Strategies for Measuring Large Scale Ground Surface Deformations: PSI Wide Area Product Approaches

Kurzfassung

The Wide Area Product (WAP) is a new interferometric product developed to provide measurement over large regions. Persistent Scatterers Interferometry (PSI) has largely proved their robust and precise performance in measuring ground surface deformation in different application domains. This technology was validated within a PSI certification activity included in the Terrafirma project, funded by the European Space Agency, where PSI results produced by different processing chains were validated against them and ground data. The inter-comparison reported that precisions below 1mm/year are achieved and the Root Mean Square Error (RMSE) ranges from 0.8 to 1.5 mm/year, based on ERS and ENVISAT data and ground survey. This validation demonstrates the great accuracy of PSI technique for measuring ground surface deformation in relatively local (20km) and pilot test areas (urban and rural areas with non-pronounced topography). In this context, however, the accurate displacement estimation over large-scale areas (more than 10.000km2) characterized by low magnitude motion gradients (3-5 mm/year), such as the ones induced by inter-seismic or Earth tidal effects, still remains an open issue. The main reason for that is the inclusion of low quality and more distant persistent scatterers in order to bridge low-quality areas, such as water bodies, crop areas and forested regions. This fact yields to spatial propagation errors on PSI integration process, poor estimation and compensation of the Atmospheric Phase Screen (APS) and the difficult to face residual long-wavelength phase patterns originated by orbit state vectors inaccuracies. Research work for generating a Wide Area Product of ground motion in preparation for the Sentinel-1 mission has been conducted in the last stages of Terrafirma as well as in other research programs. These developments propose technological updates for keeping the precision over large scale PSI analysis. Some of the updates are based on the use of external information, like meteorological models, and the employment of GNSS data for an improved calibration of large measurements. The main characteristic of a Wide Area processor shall be the capacity of concatenating parallel orbit tracks and consecutive image frames to avoid any constrain in terms of ground coverage. This is a key factor and represents the novelty of the product for particular applications like tectonic studies where maps at regional scale should be provided. Despite covering wide regions, the retrieval of large scale motions can, however, not be possible depending on the processing approach. In terms of data processing, the tests performed showed that several steps may condition the final result and should thus be carefully taken into account: the spatial resolution of the interferograms, the point network selection, the integration from a unique seed or based on several distributed seeds, and the APS estimation and calibration between different tracks among others. Depending on the configuration and performances of the different PSI processing steps, large trends or local episodes may be underestimated; therefore a standard processing is yet to be defined. The present work wants to contribute to this open topic by exposing the experience of the authors in PSI Wide Area processing over different thematic fields. The lessons learnt and the main limitations along the way will be described and analyzed. Furthermore, the different WAP strategies developed by the authors will be discussed in order to maximise the trade-off between large-scale motion and local phenomena monitoring. Conclusions and recommendations will be extended in terms of the Sentinel-1 data. The default mode of Sentinel-1, the Interferometric Wide Swath Mode, as well as the regular acquisitions plan over tectonic belts foreseen by ESA and other initiatives like COMET+, highlight the significance of this topic. Consequently, it is important to set the state of the art, identify requirements and limitations and propose solutions to them.