StaMPS Improvement for Deformation Analysis in Mountainous Regions: Implications for the Damavand Volcano and Mosha Fault in Alborz

Abstract

Interferometric Synthetic Aperture Radar (InSAR) capability to detect slow deformation over terrain areas is limited by temporal decorrelation, geometric decorrelation and atmospheric artefacts. Multitemporal InSAR methods such as Persistent Scatterer (PS-InSAR) and Small Baseline Subset (SBAS) have been developed to deal with various aspects of decorrelation and atmospheric problems affecting InSAR observations. Nevertheless, the applicability of both PS-InSAR and SBAS in mountainous regions is still challenging. Correct phase unwrapping in both methods is hampered due to geometric decorrelation in particular when using C-band SAR data for deformation analysis. In this paper, we build upon the SBAS method implemented in StaMPS software and improved the technique, here called ISBAS, to assess tectonic and volcanic deformation in the center of the Alborz Mountains in Iran using both Envisat and ALOS SAR data. We modify several aspects within the chain of the processing including: filtering prior to phase unwrapping, topographic correction within three-dimensional phase unwrapping, reducing the atmospheric noise with the help of additional GPS data, and removing the ramp caused by ionosphere turbulence and/or orbit errors to better estimate crustal deformation in this tectonically active region. Topographic correction is done within the three-dimensional unwrapping in order to improve the phase unwrapping process, which is in contrast to OPEN ACCESS Remote Sens. 2015, 7 8324 previous methods in which DEM error is estimated before/after phase unwrapping. Our experiments show that our improved SBAS approach is able to better characterize the tectonic and volcanic deformation in the center of the Alborz region than the classical SBAS.In particular, Damavand volcano shows an average uplift rate of about 3 mm/year in the year 2003-2010. The Mosha fault illustrates left-lateral motion that could be explained with a fault that is locked up to 17-18 km depths and slips with 2-4 mm/year below that depth.

Wuhan Surface Subsidence Analysis in 2015–2016 Based on Sentinel-1A Data by SBAS-InSAR

“…This phenomenon leads to signal decorrelation (e.g., temporal and spatial decorrelation) and reduces monitoring accuracy of InSAR [18]. To overcome limitations of this technique, time-series InSAR (TS-InSAR) has been proposed [19][20][21]. TS-InSAR extracts deformation information by simultaneously processing multi-SAR images obtained on different dates.…”

Impacts of Temporal-Spatial Variant Background Ionosphere on Repeat-Track GEO D-InSAR System

“…Even in the area with a lower fringe frequency, the largest deformation retrieval error in the scene is higher than 0.2 m and the mean square root error of the deformation is 0.13 m, which cannot satisfy the requirements for the deformation retrieval accuracy in any engineering applications. Therefore, some compensation algorithms based on Persistent Scatterer technology (PS) [4,[33][34][35][36][37] or some similar methods based on the high quality coherent points are really needed to eliminate the serious impacts of the interferometric phase screen errors brought by the temporal-spatial background ionosphere variation in GEO D-InSAR processing in the future. Utilizing the USTEC data in Figure 4 and Equation (14), the interferometric phase screen errors generated by 1 ( ) Φ P  and 2 ( ) Φ P  are shown in Figure 7a.…”

On the Use of the ISBAS Acronym in InSAR Applications. Comment on Vajedian, S.; Motagh, M.; Nilfouroushan, F. StaMPS Improvement for Deformation Analysis in Mountainous Regions: Implications for the Damavand Volcano and Mosha Fault in Alborz. Remote Sens. 2015, 7, 8323–8347

“…Therefore, we would propose the adoption of an alternative acronym for the Vajedian et al method and, with regard to [1], encourage amendment of the paper via a corrigendum.…”

“…The modification includes many steps including the filtering of the differential interferograms, integration with GPS data and advanced phase unwrapping "to overcome a lot of short-and long-wavelength artifacts that are clearly visible in StaMPS results" (cf. [1], p. 8331). The authors refer to this new approach as the Improved SBAS, or ISBAS, method.…”

“…Academic Editors: Richard Gloaguen and Prasad S. Thenkabail Vajedian et al [1] present an improved method for the derivation of deformation parameters using satellite Interferometric Synthetic Aperture Radar (InSAR) data. The method is a modification of the Small Baseline Subset (SBAS) method as implemented in the StaMPS (Stanford Method for Persistent Scatterers) software.…”