Mapping slope movements in Alpine environments using TerraSAR-X interferometric methods

Abstract

Mapping slope movements in Alpine environments is an increasingly important task in the context of climate change and natural hazard management. We propose the detection, mapping and inventorying of slope movements using different interferometric methods based on TerraSAR-X satellite images. Differential SAR interferograms (DInSAR), Persistent Scatterer Interferometry (PSI), Short-Baseline Interferometry (SBAS) and a semi-automated texture image analysis are presented and compared in order to determine their contribution for the automatic detection and mapping of slope movements of various velocity rates encountered in Alpine environments. Investigations are conducted in a study region of about 6 km  6 km located in the Western Swiss Alps using a unique large data set of 140 DInSAR scenes computed from 51 summer TerraSAR-X (TSX) acquisitions from 2008 to 2012. We found that PSI is able to precisely detect only points moving with velocities below 3.5 cm/yr in the LOS, with a root mean squared error of about 0.58 cm/yr compared to DGPS records. SBAS employed with 11 days summer interferograms increases the range of detectable movements to rates up to 35 cm/yr in the LOS with a root mean squared error of 6.36 cm/yr, but inaccurate measurements due to phase unwrapping are already possible for velocity rates larger than 20 cm/year. With the semi-automated texture image analysis the rough estimation of the velocity rates over an outlined moving zone is accurate for rates of ''cm/day", ''dm/month" and ''cm/month", but due to the decorrelation of yearly TSX interferograms this method fails for the observation of slow movements in the ''cm/yr" range..

Ground uplift related to permeability enhancement following the 2011 Tohoku earthquake in the Kanto Plain, Japan

“…The mean of the absolute difference of time series displacements was 3.0 mm. The accuracy almost corresponded with previous PSI studies using TerraSAR-X, which shows that the PSI result agrees with the GPS data (e.g., Yu et al 2013;Luo et al 2014;Barboux et al 2015). The PSI result demonstrates that the local uplift area did not have a clear ellipsoidal shape, but rather had a more complex spatial pattern, such as a fractal surface, than that inferred by GPS analysis.…”

Multi-Temporal X-Band Radar Interferometry Using Corner Reflectors: Application and Validation at the Corvara Landslide (Dolomites, Italy)

“…Nevertheless, displacements occurring parallel to the satellite track were largely underestimated. In this latter case, the PS-MTI technique might also have problems in the precise detection of points moving with velocities below 3.5 cm/year in the LOS, as found by Barboux et al [51].…”

“…Notti et al [50] demonstrated the potential of X-band SAR data using TerraSAR-X for landslide mapping and monitoring but a few natural PS were found in mountainous areas. Barboux et al [51] used the same band, combining PS-MTI and SBAS techniques for mapping slow movements in the Alps comparing these results to Real Time Kinematic GPS surveys. Barboux et al [52] was also limited to precisely detect points moving with velocities below 3.5 cm/year in the LOS by PS-MTI technique.…”

Innovative methods to monitor rock and mountain slope deformation

“…The most promising time series analyses for surface deformation in mountainous regions are PSI/IPTA (Persistent Scatterer Interferometry/Interferometric Point Target Analysis) and multidimensional SBAS (MSBAS) [29] [30]. Both techniques are using differential InSAR (DInSAR) using phase changes between two images in a given time to monitor lateral deformation, by filtering the topographic phase using a reference DEM.…”