Based on an actual excavation of a metro station in Tianjin, China, a fluid–solid coupling numerical model was developed to study the characteristics of groundwater flow and strata movement induced by dewatering and excavation considering the barrier effect of pre-existing adjacent underground structures. Two parameters were selected for the model: the distance between the excavation and the existing underground structure (D), and the buried depth of the adjacent structure (H). By comparing the distribution of groundwater drawdown and deformation modes of the retaining structure and the strata under different working conditions, the influence mechanism of adjacent structures on the movement of groundwater and strata was revealed. The results show that the pile foundations have different effects on the groundwater flow and excavation deformation. Generally, the maximum groundwater drawdown could be enlarged by considering the adjacent underground structure, while the retaining structure deflection would be reduced and the ground settlement could be either enlarged or reduced. Additionally, as D decreases and H increases, a much greater groundwater drawdown and a much smaller retaining structure deflection would appear, which together affect the ground behavior. On the one hand, greater groundwater drawdown would lead to greater ground settlement by soil consolidation, while on the other hand, a smaller retaining structure deflection would lead to smaller ground settlement. Thus, a complex development of ground settlement would appear, and a specific analysis should be performed to assess this in practice, based on a specific H and D.

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.

Due to the high temporal resolution (e.g., 10 s) required, and large data volumes (e.g., 360 images per hour) that result, there remain significant issues in processing continuous ground-based synthetic aperture radar (GBSAR) data. This includes the delay in creating displacement maps, the cost of computational memory, and the loss of temporal evolution in the simultaneous processing of all data together. In this paper, a new processing chain for real-time GBSAR (RT-GBSAR) is proposed on the basis of the interferometric SAR small baseline subset concept, whereby GBSAR images are processed unit by unit. The outstanding issues have been resolved by the proposed RT-GBSAR chain with three notable features: (i) low requirement of computational memory; (ii) insights into the temporal evolution of surface movements through temporarily-coherent pixels; and (iii) real-time capability of processing a theoretically infinite number of images. The feasibility of the proposed RT-GBSAR chain is demonstrated through its application to both a fast-changing sand dune and a coastal cliff with submillimeter precision.

Monitoring the surface subsidence in mining areas is conducive to the prevention and control of geological disasters, and the prediction and early warning of accidents. Hunan Province is located in South China. The mineral resource reserves are abundant; however, large and medium-sized mines account for a low proportion of the total, and the concentration of mineral resource distribution is low, meaning that traditional mining monitoring struggles to meet the needs of large-scale monitoring of mining areas in the province. The advantages of Interferometric Synthetic Aperture Radar (InSAR) technology in large-scale deformation monitoring were applied to identify and monitor the surface subsidence of coal mining fields in Hunan Province based on a Sentinel-1A dataset of 86 images taken from 2018 to 2020, and the process of developing surface subsidence was inverted by selecting typical mining areas. The results show that there are 14 places of surface subsidence in the study area, and accidents have occurred in 2 mining areas. In addition, the railway passing through the mining area of Zhouyuan Mountain is affected by the surface subsidence, presenting a potential safety hazard.

In this paper, aiming at the limitation of persistence scatterers (PS) points selection, a new method for selecting PS points has been introduced based on the average coherence coefficient, amplitude dispersion index, estimated signal-to-noise ratio and displacement standard deviation of multiple threshold optimization. The stability and quality of this method are better than that of a single model. In addition, an atmospheric correction model has also been proposed to estimate the atmospheric effects on Ground-based synthetic aperture radar (GBSAR) observations. After comparing the monitoring results before and after correction, we clearly found that the results are in good agreement with the actual observations after applying the proposed atmospheric correction approach.

Through a series of experiments of dynamic deformation and destruction under time series loading on an indoor real model bridge, Ground-based real-aperture radar interferometry (GB-InRAR) discovered that before the structure of the bridge was damaged, its amplitude and acceleration increased with the increase of load; After its structure was damaged or cracked, such dynamic characteristics as natural frequency, damping ratio, stiffness and bearing capacity decreased obviously. Moreover, GB-InRAR dynamic load monitoring of Xiangtan Railway Bridge and Inter-city Railway Bridge. In the process of vehicle dynamic load, such important parameters as bridge deflection, natural frequency and damping ratio conform to the bridge loading procedures and dynamic characteristics. The results show that the GB-InRAR can accurately measure the deflection changes, natural vibration frequency and spectrum characteristics of bridges, and it can be used as effective means of the dynamic characteristics analysis in the safety detection and health evaluation of bridges.