Coal-mining subsidence causes ground fissures and destroys surface structures, which may lead to severe casualties and economic losses. Time series interferometric synthetic aperture radar (TS-InSAR) plays an important role in surface deformation detection and monitoring without the restriction of weather and sunlight conditions. In addition, the probability integral method (PIM) is a surface movement model that is widely used in the field of mining subsidence. In recent years, the integration of TS-InSAR and the PIM has been extensively studied. In this paper, we propose a new method to estimate mining subsidence with the PIM based on TS-InSAR results. This study focuses on the improvement of a boundary constraint and dynamic parameter estimation in the PIM through the inversion of the line-of-sight (LOS) time series deformation derived by TS-InSAR. In addition, 45 Sentinel-1A images from 17 June 2015 to 27 December 2017 of a coal mine in Jiaozuo are utilized to acquire the surface displacement. We apply a time series deformation analysis using small baseline subsets (SBAS) and place the results into an improved PIM to estimate the mining parameters. The simulated mining subsidence is highly consistent with the leveling data, exhibiting an RMSE of 0.0025 m. Compared with the conventional method, the proposed method is more accurate in discovering displacement in mining areas. In the final section of this paper, some sources of error that affect the experiment are discussed.
In the past two decades, ground-based synthetic aperture radars (GB-SARs) have developed rapidly, providing a large amount of SAR data in minutes or even seconds. However, the real-time processing of big data is a challenge for the existing GB-SAR interferometry (GB-InSAR) technology. In this paper, we propose a near-real-time GB-InSAR method for monitoring slope surface deformation. The proposed method uses short baseline SAR data to generate interferograms to improve temporal coherence and reduce atmospheric interference. Then, based on the wrapped phase of each interferogram, a network method is used to estimate and remove systematic errors (such as atmospheric delay, radar center shift error, etc.). After the phase unwrapping, a least squares estimator is used for the overall solution to obtain the initial deformation parameters. When new data are added, a sequential estimator is used to combine the previous processing results and dynamically update the deformation parameters. Sequential estimators could avoid repeated calculations and improve data processing efficiency. Finally, the method is validated with the measured data. The results show that the average deviation between the proposed method and the overall estimation was less than 0.01 mm, which could be considered a consistent estimation accuracy. In addition, the calculation time of the sequential estimator was less sensitive than the total amount of data, and the time-consuming growth rate of each additional period of data was about 1/10 of the overall calculation. In summary, the new method could quickly and effectively obtain high-precision surface deformation information and meet the needs of near-real-time slope deformation monitoring.
Time series interferometric synthetic aperture radar (TS-InSAR) has been a powerful tool for monitoring land surface deformation in the last two decades. Atmospheric effects cause large-scale delays in InSAR observations, which is one of the difficulties facing deformation calculations from differential InSAR (D-InSAR) and time-series InSAR. Currently, atmospheric delay is derived mainly from auxiliary data from sources such as the global navigation satellite system (GNSS) and moderateresolution imaging spectroradiometry (MODIS), but GNSS data are limited by the sparse distribution of observation stations. MODIS data also may not temporally match SAR image acquisition, which leads to low accuracy in atmospheric phase correction. This paper presents a decomposition method to remove atmospheric delay. We consider the atmospheric phase to be caused by the combined changes in spatial position and elevation. Therefore, quadtree segmentation is applied to divide the topographic units, and we improve the drift function of universal kriging by adding an elevation component. We then interpolate the whole atmospheric phase space from reliable sampling points estimated by the coherence coefficient. Using Sentinel-1 data, we test the proposed method in discriminating and monitoring a mining subsidence area in Shanxi Province and compare the results with the results from interferometric point target analysis (IPTA) and the network-based variance-covariance estimation (NVCE) method. The results demonstrate that the proposed method is superior to existing methods for the detection of deformation inverted from time-series InSAR.
Earthquake disasters are frequent, and the seismic intensity is large in Northeast China. Earthquake activity research is an important aspect of earthquake disaster management. We chose some unconventional means to study fault activity, to find updated activity evidence. The Ms 5.3 earthquake occurred near the Fuyu North Fault (FNF) of China on May 27, 2018. Using the Sentinel-1B descending orbit data from 2016 to 2019, the line-of-sight (LOS) surface deformation in the study area was calculated by using the small baseline subset (SBAS) method. After transforming to the horizontal EW deformation, the variance component estimation method was used for fusion reconstruction with the EW data of the surrounding GNSS stations. The polynomial least square method is used to fit the fault slip rate of three EW data on the surface trace of the FNF. The fitting results of the three regions show that the horizontal eastward distribution rate of the upper plate is significantly greater than that of the lower plate, which is left-lateral clockwise torsion. The vertical structural deformation caused by the growth strata of the upper and lower plates of the upper SYT2 seismic profile of the FNF is quantitatively calculated, and the thrust rate of the upper plate is 0.2 mm/y relative to that of the lower plate. Based on the Li Siguang chessboard structure model, we found that the compression stress in the north-south direction is gradually weakened, and the compression stress in the east-west direction is gradually enhanced. Through the Coulomb stress analysis, the three events of CMT only induced the historical focal location of the surrounding part. The events of 2017 did not induce the events of 2018, but the events of 2019 were related to the induced effects of 2017 and 2018.
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