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A stack of images is a prerequisite for the multi-temporal interferometric synthetic aperture radar (MT-InSAR) due to the wrapped nature of the interferometric phase. Although the SBAS technique can relieve the requirement of the amount of SAR data, dozens of SAR acquisitions could be regarded as the minimum requirement. However, due to the limitation of the imaging capability of the spaceborne SAR system, the amount of available SAR data acquired from only one SAR sensor is often not enough to satisfy the requirement for phase unwrapping based on the Nyquist sampling assumption. Fortunately, there sometimes may be more than one SAR stack, that is, stacks of SAR data acquired from different SAR systems. In this study, we propose a methodology to detect ground deformation by combining multiple SAR images acquired from different satellite systems for MT-InSAR analysis. First, the low-pass deformation is estimated based on time series SAR acquisitions with low spatial resolution and long wavelengths such as ENVISAT ASAR (ASAR). This information is then incorporated into the processing of time series of SAR acquisitions with high spatial resolution and short wavelength, such as TerraSAR-X (TSX). Specifically, the low-pass deformation will be subtracted from each differential interferogram generated from short-wavelength SAR images, and the rest of the MT-InSAR analysis will be based on the double-differentiation interferograms. Then, the residual deformation will be calculated from these double-differentiation interferograms and together with the low-pass deformation forms the full deformation. As the principal component of deformation has already been subtracted, the phase gradient of those double-differentiated interferograms will be smooth enough to facilitate the phase unwrapping. Between January 2009 and September 2010, 14 ASAR images and 11 TSX images acquired from Tianjin, China are selected as the test data. A root means square error (RMSE) of 9.1 mm/year is achieved from 11 TSX images, while a root means square error of 3.7 mm/year is achieved from 14 ASAR images. However, an RMSE of 1.6 mm/year is achieved when integrating 11 TSX images and 14 ASAR images for MT-InSAR analysis. The experiments show that the proposed method can effectively detect ground deformation.

Describing the dynamic characteristics of glacier surge events is a precursor to being able to understand their driving mechanisms. Here, a comprehensive suite of surface velocities and surface elevation changes for the surging South Rimo Glacier (SRG), situated in the East Karakoram region, are obtained by offset-tracking from Sentinal-1A and geodetic method from TerraSAR-X/TanDEM-X and Ice, Cloud, and land Elevation Satellite-2 Advanced Topographic Laser Altimeter System. The surge of SRG initiated in the summer of 2018, and the rapid and dramatic increase in surface velocities reached a peak (∼12 m d−1) in August 2019. By the summer of 2020, the surface velocity of SRG had returned to its pre-surge level. We interpret that the evolution of the latest SRG surge was probably triggered by changes in subglacial thermal conditions, and was ultimately accelerated by hydrological processes. Based on historical analysis, a surge return period of ∼25–30 years prevails at SRG. Spatiotemporal analyses of surface velocities and elevation changes such as these can provide useful information about surge mechanisms and their controls.