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Abstract

We assemble a processing chain that handles InSAR computation from raw data to time series analysis. A large part of the chain (from raw data to geocoded unwrapped interferograms) is based on ROI PAC modules (Rosen et al., 2004), with original routines rearranged and combined with new routines to process in series and in a common radar geometry all SAR images and interferograms. A new feature of the software is the range-dependent spectral filtering to improve coherence in interferograms with long spatial baselines. Additional components include a module to estimate and remove digital elevation model errors before unwrapping, a module to mitigate the effects of the atmospheric phase delay and remove residual orbit errors, and a module to construct the phase change time series from small baseline interferograms (Berardino et al. 2002). This paper describes the main elements of the processing chain and presents an example of application of the software using a data set from the ENVISAT mission covering the Etna volcano. The detection of slow, time-dependent ground motion using the InSAR technique requires the analysis and combination of multiple radar data takes over an extended time period. Processing individual image pairs, one at a time, becomes difficult and time consuming when exploiting the large amount of data in the archive of recent missions (ERS, Envisat, RADARSAT). This task will become even greater with future missions like Sentinel-1 with a return period of 12 days. The NSBAS package is a fully automatic chain of processing producing a timelines of the line of sight surface movement over an area. It has been especially optimized for the monitoring of transient ground motion of small amplitude, taking place over large areas and in natural settings. In the next sections we synthethize the various features of the chain and refer to publications for the original description and discussion of the software components applied to various natural processes. The NSBAS processing chain is depicted in a flow diagram in Fig. 1. In the present paper, it is applied to the study of the Geohazards Supersite of Mount Etna volcano using Envisat data from an ascending track (Fig. 2) This dataset has been well studied and provides us with a good case example. It consists of 63 SAR data between 2003 and 2010.