Characterising near-fault deformation in the Apennines through the use of high-resolution Pleiades optical satellite data

Bob Elliott, Ken McCaffrey, Richard Walters (all Durham University), Dave Mackenzie (3vGeomatics), Laura Gregory (Leeds University)

Characterising near-fault deformation can improve understanding of how major co-seismic slip at depth is transferred to the surface. Deformation observed close to the fault scarp can identify where there has been shallow slip deficit, and the role of minor faults adjacent to the main faults as controlling influences in co-seismic slip distribution. However, field work and remote sensing techniques such as InSAR and GNSS are often inefficient or unreliable in characterising near-fault deformation due to exposure and data resolution issues. We use high resolution topographical models from optical satellite data from the Pleiades constellations to help identify the co-seismic deformation associated with the 30^th October 2016 Norcia earthquake.  We jointly inverted a total of 11 datasets including Pleiades-derived DEM difference data, InSAR and GNSS (far-field and short baseline)) for slip at depth following the method of Okada (1985). Compared to previous models derived from geodetic datasets, we used a relatively complicated fault geometry set-up in the area covered by the Pleiades datasets. By combining the near-fault input provided by the Pleiades data with far-field data we were able to model near-surface slip as well as slip at depth with a good fit to the Pleiades data, without losing the fit to the far-field data. The results show remarkable detail of slip transfer from the main faults onto minor structures in the hanging wall of the Monte Vettore fault within the top 2 km below the surface. Slip vectors near the surface also display considerable divergence from slip vectors at depth. This research provides valuable insight into the distribution of near-fault co-seismic slip in an area of complex faulting,