Preprints
https://doi.org/10.5194/sed-6-2759-2014
https://doi.org/10.5194/sed-6-2759-2014
17 Sep 2014
 | 17 Sep 2014
Status: this preprint was under review for the journal SE. A revision for further review has not been submitted.

An improved approach to estimate large-gradient deformation using high resolution TerraSAR-X data

D. Liu, R. Chen, B. Riedel, and W. Niemeier

Abstract. Interferometric Synthetic Aperture Radar (InSAR) has shown unique capabilities in numerous applications for deformation monitoring. However, InSAR will lose effectiveness with large-gradient deformation due to the limitation of maximum detectable phase gradient and the phase unwrapping step of InSAR. Coalfield is the exact object providing such challenges for InSAR technique. Strong mining activities often induces large scale non-linear deformation with large gradient. This paper integrates offset tracking technique based on Corner Reflector (CR) and InSAR to overcome relevant problems. By applying offset tracking to high resolution TerraSAR-X intensity images, the coarse estimation of large deformation was obtained and extracted, allowing the following InSAR processing to carry out phase unwrapping correctly. Finally, the fine estimation of deformation was done by the Persistent Scatterer InSAR (PSI) technique. The detected deformation time series indicated good root-mean-square errors (RMSE), validated by GPS in situ investigation. All InSAR data were processed in the open source software StaMPS and one in-house InSAR package.

D. Liu, R. Chen, B. Riedel, and W. Niemeier
 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
D. Liu, R. Chen, B. Riedel, and W. Niemeier
D. Liu, R. Chen, B. Riedel, and W. Niemeier

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