation fields. The robustness and sensitivity of the applied algorithm are essential for the reliable detection of local and potentially small, horizontal, or vertical deformation. We present the new Robust 3D Imaging (R3DI) approach, which relies on a multivariate median estimate of the horizontal strain rate and local rotation and utilizes an increasing number of stations until the results are significant at the 2σ level. This approach allows for a robust estimate, while the spatial resolution achieved depends solely on the density of the station network and the local deformation rate. Checkerboard tests with synthetic velocities based on a regular deformation pattern in Europe confirmed the robust recovery of extension and contraction cells. Velocities predicted from the recovery show a median difference of 0.04 mm yr−1 (length similarity of 74.9 %) compared to the inputs. R3DI can also estimate vertical land motion at the same spatial resolution as used in the strain rate estimation. A recovery of the robustly imaged deformation in Europe reveals, for example, the large-scale GIA-related extension of +12 nstrain yr−1 in the area of maximum uplift rates in Scandinavia, as well as small-scale contractions of −134 nstrain yr−1 above the Groningen gas field. The gridded velocity field, determined from the velocity gradient tensor, indicates that R3DI is capable of automatically determining plate boundaries if a sufficient station network is provided. The gridded velocity field is compared against the recently published EuVeM2022 and shows mean horizontal velocity differences of 1.1 mm yr−1 over entire Europe or 0.4 mm yr−1 for the stable part of Europe.