The Advancement of Intraplate Tectonic Motion Detection by the Use of Atmospherically Corrected InSAR Time-series and its Decomposition into a 3D Field Vector in South-East Sicily, Italy.

Abstract:

This study provides insights into the advancements gained by applying a tropospheric correction to a time-series InSAR small baseline network processed using the StaMPS software for the Hyblean Plateau in south-east Sicily, Italy. The contribution of the atmosphere is one of the major error sources in repeat-pass InSAR in general. For time-series analysis spatial and temporal filtering of the interferometric phase can be used to address atmospheric signals. This however might be at the cost of smoothing and removal of the tectonic deformation. We applied a tropospheric correction to each interferogram based on estimates of the ERA-Interim weather model, provided by the European Center for Medium-Range Weather Forecast (ECMWF). This approach is part of the InSAR Atmospheric Correction Toolbox (Bekaert et al, in prep) and converts the tropospheric water vapor content into the phase-delay of the radar line-of-sight. For the analysis we used 49 descending and 58 ascending Envisat SAR images, which cover the time period from 2003 until 2010. In addition, we have processed 30 SAR images of RADARSAT-2 for the period between 2010-2012. Furthermore, we used the different viewing geometries and the integration of GPS data to decompose the single line-of-sight velocities into a 3-dimensional field vector by applying the SISTEM approach (Guglielmino et al. 2011).

First results reveal that the atmospherically corrected data retain the deformation signal along geological structures like the Scicli-Ragusa fault whilst the standard filtering approach is canceling out these very slow deformation patterns. Simultaneously, the variability of the signal in space is diminished and thus gives more confidence on the deformation patterns observed by the SAR. Consequently, the decomposition of the line-of-sight velocities and the integration with the GPS data allows us to retrieve a more realistic deformation field.