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Decomposing DInSAR time-series into 3-D in combination with GPS in the case of Low strain rates: An application to the hyblean plateau, Sicily, Italy

Academic Article
Publication Date:
2017
abstract:
Differential Interferometric SAR (DInSAR) time-series techniques can be used to derive surface displacement rates with accuracies of 1 mm/year, by measuring the one-dimensional distance change between a satellite and the surface over time. However, the slanted direction of the measurements complicates interpretation of the signal, especially in regions that are subject to multiple deformation processes. The Simultaneous and Integrated Strain Tensor Estimation from Geodetic and Satellite Deformation Measurements (SISTEM) algorithm enables decomposition into a three-dimensional velocity field through joint inversion with GNSS measurements, but has never been applied to interseismic deformation where strain rates are low. Here, we apply SISTEM for the first time to detect tectonic deformation on the Hyblean Foreland Plateau in South-East Sicily. In order to increase the signal-to-noise ratio of the DInSAR data beforehand, we reduce atmospheric InSAR noise using a weather model and combine it with a multi-directional spatial filtering technique. The resultant three-dimensional velocity field allows identification of anthropogenic, as well as tectonic deformation, with sub-centimeter accuracies in areas of sufficient GPS coverage. Our enhanced method allows for a more detailed view of ongoing deformation processes as compared to the single use of either GNSS or DInSAR only and thus is suited to improve assessments of regional seismic hazard.
Iris type:
1.1 Articolo in rivista
Keywords:
DInSAR time-series, GPS, Joint inversion, Neotectonics, SISTEM, StaMPS, TRAIN, Tropospheric correction, Earth and Planetary Sciences
List of contributors:
Vollrath, Andreas; Zucca, Francesco; Bekaert, David; Bonforte, Alessandro; Guglielmino, Francesco; Hooper, Andrew J.; Stramondo, Salvatore
Authors of the University:
ZUCCA FRANCESCO
Handle:
https://iris.unipv.it/handle/11571/1181184
Published in:
REMOTE SENSING
Journal
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URL

http://www.mdpi.com/2072-4292/9/1/33/pdf
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