Northeastern Italy is an area characterized by an active tectonic regime with a convergence rate of about 2 mm/yr due to the NNW motion of the Adria plate and its counterclockwise rotation with respect to Eurasia.  The N-S shortening is accommodated by the Southeastern Alps and the External Dinarides, mainly dominated by active thrust-and-fold systems and strike-slip faults (D’Agostino et al., 2005; Serpelloni et al., 2016). In the present study, we exploited the potential of geodetic data to extract information about the surface deformation in response to active tectonics.   We used a Multi-Temporal InSAR approach called Stanford Method for Persistent Scatterers (StaMPS). The technique, based on the detection of coherent and temporally stable pixels in a stack of single-master differential interferograms, allows obtaining mean ground velocity maps. We used Sentinel-1 SAR images acquired in ascending and descending orbits, spanning 2015-2019 temporal interval, as inputs for SNAP2StaMPS and StaMPS software (Foumelis et al., 2018; Hooper et al., 2012). After the PSI processing, we applied spatial-temporal filters and we performed some post-processing operations to obtain reliable PS candidates. We also performed a calibration by using Adria-fixed GNSS velocities to remove orbital ramps and residual atmospheric contributions. Finally, we obtained Line-Of-Sight calibrated mean ground velocity maps for ascending and descending tracks and, after the decomposition, East-West and vertical velocity maps. According to the results, we identify some deformation patterns, potentially related to active tectonics. Towards the Alps, we notice a positive vertical signal reaching about 2 mm/yr. In contrast, the East-West map shows deformation patterns with 1-2 mm/yr rate on the northeastern sector and on the Friulian pedemountain and plain areas. The analysis and the modeling of these signals will clarify the relationship with active tectonics in the study area.

Displacement rate measurement in Northeastern Italy by using PS-InSAR and GNSS data

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