Search

Revealing the land subsidence in Beijing, China, induced by the massive groundwater extraction in the past three decades, is important to mitigate the hazards and protect the residences and infrastructure. Many SAR (Synthetic Aperture Radar) datasets have been successfully applied to reveal the land subsidence over Beijing in previous research, while few works were achieved on land subsidence revealed by time-series InSAR (Interferometric Synthetic Aperture Radar) with Gaofen-3 SAR images. In this study, we successfully perform the time-series InSAR analysis with Gaofen-3 SAR images to extract the land subsidence in Beijing from 2020 to 2021. The Sentinel-1 SAR images were used to assess the accuracy of Gaofen-3 images. The subsidence scale and extent are consistent in detected major subsidence bowls between the two datasets. The spatial–temporal evolution and the deceleration of Beijing land subsidence were revealed by comparing with the Sentinel-1 results from 2017 to 2020. Moreover, we evaluated the interferometric performance of Gaofen-3 satellite SAR imagery and analyzed the main factors that mostly influence the coherence and quality of interferograms. Our results proved that the long perpendicular baselines decrease the coherence seriously over the study area, and the artifacts induced by inaccurate orbit information reduce the quality of the Gaofen-3 interferograms. Refining and removing the two main artifacts could improve the quality of interferograms formed by Gaofen-3 SAR images. [ABSTRACT FROM AUTHOR]

Surface subsidence is a serious threat to human life, buildings and traffic in Beijing. Surface subsidence is closely related to human activities, and human activities in Beijing area showed a decreasing trend during the Corona Virus Disease 2019 (COVID-19). To study surface subsidence in Beijing before and after the COVID-19 outbreak and its causes, a total of 51 Sentinel-1A SAR images covering Beijing from January 2018 to April 2022 were selected to derive subsidence information by Time Series Interferometry Synthetic Aperture Radar (TS-InSAR). The results of surface subsidence in Beijing demonstrate that Changping, Chaoyang, Tongzhou and Daxing Districts exhibited the most serious subsidence phenomenon before the COVID-19 outbreak. The four main subsidence areas form an anti-Beijing Bay that surrounds other important urban areas. The maximum subsidence rate reached −57.0 mm/year. After the COVID-19 outbreak, the main subsidence area was separated into three giant subsidence funnels and several small subsidence funnels. During this period, the maximum subsidence rate was reduced to −43.0 mm/year. Human activity decrease with the COVID-19 outbreak. This study effectively analysed the influence of natural factors on surface subsidence after excluding most of the human factors. The following conclusions are obtained from the analysis: (1) Groundwater level changes, Beijing's geological structure and infrastructure construction are the main reasons for surface subsidence in Beijing. (2) Seasonal changes in rainfall and temperature indirectly affect groundwater level changes, thereby affecting surface subsidence in the area. (3) The COVID-19 outbreak in early 2020 reduced the payload of Beijing's transportation facilities. It also slowed down the progress of various infrastructure construction projects in Beijing. These scenarios affected the pressure on the soft land base in Beijing and reduced the surface subsidence trend to some extent. [ABSTRACT FROM AUTHOR]

The long-term over-exploitation of groundwater has not only caused the compaction of aquifer thickness and surface deformation but has also further aggravated the loss of groundwater storage (GWS) in Beijing plain. The South-to-North Water Diversion Project (SNWDP) furnishes a new source of water for Beijing. By reviewing related studies, it was found that there are few studies on the realization of GWS estimation based on InSAR technology considering the lag effect. Therefore, in this study, firstly, the long-time series deformation characteristics of Beijing plain were obtained from 46 RadarSat-2 images using small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology. Secondly, the seasonal components of surface deformation and hydraulic head change were extracted by means of multichannel singular spectrum analysis (MSSA), verifying the separation accuracy by means of Monto Carlo-SSA (MC-SSA). Finally, for the hydrodynamic delay (aquifer water supply/drainage) of the complex aquifer system, we introduced the time lag cross-correlation (TLCC) approach to correct the hysteresis response of seasonal deformation relative to the variation of the aquifer system head, so as to realize the estimation of aquifer storage properties and GWS loss, even unrecoverable GWS (UGWS). The results showed that the average annual variation of total GWS (TGWS) in Beijing plain was −6.702 × 107 m3, of which the depletion volume of UGWS was −6.168 × 107 m3, accounting for 92.03% of the TGWS. On a temporal scale, the depletion of UGWS lagged behind the total head change, with about one year of lag time. On a spatial scale, in contrast to the north of Beijing plain, the depletion of UGWS in the south only recovered briefly after 2015 and then continued to decline. This further indicated that the process of the decline of middle-deep confined head and long-term GWS loss caused by over-exploitation of groundwater was irreversible. These findings are of great significance to optimize the allocation of groundwater resources, reduce the harm of land subsidence and protect groundwater resources. [ABSTRACT FROM AUTHOR]

The coordinated development of the Beijing-Tianjin-Hebei has become a national strategy with Beijing and Tianjin as twin engines driving the regional development. However, the Beijing-Tianjin-Hebei region has suffered dramatic ground subsidence during last two to three decades, mainly due to long-term groundwater withdrawal. Although, annual spirit leveling has been conducted routinely in some parts of Beijing and Tianjin, and InSAR technique has also been used to monitor ground subsidence in some local areas of the region, there is a lack of a complete survey of ground subsidence over the whole region. In this paper, we report a research on mapping ground subsidence in the Beijing-Tianjin-Hebei region over a long time span from 1992 to 2014. Three SAR datasets from four satellites are used: ERS-1/2 SAR images from 1992 to 2000, ENVISAT ASAR images from 2003 to 2010, and RADARSAT-2 images from 2012 to 2014. An improved multi-temporal InSAR method, namely "Multiple-master Coherent Target Small-Baseline InSAR" (MCTSB-InSAR), has been developed to process the datasets. A unique feature of MCTSB-InSAR is the adjustment process useful for wide area monitoring which provides an integrated solution for both calibration of InSAR-derived deformation and the harmonization of the deformation estimates from overlapping SAR frames. Three maps of the subsidence rate corresponding to the three periods over the wide Beijing-Tianjin-Hebei region are generated, with respective accuracy of 8.7 mm/year (1992-2000), 4.7 mm/year (2003-2010), and 5.4 mm/year (2012-2014) validated by more than 120 leveling measurements. The spatial-temporal characteristics of the development of ground subsidence in Beijing and Tianjin are analyzed. This research represents a first-ever effort on mapping ground subsidence over very large area and over long time span in China. The result is of significance to serve the decision-making on ground subsidence mitigation in the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Beijing-Tianjin-Hebei (BTH) has been suffering from severe groundwater storage (GWS) consumption and land subsidence (LS) for a long period. The overexploitation of groundwater brings about severe land subsidence, which affects the safety and development of BTH. In this paper, we utilized multi-frame synthetic aperture radar datasets obtained by the Rardarsat-2 satellite to monitor land subsidence's temporal and spatial distribution in the BTH from 2012 to 2016 based on multi-temporal interferometric synthetic aperture radar (MT-InSAR). In addition, we also employed the Gravity Recovery and Climate Experiment (GRACE) mascon datasets acquired by the Center for Space Research (CSR) and Jet Propulsion Laboratory (JPL) to obtain the GWS anomalies (GWSA) of BTH from 2003 to 2016. Then we evaluate the accuracy of the results obtained. Furthermore, we explored the relationship between the regional GWSA and the average cumulative subsidence in the BTH. The total volume change of subsidence is 59.46% of the total volume change of groundwater storage. Moreover, the long-term decreasing trend of the GWSA (14.221 mm/year) and average cumulative subsidence (17.382 mm/year) show a relatively high consistency. Finally, we analyze the heterogeneity of GWS change (GWSC) and LS change (LSC) in the four typical areas by the Lorenz curve model. The implementation of the South-to-North Water Diversion Project (MSWDP) affects the heterogeneity of GWSC and LSC. It can be seen that the largest heterogeneity of LSC lags behind the GWSC in the Tianjin-Langfang-Hengshui-Baoding area. The largest uneven subsidence in Beijing and Tianjin occurred in 2015, and the largest uneven subsidence in Hengshui-Baoding occurred in 2014. After that, the heterogeneity of subsidence gradually tends to stable. [ABSTRACT FROM AUTHOR]

In urban areas, deformation of transportation infrastructures may lead to serious safety accidents. Timely and accurate monitoring of the structural deformation is critical for prevention of transportation accidents and assurance of construction quality, particularly in areas with regional land subsidence, such as the city of Beijing. In this study, we proposed a method for the detection of seasonal deformation of highway overpasses using the integration of persistent scatterers Interferometric Synthetic Aperture Radar (PS-InSAR) techniques and seasonal indices, i.e., deformation concentration degree (DCD) and deformation concentration period (DCP) indices. Taking eastern Beijing urban area as a case study area, we first used the PS-InSAR technique to derive time series surface deformation based on 55 TerraSAR-X images during 2010–2016. Then, we proposed DCD and DCP indices to characterize seasonal deformation of 25 highway overpasses in the study area, with DCD representing to what degree the annual deformation is distributed in a year, and DCP representing the period on which deformation concentrates in the year. Our results showed that the maximum annual deformation rate reached −141.3 mm/year in Beijing urban area, and the PS-InSAR measurements agreed well with levelling measurements (R2 > 0.97). For PS pixels with DCD ≥ 0.3, the monthly deformation showed obvious seasonal patterns with deformation values during some months greater than those during the other months. DCP revealed that the settlement during autumn and winter was more serious than that in spring and summer. The seasonal patterns seemed to be related to the location, structure, and construction age of the overpasses. The upper-level overpasses, the newly constructed overpasses, and those located in the subsidence area (rate < −40 mm/year) tended to show a greater seasonal pattern. The seasonal deformation variations were also affected by groundwater-level fluctuation, temperature, and compressible layer. [ABSTRACT FROM AUTHOR]

Beijing is a major city suffering from land subsidence due to long-term over-exploitation of groundwater. The South-to-North Water Diversion Project (SNWDP), however, has had a significant impact on the structure of water consumption since the end of 2014, and it is changing the status of land subsidence in Beijing. In this study, we employed Persistent Scatterers Synthetic Aperture Radar Interferometric (PS-InSAR) to investigate the decadal evolution of land subsidence in Beijing with 100 TerraSAR-X stripmap images collected from April 2010 to December 2019. The water resources, historic climate and urban construction data were compiled for the years of 2010 to 2019 to analyze changes in groundwater level, human activity, surface geology, active faults and land subsidence patterns. The results show that the changes in the water supply structure are correlated to a rise in groundwater level after 2015. These changes include an increase in the water supply from the SNWDP, a reduction in groundwater exploitation, the optimization of water consumption, replacing recycled water for environmental water and a reduction in the use of water for agriculture. Land subsidence in the study area was concentrated in the eastern regions, trending towards a decreasing velocity starting about two years after the commencement of SNWDP in 2015. Uneven subsidence in the land subsidence area was related to excavations of underground soil, and the construction of Line 6 and Line 7 led to rapid nonlinear subsidence. Our results have scientific significance for reducing subsidence hazards in the context of SNWDP and urban expansion. [ABSTRACT FROM AUTHOR]

Since the 1930s, due to the rapid development of the city and the increase of population, the demand from Beijing residents for water resources has gradually increased. Land deformation in the Beijing Plain is a serious issue. In order to warn of, and mitigate, disasters, it is urgently necessary to obtain the latest rate, extent, and temporal evolution of land subsidence in Beijing. Firstly, the temporal and spatial distribution characteristics of land deformation in Beijing during 2003–2020 were unveiled using the time-series interferometric synthetic aperture radar (InSAR) technique and two different satellite datasets, sentinel-1a/1b and ENVISAT ASAR. By means of combining calibration of InSAR results with the global positioning system (GPS), we studied the evolutionary process of long-term land subsidence in Beijing. The precision of our InSAR annual subsidence results is less than 10 mm. Land subsidence in Beijing is unevenly distributed, and so five main land subsidence zones were monitored. The time-series results showed that the rate of land subsidence rate continued to increase from 2003 to 2015, but has gradually shown a slowing trend from 2015 to 2020. Further, we used the quadratic polynomial fitting method to interpolate the time-series deformation results from 2010 to 2015, and compared these with GPS. The results demonstrated that although the InSAR observation method is not strictly registered with GPS in time, its deformation trend is consistent. In addition, the calibrated long time-series was consistent with the three deformation stages of land subsidence evolution in Beijing. Finally, we analyzed the deformation information obtained by InSAR technology in combination with land use type data, precipitation and groundwater data. The results demonstrated that the central area is mostly stable, and land deformation in the northeast is obvious and uneven. In addition, land use type and precipitation have little influence on land subsidence. Changes in land subsidence were closely related to changes in groundwater level, and seasonal variations in deformation correlated with precipitation. [ABSTRACT FROM AUTHOR]

Rapid simulation of land subsidence can provide an effective means of facilitating its management and control. This paper innovatively introduced a back-propagation (BP) neural network subsidence simulation model which was optimized by the sparrow search algorithm (SSA), hereinafter referred to as the SSA-BP model, to simulate land subsidence in Tongzhou District, Beijing. First, based on the time series interferometric synthetic aperture radar (InSAR) monitoring, different technologies such as spatial analysis, Google Earth Engine (GEE), and machine learning were utilized together with a variety of multi-source spatial data, including groundwater level, compressible layer thickness, Visible Infrared Imager Radiometer Suite (VIIRS) nighttime light images, and the OpenStreetMap (OSM) road distribution. Furthermore, we determined the optimal grid scale for land subsidence research and worked out a multifactor-driven SSA-BP land subsidence simulation model for which sensitivity analysis was performed with great care. Main conclusions: (1) From November 2010 to January 2020, the average annual surface displacement rate in Beijing's subcentre, Tongzhou, ranged from −133.9 to +3.9 mm/year. (2) Our SSA-BP land subsidence simulation model allows for a relatively high overall accuracy. The average root mean square error (RMSE) is 5.00 mm/year, the average mean absolute error (MAE) is 3.80 mm/year, and the average coefficient of determination (R2) is 0.83. (3) Sensitivity analysis shows that the SSA-BP model driven by multiple factors has a far better simulation performance than the model driven by any single weighting factor, and displays the highest sensitivity to the groundwater level factor among all the weighting factors. In terms of subdividing the study area, our SSA-BP land subsidence model runs with multifunctional zones displayed a higher accuracy than that without. This paper made use of a machine learning model to simulate land subsidence in Beijing's Tongzhou District and explored the sensitivity of different factors to land subsidence, which is helpful for its scientific prevention. [ABSTRACT FROM AUTHOR]

Excessive exploitation of the groundwater has resulted in obvious three-dimensional (3D) deformation features on the surface of the Beijing Plain. This paper, by combining Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) technologies, has obtained time-series information of the 3D surface deformation in the Beijing Plain, analyzing its spatial distribution characteristics. On this basis, the relationship between different controlling factors with the 3D deformation of the surface has been analyzed as well. The following results are obtained: (1) From 2013 to 2018, the land subsidence, which generally showed the trend of slowing down, was mainly concentrated in the eastern, northern, and southern regions of Beijing Plain, with multiple subsidence centers. (2) Under the International Terrestrial Reference Frame 2005 (ITRF2005), the horizontal direction of all GPS points in the plain is basically the same, with the dominant movement direction being NE112.5°~NE113.8°. Under the Eurasian reference frame, the horizontal movement rate of GPS points significantly decreases. The movement rate and direction of each point are not characteristic of overall trend activity. (3) The distribution and extent of the 3D surface deformation in the Beijing Plain are controlled by the basement structure. Part of the subsided area corresponds to a Quaternary depression formed at the junction of active faults disrupting the area. Similarly, the distribution of horizontal deformation in the E-W and N-S directions of the plain is controlled by the regional basement structure comprising major faults bounding horizontal deformation. (4) Groundwater exploitation is the main cause of the 3D surface deformation in the Beijing Plain. The groundwater funnels of the second and third confined aquifer are in suitable agreement with the land subsidence. The horizontal movement in the Beijing Plain is either directed toward the center of the groundwater or the land subsidence funnel, and the deformation is directed from areas with higher to areas with lower groundwater levels. [ABSTRACT FROM AUTHOR]

Land subsidence is one of the most important geological hazards in Beijing, China, and its scope and magnitude have been growing rapidly over the past few decades, mainly due to long-term groundwater withdrawal. Interferometric Synthetic Aperture Radar (InSAR) has been used to monitor the deformation in Beijing, but there is a lack of analysis of the long-term spatiotemporal evolution of land subsidence. This study focused on detecting and characterizing spatiotemporal changes in subsidence in the Beijing Plain by using Persistent Scatterer Interferometry (PSI) and geographic spatial analysis. Land subsidence during 2003–2015 was monitored by using ENVISAT ASAR (2003–2010), RADARSAT-2 (2011–2015) and TerraSAR-X (2010–2015) images, with results that are consistent with independent leveling measurements. The radar-based deformation velocity ranged from −136.9 to +15.2 mm/year during 2003–2010, and −149.4 to +8.9 mm/year during 2011–2015 relative to the reference point. The main subsidence areas include Chaoyang, Tongzhou, Shunyi and Changping districts, where seven subsidence bowls were observed between 2003 and 2015. Equal Fan Analysis Method (EFAM) shows that the maximum extensive direction was eastward, with a growing speed of 11.30 km2/year. Areas of differential subsidence were mostly located at the boundaries of the seven subsidence bowls, as indicated by the subsidence rate slope. Notably, the area of greatest subsidence was generally consistent with the patterns of groundwater decline in the Beijing Plain. [ABSTRACT FROM AUTHOR]

Beijing is severely affected by land subsidence, and rapid urbanisation and building construction might accelerate the land subsidence process. Based on 39 Envisat Advanced Synthetic Aperture Radar (ASAR) images acquired between 2003–2010, 55 TerraSAR-X images acquired between 2010–2016, and urban building information, we analysed the relationship between land subsidence and buildings at the regional, block, and building scales. The results show that the surface displacement rate in the Beijing urban area ranged from −109 mm/year to +13 mm/year between 2003–2010, and from −151 mm/year to +19 mm/year between 2010–2016; two subsidence bowls were mainly distributed in the eastern part of the Chaoyang District. The displacement rate agreed well with the levelling measurements, with an average bias of less than six mm/year. At the regional scale, the spatial pattern of land subsidence was mainly controlled by groundwater extraction, compressible layer thickness, and geological faults. Subsidence centres were located in the area around ground water funnels with a compressible layer depth of 50–70 m. The block-scale analysis demonstrated a clear correlation between the block construction age and the spatial unevenness of subsidence. The blocks constructed between 1998–2005 and after 2005 showed considerably more subsidence unevenness and temporal instability than the blocks constructed before 1998 during both time periods. The examination of the new blocks showed that the spatial unevenness increased with building volume variability. For the 16 blocks with a high building volume, variability, and subsidence unevenness, the building-scale analysis showed a positive relationship between building volume and settlement in most blocks, although the R2 was lower than 0.5. The results indicate that intense building construction in urban areas could cause differential settlement at the block scale in Beijing, while the settlement of single buildings could be influenced by the integrated effects of building volume, foundation structures, and the hydrogeological background. [ABSTRACT FROM AUTHOR]

Identifying Persistent Scatterers (PSs) is one of the key processing steps of the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique. The number, density, and reliability of identified PSs directly affect the monitoring accuracy of land subsidence, especially in higher density urban environments. As a result of the side-looking viewing geometry of SAR, the layover effect poses a major challenge to the PS identification. This research proposes joint modeling of the PS-InSAR technique and RELAX algorithm for SAR tomography (PS-InSAR+RELAX) to detect single and double scatterers and to improve the identification and reliability of PSs. It has been demonstrated that RELAX improves separation of the scatterers when compared to two other spectral analysis methods for SAR tomography, Beam-Forming (BF) and Singular Value Decomposition (SVD). RELAX exhibits the least noise when the number of baseline changes from 15 to 30, and it can separate the scatterers at a lower Normal-Slant-Range (NSR) height than the two other methods. As RELAX can better identify, separate, and then filter out layover scatterers, the number and density of PSs identified by PS-InSAR+RELAX is reduced and visually simplified, suggesting that the method can effectively reduce the influence of the layover effect on the PS identification. Also, the PSs identified by PS-InSAR+RELAX are more coherent than those identified by the traditional PS-InSAR technique. The proposed technique has been applied to Sentinel-1A data acquired from 2014 to 2016, to monitor land subsidence in the city of Beijing, China. When evaluated against the leveling measurements, PS-InSAR+RELAX performs better than the traditional PS-InSAR technique, with the correlation coefficients (r) of r = 0.98 and r = 0.95, respectively. [ABSTRACT FROM AUTHOR]

Land subsidence threatens the stable operation of urban rail transit, including subways. Obtaining deformation information during the entire life-cycle of a subway becomes a necessary means to guarantee urban safety. Restricted by sensor life and cost, the single-sensor Multi-temporal Interferometric Synthetic Aperture Radar (MTI) technology has been unable to meet the needs of long-term sequence, high-resolution deformation monitoring, especially of linear objects. The multi-sensor MTI time-series fusion (MMTI-TSF) techniques has been proposed to solve this problem, but rarely mentioned. In this paper, an improved MMTI-TSF is systematically explained and its limitations are discussed. Taking the Beijing Subway Network (BSN) as a case study, through cross-validation and timing verification, we find that the improved MMTI-TSF results have higher accuracy (R2 of 98% and, Root Mean Squared Error (RMSE) of 4mm), and compared with 38 leveling points, the fitting effect of the time series is good. We analyzed the characteristics of deformation along the BSN over a 15-year periods. The results suggest that there is a higher risk of instability in the eastern section of Beijing Subway Line 6 (L6). The land subsidence characteristics along the subway lines are related to its position from the subsidence center, and the edge of the subsidence center presents a segmented feature. [ABSTRACT FROM AUTHOR]