In this paper, we propose a method for the analysis of tectonic movement and crustal deformation by using GNSS baseline length change rates or baseline linear strain rates. The method is applied to daily coordinate solutions of continuous GNSS stations of the Crustal Movement Observation Network of China (CMONOC). The results show that: (a) The baseline linear strain rates are uneven in space, which is prominent in the Tianshan, Sichuan-Yunnan, Qinghai-Tibet Plateau, and Yanjing areas, with a maximum value of 1 × 10⁻⁷ a⁻¹, and about two orders smaller in the South China block, the Northeast block, and the inner area of the Tarim basin, where the average baseline linear strain rates are 1.471 × 10⁻⁹ a⁻¹, 2.242 × 10⁻⁹ a⁻¹, and 3.056 × 10⁻⁹ a⁻¹, respectively; (b) Active crustal deformation and strong earthquakes in the Xinjiang area are mainly located in the north and south sides of the Tianshan block; the compression deformations both inside the Tarim block and in the southern Tianshan fault zone are all increasing from east to west, and the Tarim block is not a completely “rigid block”, with the shrinkage rate in the west part at about 1~2 mm/a; (c) The principal directions of crustal deformation in the Xinjiang, Tibet, and Sichuan-Yunnan regions are generally in the north—south compression and east—west extension, indicating that the collision and wedging between the Indian and Eurasian plates are still the main source of tectonic movements in mainland China.

The application of multitemporal interferometric synthetic aperture radar (MTInSAR) technology in bridge structural health monitoring often encounters considerable challenges due to the intricate nature of bridge structures. Notably, the thermal expansion and contraction (TEC) of bridges can lead to prominent interferometric phase jumps at the expansion joints. When the magnitude of the phase jump exceeds $\pi $ , the continuity assumption required for phase unwrapping is no longer valid. Consequently, classical phase unwrapping methods fail to accurately retrieve bridge deformation. To address this limitation, we propose an adaptive MTInSAR method that can partition the bridge into independent segments and concurrently estimate deformation from multiple reference points. The algorithm first identifies expansion joint locations using a mean square error threshold. Subsequently, reference point selection and segmental phase unwrapping are performed to derive displacement time series of persistent scatterers (PSs), where the mechanical properties of the bridge structure are considered. We validate the effectiveness of the method using 23 TerraSAR-X (TSX) images of the Shanghai Yangtze River Bridge. The results demonstrate the successful detection of expansion joints and reliable phase unwrapping in PS subnetworks. Moreover, a comparative analysis with the classical minimum cost flow (MCF) method highlights the superior adaptability and reliability of the proposed approach. Finally, threshold values for triggering conditions when phase jumps occur are quantified. The proposed work will enhance the robust monitoring of bridge motions, safeguarding the structural health of bridges.

With well-controlled orbits and more accurate timing system of the new generation SAR satellites, the ability of high precision geolocation with multiple SAR acquisitions has been verified based on radar reflectors. In this paper, SAR absolute and differential geolocation methods are introduced and implemented to retrieve coordinates of two different types of radar reflectors: corner reflectors and multi-directional dihedral reflectors. The experimental results demonstrate that decimeter even centimeter level positioning accuracy can be obtained by SAR stereo geolocation based on multi-aspect SAR acquisitions from RadarSAT-2, Cosmo-SkyMed, Sentinel-1 and TerraSAR-X, respectively.

Interferometric Synthetic Aperture Radar (InSAR) has become an essential tool for monitoring surface deformation with high precision and wide spatial coverage. Among various InSAR techniques, the Stacking InSAR approach is widely used for geological hazard assessments due to its computational efficiency and robustness against decorrelation noise. However, Digital Elevation Model (DEM) errors remain a significant challenge, introducing spurious deformation signals and degrading deformation rate estimates. We present here a rigorous analysis of the impact of DEM errors on Stacking InSAR-derived deformation rates and introduce an enhanced method that effectively mitigates these errors. Unlike conventional correction techniques that require explicit DEM error estimation, the proposed method leverages perpendicular baseline averaging, eliminating DEM-induced biases while maintaining computational simplicity. The method is validated using both simulated and real Sentinel-1A datasets from two tracks, with results compared against conventional Stacking and Small Baseline Subset (SBAS) approaches. The findings demonstrate that the proposed method significantly improves deformation rate estimation by suppressing DEM-induced artifacts, thereby enhancing the reliability of InSAR applications in geological hazard monitoring and deformation assessment.

As a major city in eastern China, Suzhou faces significant challenges in metro construction due to its soft soil conditions, as excavations can induce differential settlement in nearby buildings. To assess such impacts, this study employs decade-scale (2009–2019) multitemporal InSAR using high-resolution TerraSAR-X imagery. A customized processing chain—integrating Persistent Scatterer and Small Baseline approaches with optimized phase unwrapping and thermal dilation correction—was applied to extract time-series deformation along Suzhou's metro network. The results show overall stability in central zones, with negligible subsidence within the historic moat area, yet reveal several localized subsidence bowls exceeding 15 mm/year in the suburbs. Time-series analysis correlates settlement of high-rise buildings (> 14 mm/year) with surface loading and soil consolidation. By integrating InSAR-derived displacements with building safety standards and metro engineering thresholds, a risk evaluation framework was developed. Its application to 49,279 structures identified 4 severely at-risk buildings (0.008%), 101 moderately at-risk buildings (0.205%), and 172 mildly at-risk buildings (0.349%). This work establishes a practical risk-assessment protocol and provides the first large-scale visualization of subsidence hazards along Suzhou's metro lines, offering valuable guidance for metro planning, operational safety, and infrastructure preservation.