Owing to accelerated urbanization, land subsidence has damaged urban infrastructure and impeded sustainable economic and social development in Qingdao City, China. Combining interferometric synthetic aperture radar (InSAR) and generic atmospheric correction online service (GACOS), atmospheric correction has not yet been investigated for land subsidence in Qingdao. A small baseline subset of InSAR (SBAS InSAR), GACOS, and 28 Sentinel-1A images were combined to produce a land subsidence time series from January 2019 to December 2020 for the urban areas of Qingdao, and the spatiotemporal evolution of land subsidence before and after GACOS atmospheric correction was compared, analyzed, and verified using leveling data. Our work demonstrates that the overall surface condition of the Qingdao urban area is stable, and subsidence areas are mainly concentrated in the coastal area of Jiaozhou Bay, northwestern Jimo District, and northern Chengyang District. The GACOS atmospheric correction could reduce the root-mean-square error of the differential interferometric phase. The land subsidence time series after correction was in better agreement with the leveling-monitored results. It is effective to perform GACOS atmospheric correction to improve the accuracy of SBAS InSAR-monitored land subsidence over a large scale and long time series in coastal cities.
Oil and gas extraction can cause ground subsidence, posing a threat to human safety. Therefore, timely identification of subsidence areas and implementation of mitigation measures are of significant importance. This study employed SBAS-InSAR technology to process 29 scenes of Sentinel-1A images covering the Thamama C area of the Bab oilfield. It thoroughly analyzed the spatio-temporal distribution characteristics of surface subsidence in the research area from March 2022 to March 2023. Three distinct areas with prominent subsidence were selected as feature areas, and their stability was analyzed using the entropy method. The results indicate that: (1) As of March 6, 2023, the overall research area exhibited a subsidence trend, with the extent and magnitude of subsidence continuously expanding over time. (2) By calculating the entropy values of the three selected feature areas using the entropy method, it was observed that all three areas experienced a certain degree of deformation fluctuation. This highlights the need for attention in subsequent production and construction activities. The study demonstrates that combining the entropy method with SBAS-InSAR technology enables effective monitoring and analysis of large-scale and long-term deformation in mining areas, providing assurance for the construction and operation of relevant engineering projects.
The accuracy of differential interferometric synthetic aperture radar (DInSAR) in monitoring the ground subsidence is a major challenge to be addressed urgently. Using the repeat track DInSAR and GIS spatial analysis tools, eight C-band Sentinel-1A SAR images of the Guotun coal mine (China) were processed to determine the mining subsidence from November 27, 2015 to July 24, 2016. The mining data of 13 working faces and the DInSAR- and leveling-monitored results were compared. A method was proposed to solve the problem of time inconsistency between DInSAR- and leveling-monitored results. The location, spatial distribution, scope, and variations of mining subsidence monitored by Sentinel-1A repeat track DInSAR were consistent with the mining progress of the working faces. The accuracy of the DInSAR-monitored subsidence values was directly related to the coherence of the subsidence zones, and the absolute difference from the leveling-monitored values was small at the subsidence edge but large at the subsidence center.
To overcome the illposed problems existing in small baseline subsets deformation, the Liu-type estimator is used to improve the accuracy of calculation. The Liu-type estimator introduces parameter d to improve the fitting and statistical properties after the condition number of the design matrix is reduced to the desired level, which makes the solution of illposed problems robust. In the experiment, subsidence rates relevant to the Beijing area are computed from the ENVISAT satellite radar data from the European Space Agency from 2007 to 2010. The experimental results show that the accuracy of the deformation rates computed with the Liu-type estimator is clearly improved.
The external digital elevation model (DEM) error is one of the main factors that affect the accuracy of mine subsidence monitored by two-pass differential interferometric synthetic aperture radar (DInSAR), which has been widely used in monitoring mining-induced subsidence. The theoretical relationship between external DEM error and monitored deformation error is derived based on the principles of interferometric synthetic aperture radar (DInSAR) and two-pass DInSAR. Taking the Dongtan and Yangcun mine areas of Jining as test areas, the difference and accuracy of 1:50000, ASTER GDEM V2, and SRTM DEMs are compared and analyzed. Two interferometric pairs of Advanced Land Observing Satellite Phased Array L-band SAR covering the test areas are processed using two-pass DInSAR with three external DEMs to compare and analyze the effect of three external DEMs on monitored mine subsidence in high- and low-coherence subsidence regions. Moreover, the reliability and accuracy of the three DInSAR-monitored results are compared and verified with leveling-measured subsidence values. Results show that the effect of external DEM on mine subsidence monitored by two-pass DInSAR is not only related to radar look angle, perpendicular baseline, slant range, and external DEM error, but also to the ground resolution of DEM, the magnitude of subsidence, and the coherence of test areas.
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