Development Of Land Subsidence Research Articles

Multisource remote sensing monitoring and analyzing for land subsidence and crop growth in a coal mining area under different rainfall conditions

Coal has been crucial in driving economic development and production construction. However, the mining-induced subsidence may cause irreversible damage to the surrounding environment of vegetation growth. Meanwhile, with the worsening of global warming, the frequency and intensity of extreme water-related weather events, such as droughts and excessive rainfall, are on the rise, which leads to heightened impacts on ecosystems and agricultural production. Consequently, extreme water-related weather, the distribution of land subsidence, and its effect on vegetation have attracted significant attention. Based on the Sentinel-1 radar data and Sentinel-2 multispectral data from 2017 to 2022, the SBAS-InSAR technology, the object-oriented classification, and the Normalized Difference Vegetation Index (NDVI) were employed respectively in the study to obtain the spatial-temporal evolution of land subsidence, subsidence-induced water, and crop growth in Tiefa mining area, a representative coal mining area in Northeast China. Moreover, the relationship between land subsidence, subsidence-induced water, and vegetation change was analyzed combined with summer precipitation data. The results showed that: (1) The average cumulative subsidence of the mining area was 256.8 mm, and the subsidence area was 42.525 km2 for the six years. Among them, the heaviest subsidence reached a maximum of 380.5 mm in 2022, and the largest subsidence area was 20.109 km2 in 2017. (2) When the rainfall was excessive, the area of subsidence-induced water would increase sharply, with a proportion jumping to 9.71% from 5.37%, which indicated the subsidence would further amplify the destructive effect of excessive rainfall and waterlogging on land resources. (3) In addition to the existing water pits, ground cracks and shallow subsidence pits appeared under the influence of underground coal mining. The direct impact of ground cracks on crops was not apparent, while the effect of subsidence pits on crops under different rainfall conditions was dual character. In dry years, crops in the subsidence pits could grow better due to higher soil moisture. In wet years, crops in the subsidence pits would suffer the more severe waterlogging. The research results are of great significance for further understanding the influence of coal mining on surface vegetation in mining areas in Northeast China.

Development and Comparison of InSAR-Based Land Subsidence Prediction Models

Land subsidence caused by human engineering activities is a serious problem worldwide. We selected Qian’an County as the study area to explore the evolution of land subsidence and predict its deformation trend. This study utilized synthetic aperture radar interferometry (InSAR) technology to process 64 Sentinel-1 data covering the area, and high-precision and high-resolution surface deformation data from January 2017 to December 2021 were obtained to analyze the deformation characteristics and evolution of land subsidence. Then, land subsidence was predicted using the intelligence neural network theory, machine learning methods, time-series prediction models, dynamic data processing techniques, and engineering geology of ground subsidence. This study developed three time-series prediction models: a support vector regression (SVR), a Holt Exponential Smoothing (Holt) model, and multi-layer perceptron (MLP) models. A time-series prediction analysis was conducted using the surface deformation data of the subsidence funnel area of Zhouzi Village, Qian’an County. In addition, the advantages and disadvantages of the three models were compared and analyzed. The results show that the three developed time-series data prediction models can effectively capture the time-series-related characteristics of surface deformation in the study area. The SVR and Holt models are suitable for analyzing fewer external interference factors and shorter periods, while the MLP model has high accuracy and universality, making it suitable for predicting both short-term and long-term surface deformation. Ultimately, our results are valuable for further research on land subsidence prediction.

Spatio-temporal evolution of land subsidence and susceptibility zonation of associated ground fissures in the urban area of loess plateau: a case in Xianyang city, China

For over 50 years, the Xianyang city on the Chinese loess plateau, has been deeply affected by land subsidence and its associated ground fissures. In this study, 67 Sentinel-1A images from 2015 to 2022 were analysed to obtain the spatio-temporal evolution of land subsidence. Subsidence centers identified in Yunyang town and Luqiao town exhibit annual subsidence rates of −31 mm/a and −26.7 mm/a, respectively, culminating in total subsidence of −258 mm in Yunyang town and −139 mm in Luqiao town. Moreover, time series analysis revealed that both towns exhibit pronounced seasonal subsidence patterns. It is believed that human cultivation and groundwater overuse, combined with the effects of active faults, have led to uneven land subsidence. Then, the gradient of land subsidence and its potential relation to ground fissure hazards were evaluated. The results highlight a strong spatial correlation between high subsidence gradient areas and dense ground fissure distribution. Therefore, we proposed for the first time to introduce the land subsidence gradient factors for the susceptibility mapping of ground fissures using the artificial neural network algorithm. The susceptibility zonation results show that integrating the gradient factor can improve the rationality of the susceptibility evaluation. The above understanding provides valuable support for disaster prevention and mitigation in urban areas affected by land subsidence and ground fissures in loess regions.

Simulating earth deformation evolution caused by groundwater pumping through ordinary state-based Peridynamics method

Earth deformation including land subsidence and the related earth fissures caused by the over-exploitation of groundwater resources is threatening countries all over the World. At present, the simulation of earth deformation of aquifer system is mainly based on continuum and contact mechanics. These approaches lead to two main challenges, i.e. the need of knowing the location of possible earth fissures in advance and using meshes that must be adjusted during the rupture propagation. Here, ordinary state-based Peridynamics method is firstly introduced to simulate the evolution of continuous and discontinuous earth deformation due to groundwater withdrawal. A failure criteria accounting for shear and tensile strain simultaneously is proposed. The approach is used to simulate the evolution of land subsidence and earth fissures in compressible sedimentary soils with buried rigid ridges. Two case studies are reproduced: one is a test carried out in laboratory and the other one concerns Guangming village, Yangtze River delta. In both cases, the presence of a shallow buried bedrock crossing the alluvial deposits is responsible for the initiation and growth of earth fissure that a satisfactory captured by the model. For the lab experiment, a 0.1 m deep fissure appearing above the rocky tip is computed. In Guangming village area, results show that some small fissure groups were initiated. Then, three main earth fissures developed rapidly with the maximum depth of 32.5 m. This study proposes a consistency modelling framework to simulate continuum earth deformation and discontinuous fissures due to groundwater withdrawal in specific geological settings, and supply a reliable scientific tool for early warning of this geo-hazard.

Land subsidence along the Beijing-Tianjin high-speed railway before and after the South-to-North water diversion project with multi-source monitoring datasets

The development of land subsidence has seriously affected the safe operation of Beijing-Tianjin high-speed railway. The South-to-North Water Diversion Project Central Route (SNWDP-CR) was officially put into operation in December 2014. It has changed the water supply pattern in Beijing and provided conditions for reducing groundwater exploitation and controlling land subsidence. In this paper, the time-series interferometric data, in situ monitoring data of recent 20 years and the basic geological datasets are combined to compare and analyze the changes of groundwater level, land subsidence and the main subsidence layers along the Beijing-Tianjin high-speed railway before and after the SNWDP-CR. The effects of the environment of Quaternary sedimentary, groundwater exploitation and soil deformation of different lithology on land subsidence along the high-speed railway under the background of new water conditions are revealed. The main conclusions are as follows: 1) The serious land subsidence area along the Beijing-Tianjin high-speed railway always concentrated in the section of DK11-DK23. After the operation of SNWDP-CR, the land subsidence along the railway generally showed a slowing trend. The maximum subsidence rate was reduced from 80 mm/yr to 49 mm/yr. The length of subsidence rate that more than 50 mm/yr of the section was reduced from 8.0 km to 0 km. 2) The groundwater level of different aquifer groups along the Beijing-Tianjin high-speed railway rose and declined before and after the SNWDP-CR. in eastern part of the plain, the groundwater level of each aquifer group has changed from a continuous decline (range 0.13–1.82 m) to a gradual rise (range 0.45–1.87 m) since 2017. However, in the southeast of the plain, the groundwater level still showed a continuous decline trend, with an average annual decline of 1.2–1.8 m. 3) From 2006 to 2019, the subsidence of the first, second and third compression layer group along the railway accounted for 2.71%, 28.29% and 69%, respectively. The third compression layer group (monitoring layer 94–182 m) had the largest subsidence proportion and was the main subsidence layer. 4) The land subsidence along the Beijing-Tianjin high-speed railway is controlled by the basement structure. The difference of groundwater exploitation intensity led to differences in the spatial distribution of land subsidence along the railway. The subsidence of the soil layer below the bearing layer (about 50 m) of the high-speed railway pile foundation exhibited the characteristics of viscoplastic or viscoelastic plasticity deformation. This section of strata is a key layer that needs to be considered for land subsidence control along the Beijing-Tianjin high-speed railway in the future.

Mechanism the land subsidence from multiple spatial scales and hydrogeological conditions – A case study in Beijing-Tianjin-Hebei, China.

Study regionBeijing-Tianjin-Hebei (BTH) region, China Study focusBTH has long been suffering from severe and uneven land subsidence. Finding out the spatial evolution of land subsidence is helpful to collaborative prevention and control. We innovatively revealed the spatial distribution of land subsidence from the mountains to the coastal area along four hydrogeological profiles, and inferred the land subsidence mechanism on the overall scale, local plain scale and typical regional scale. Small Baseline Subsets Interferometric Synthetic Aperture Radar was employed to collect displacement information in the BTH region from January 2012 to January 2020. We obtained groundwater storage data from the Gravity Recovery and Climate Experiment. New hydrological insights for the regionOn the overall scale, from 2012 to 2019, the Changping-TongZhou district of Beijing suffered the most serious land subsidence, with an annual subsidence rate of 159 mm and a cumulative subsidence as high as 928 mm. On the local plain scale, areas experiencing severe subsidence were generally located in the central plain. Fractures in the area obviously influenced the spatial distribution of subsidence. On the typical regional scale, a positive correlation was found between land subsidence and groundwater depletion. The relationship between precipitation and land subsidence in Hebei was the most convincing (R2 = 0.64). This study provides a scientific basis for regional coordination in land subsidence control. Data availabilityData can be provided by the corresponding authors upon request.

Land Subsidence Prediction and Analysis along Typical High-Speed Railways in the Beijing–Tianjin–Hebei Plain Area

High-speed railways in the Beijing–Tianjin–Hebei (BTH) Plain are gradually becoming more widespread, covering a greater area. The operational safety of high-speed railways is influenced by the continuous development of land subsidence. It is necessary to predict the subsidence along the high-speed railways; thus, this work is of critical importance to the safety of high-speed railway operation. In this study, we processed Sentinel-1A data using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire the land subsidence in the typical BTH area. Then, we combined the Empirical Mode Decomposition (EMD) and Gradient Boosting Decision Tree (GBDT) methods (EMD-GBDT) to forecast land subsidence along high-speed railways. The results revealed that some parts of the high-speed railways in the BTH plain had passed through or approached the land subsidence area; the maximum cumulative subsidence of the Beijing–Shanghai, Tianjin–Baoding and Shijiazhuang–Jinan high-speed railways reached 326 mm, 384 mm and 350 mm, respectively. The forecasting accuracy for land subsidence along high-speed railways was enhanced by the EMD-GBDT model. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were 0.38 mm to 0.56 mm and 0.23 mm to 0.38 mm, respectively.

Land Subsidence in a Coastal City Based on SBAS-InSAR Monitoring: A Case Study of Zhuhai, China

The superimposed effects of sea level rise caused by global warming and land subsidence seriously threaten the sustainable development of coastal cities. In recent years, an important coastal city in China, Zhuhai, has been suffering from severe and widespread land subsidence; however, the characteristics, triggers, and vulnerability assessment of ground subsidence in Zhuhai are still unclear. Therefore, we used the SBAS-InSAR technique to process 51 Sentinel-1A images to monitor the land subsidence in Zhuhai during the period from August 2016 to June 2019. The results showed that there was extensive land subsidence in the study area, with a maximum rate of −109.75 mm/yr. The surface had sequentially undergone a process of minor uplift and decline fluctuation, sharp settlement, and stable subsidence. The distribution and evolution of land subsidence were controlled by tectonic fractures and triggered by the thickness of soft soil, the intensity of groundwater development, and the seasonal changes of atmospheric precipitation. The comprehensive index method and the analytic hierarchy process were applied to derive extremely high subsidence vulnerability in several village communities and some traffic arteries in Zhuhai. Our research provides a theoretical basis for urban disaster prevention in Zhuhai and the construction planning of coastal cities around the world.

Research on prevention and control methods of land subsidence induced by groundwater overexploitation based on three-dimensional fluid solid coupling model—a case study of Guangrao County

Land subsidence is an environmental geological phenomenon with slowly decreasing ground elevation, The North China Plain is one of the areas with the most serious land subsidence in China, and Guangrao County is one of the subsidence centers. This paper is based on the hydrogeological and engineering geological data of Guangrao County, the groundwater monitoring data for many years and the land subsidence monitoring data, systematically analyzes the dynamic characteristics of groundwater, the distribution and evolution of land subsidence, and the correlation between groundwater exploitation and land subsidence development in different layers of this area. Based on Biot porous medium consolidation theory, establishes a three-dimensional fluid solid coupling numerical model of land subsidence in Guangrao County, restores the development process of land subsidence, predicts and analyzes the subsidence evolution law under different groundwater exploitation schemes, and proposes targeted prevention and control measures. The research results show that: the shallow groundwater forms a cone of depression with Guangbei Salt Field as the center, and the deep groundwater forms an elliptical regional cone of depression with the urban area as the center. The ground is gradually formed two small settlement areas with the urban area of Guangrao County and Guangbei Salt Field as the settlement center, and there is a trend of interrelated expansion. The three-dimensional fluid solid coupling model of land subsidence accurately restored the development process of land subsidence in the study area, predicted that under the current groundwater exploitation conditions, by 2040, the settlement of Guangrao urban settlement center will increase to 1,350 mm, forming a large regional funnel centered around the urban area, and gradually developing and expanding around. Prohibition of groundwater exploitation in the main funnel area is a more reasonable and effective exploitation plan to prevent the development of land subsidence.

Tri-decadal evolution of land subsidence in the Beijing Plain revealed by multi-epoch satellite InSAR observations

The persistent land subsidence in the Beijing Plain induced by the massive exploitation of groundwater caused significant decreases in ground elevation and damages to buildings and civil infrastructures. Although various satellite SAR datasets have been analyzed to monitor subsidence in the Beijing Plain, no multi-decadal scale deformation measurement has been derived from multi-sensor InSAR results, and the recent deceleration of land subsidence or even uplift remains unclear. This study retrieved land subsidence measurements over the past three decades (1992–2022) by integrating multi-sensor C-band InSAR measurements into a logistic model. The cumulative subsidence presented three major subsidence funnels surrounding downtown in the North, Northeast, and East, with the maximum vertical displacement as high as 1.98 m in the Chaoyang District. The land subsidence positively responded to the changes in groundwater depth, showing a clear deceleration since 2016. After five and half years, it became almost stagnated within the context of continuous groundwater recovery, which implied the delayed compaction of lowly draining aquitards. Only slight residual subsidence persisted in Chaoyang, Shunyi, and Daxing Districts. Meanwhile, land uplift happened in Shunyi, Huairou, and Pinggu Districts. Remarkably, a portion of the land subsidence in the Chaobai Plain reversed to uplift due to multiple artificial recharges using diverted water. Although groundwater storage could recover significantly in the next decade, most severely sunken lands and inelastically compacted aquitards are irrecoverable, leading to a permanent loss of storage capacity in the Beijing Plain. This study provides scientific data support for the local government decision-maker to better manage groundwater resources and mitigate land subsidence, which presents a typical example of monitoring long-term land subsidence in similar global megacities.

Influence of Urban Expansion on Land Subsidence: A Case Study of Tongzhou District, Beijing

Land subsidence is a common urban geological disaster. With the acceleration of urbanization, land subsidence is increasingly affected by urban expansion. It is of great significance to study the influence of urban expansion on land subsidence for urbanization construction and policy guidance. Under the strategic background of building Beijing into a sub-center of the city, the rapid expansion of Tongzhou city, the accelerated construction of infrastructure and the sharp increase of population will all put new pressure on the evolution of land subsidence in Tongzhou. This paper takes Tongzhou District of Beijing as an example, and takes 2015-2021 as the research period. In order to reflect the increment of urban expansion process, the improved multilinear model and land use monitoring based on RS and GIS are used to study the urban expansion process, and the relationship between urban expansion and land subsidence in Tongzhou District is analyzed by using Sentinel-2 satellite remote sensing image data and GIS spatial analysis method. The results show that: 1) With the increase of years, the annual settlement in Tongzhou District of Beijing shows a slowing trend. 2) The process of urban expansion is accelerating, and the urban expansion shows a trend of first accelerating and then slowing down, which leads to the evolution of land subsidence in Tongzhou city. 3) There is a high correlation between the process of urban expansion and the trend of settlement.

Land subsidence prediction model based on its influencing factors and machine learning methods

Land subsidence has caused huge economic losses in the Beijing plains (BP) since 1980s. Building land subsidence prediction models that can predict the development of land subsidence is of great significance for improving the safety of cities and reducing economic losses in Eastern Beijing plains. The pattern of evolution of land subsidence is affected by many factors including groundwater level in different aquifers, thicknesses of compressible layers, and static and dynamic loads caused by urban construction. First, we used the small baseline subset Interferometric Synthetic Aperture Radar (SBAS‐InSAR) technology on 47 ENVISAT ASAR images and 48 RADARSAT‐2 images and used Persistent Scatterers Interferometric Aperture Radar (PS-InSAR) technology on 27 Sentinel-1 images to obtain the land subsidence monitoring results from June 2003 to September 2018. Second, the accuracy of the InSAR monitoring results was validated by using leveling benchmark land subsidence monitoring results. Finally, we built land subsidence rate prediction models and land subsidence gradient prediction models by combining land subsidence influencing factors and four machine learning methods including support vector machine (SVM), Gradient Boosting Decision Tree (GBDT), Random forest (RF) and Extremely Randomized Trees (ERT). The findings show: (1) The InSAR monitoring results revealed that the Beijing Plain has experienced serious land subsidence during the 2003–2010, 2011–2015 and 2016–2018 periods. (2): The InSAR monitoring results agreed well with the leveling benchmark monitoring results with the Pearson correlation coefficients of two monitoring results were all greater than 0.95 during the 2003–2010, 2011–2015 and 2016–2018 periods, respectively. (3): We found that the land subsidence prediction based on ERT method is the optimal model among four land subsidence prediction models and that the prediction performance of land subsidence prediction model based on ERT method will be greatly improved when apply this prediction model in sub study areas where the land subsidence mechanism is similar owning to the similar hydrogeological parameters.

Land Subsidence Evolution and Simulation in the Western Coastal Area of Bohai Bay, China

Groundwater overexploitation and loading of buildings have been the main factors triggering land subsidence along the west coast of Bohai Bay, China, since the 2000s. Uneven subsidence has been causing damage to buildings and civil facilities, loss of elevation, increasing the risk of flood and seawater intrusion, and threatening the safety of people’s lives and property. This paper analyzed the spatial and temporal features of land subsidence along the coastal area from 2003 to 2010 and from 2015 to 2020, respectively. The relations between the initiating factors and land subsidence were explored. Then, the simulation model of land subsidence was constructed through a deep learning method. During the process, multiple data were collected, including land satellite (Landsat), environmental satellite advanced synthetic aperture radar (ENVISAT ASAR) and Sentinel-1 images, leveling data, lithological data, and groundwater level data. The area occupied by buildings and vertical displacement were extracted by using supervised classification, small baseline subset (SBAS), and persistent scatterer interferometry (PSI) technologies. The gated recurrent unit (GRU) neural network was adopted to simulate the evolution of land subsidence. Results showed that the maximum annual vertical displacement rate decreased from −94 mm/yr during 2003–2010 to −87 mm/yr during 2015–2020. The correlation efficiency between the groundwater level of the third confined aquifer group and land subsidence was larger than the area occupied by buildings and the compressible layer thickness with subsidence. The constructed GRU neural network model can simulate subsidence from September 2019 to December 2019, with the overall RMSE and MAE being 3.16 mm and 2.19 mm, respectively. This work can facilitate an understanding of the evolution and prevention of land subsidence along the west coast of Bohai Bay, which will provide information for policy decisions and flood-fighting plans of the worldwide coastal cities.

Dewatering-Induced Stratified Settlement around Deep Excavation: Physical Model Study

The multi-aquifer and multi-aquitard system (MAMA) is a typical geological structure in deltas. Thus, the risks and challenges to settlement control and environmental protection are increased when demand for underground space extends to deeper strata. In this study, dewatering-induced stratified settlement in MAMA is divided into three stages according to whether the overlying aquitard is coupled with groundwater seepage. Subsequently, large physical model tests were carried out. Seepage and compression in the overlying strata come after the compression in the confined aquifer and the coordinated deformation in the overlying strata. The soil is compressed under the seepage drive within the hydraulic gradient range, while the soil above it is still affected by coordinated deformation and shows expansion. Dewatering-induced uneven settlement will cause damage to existing foundations and underground structures. Large-scale and uninterrupted excavation and dewatering are the main reasons for the continuous development of land subsidence. Although artificial groundwater recharging can reduce the settlement of the existing building, underground structure, and surrounding strata, a reasonable space arrangement is needed.

Spatiotemporal heterogeneity of land subsidence in Beijing

Land subsidence induced by groundwater level decline has spatiotemporal variations. Taking the Interferometric Synthetic Aperture Radar (InSAR) results and the groundwater subsidence data acquired by the monitoring stations as the source material, this paper aims to reveal the spatiotemporal heterogeneity of groundwater-land subsidence in Beijing plain by using the Wind Rose Map (WRM) method and the Change Point Analysis (CPA) method. The WRM results show that the amount and variation in subsidence differs in different directions. This method detected the formation of new subsidence centers and the slowdown of land subsidence in 2008. The CPA results show that obvious changes are detected in subsidence development at the Wangsiying (WSY), Tianzhu (TZ) and Wangjing (WJ) stations. However, there is a relatively stable trend of groundwater decline and land subsidence at the Tianzhu (TZ) station. The stages of land subsidence development show a significant response to groundwater. Moreover, changes in land subsidence also show delayed response behind the changes in groundwater level. The time-lag could be affected by the variation in amplitude of the groundwater level.

Identification and assessment of land subsidence development in rural areas using PS interferometry: a case study in Western Michoacan, Mexico

Identification and assessment of land subsidence development in rural areas using PS interferometry: a case study in Western Michoacan, Mexico

Analysis of the Spatial and Temporal Evolution of Land Subsidence in Wuhan, China from 2017 to 2021

Land subsidence is a common geological hazard. Rapid urban expansion has led to different degrees of ground subsidence within Wuhan in the past few years. The novel coronavirus outbreak in 2020 has seriously impacted urban construction and people’s lives in Wuhan. Land subsidence in Wuhan has changed greatly with the resumption of work and production. We used 80 Sentinel-1A Synthetic Aperture Radar (SAR) images covering Wuhan to obtain the land subsidence change information of Wuhan from July 2017 to September 2021 by using the small baseline subset interferometric SAR technique. Results show that the subsidence in Wuhan is uneven and concentrated in a few areas, and the maximum subsidence rate reached 57 mm/yr during the study period. Compared with land deformation before 2017, the land subsidence in Wuhan is more obvious after 2020. The most severe area of subsidence is located near Qingling in Hongshan District, with a maximum accumulated subsidence of 90 mm, and obvious subsidence funnels are observed in Qiaokou, Jiangan, Wuchang and Qingshan Districts. The location of subsidence centers in Wuhan is associated with building intensity, and most of the subsidence funnels are formed in connection with urban subway construction and building construction. Carbonate belt and soft ground cover areas are more likely to lead to karst collapse and land subsidence phenomena. Seasonal changes are observed in the land subsidence in Wuhan. A large amount of rainfall can replenish groundwater resources and reduce the rate of land subsidence. The change in water level in the Yangtze River has a certain impact on the land subsidence along the rivers in Wuhan, but the overall impact is small. An obvious uplift is observed in Caidian District in the south of Wuhan, and the reason may be related to the physical and chemical expansion effects of the expansive clay.

Land Subsidence Monitoring and Dynamic Prediction of Reclaimed Islands with Multi-Temporal InSAR Techniques in Xiamen and Zhangzhou Cities, China

Artificial islands and land reclamation are one of the most important ways to expand urban space in coastal cities. Long-term consolidation of reclaimed material and compaction of marine sediments can cause ground subsidence, which may threaten the buildings and infrastructure on the reclaimed lands. Therefore, it is crucial to monitor the land subsidence and predict the future deformation trend to mitigate the damage and take measures for the land reclamation and any infrastructure. In this paper, a total of 125 SAR images acquired by the C-band Sentinel-1A satellite between June 2017 and September 2021 are collected. The small baseline subsets (SBAS) SAR interferometry (InSAR) method is first conducted to detect the land deformation in Xiamen and Zhangzhou cities of Fujian Province, China, and the distributed scatterers (DS)-InSAR method is used to recover the complete deformation history of some typical areas including Xiamen Airport in Dadeng Island and Shuangyu Island. Then, the sequential estimation and the geotechnical model are jointly applied to demonstrate the current and future evolution of land subsidence of the constructed roads on Shuangyu Island. The results show that the maximum cumulative deformation reaches 425 mm of Xiamen Xiang’an Airport and 626 mm of Shuangyu Island, and the maximum deformation is predicted to be as large as 1.1 m by 2026 of Shuangyu Island. This research will provide important guidelines for the design and construction of Xiamen Xiang’an Airport and Shuangyu Island to prevent and control land subsidence.

Characterizing Spatiotemporal Patterns of Land Deformation in the Santa Ana Basin, Los Angeles, from InSAR Time Series and Independent Component Analysis

The excessive extraction and recharge of groundwater lead to long-time seasonal land subsidence in Los Angeles, USA, and especially in the Santa Ana basin. The rate of land subsidence in the Santa Ana basin has been rising, which could pose a danger to infrastructure and human lives. However, the most recent research on land surface deformation in the area was conducted using the traditional parameter estimation method, resulting in little understanding of the regional spatiotemporal characteristics. The parametric method consists of a least square linear inversion, using the pre-defined mathematical geometric or geophysical theoretical models to describe groundwater deformation, and it requires precise external environmental variables and accurate geophysical parameters, which are more difficult to implement. In this study, multitemporal InSAR-derived deformation time series are analyzed by using 69 descending C-band Sentinel-1A SAR scenes acquired from 2015 to 2018. A method based on independent component analysis (ICA) is applied to characterize the spatial pattern and temporal evolution of land subsidence in the Santa Ana basin. The results reveal two different spatial and temporal deformation patterns in the basin. First, a widespread seasonal deformation is identified by the first component, related to annual seasonal groundwater level changes, and the overall deformation shows a concentrated spatial pattern. The second component captures a long-term signal with a large-scale spatial pattern. For quantitative assessment, the obtained deformation time series are compared with the GNSS data, validating an accuracy of millimeters. We further calculate the cross-correlation coefficient and the elastic skeletal storage coefficient from the ICA-derived seasonal deformation and groundwater level, which reveals that the deformation responds quickly (i.e., a lag of 8 days) to the change in groundwater and the Santa Ana aquifer retains almost the same elasticity for at least 15 years. Quantifying the spatiotemporal characteristics of the deformation in the Santa Ana basin can provide a reference for the monitoring and managing of groundwater.

Beijing Land Subsidence Revealed Using PS-InSAR with Long Time Series TerraSAR-X SAR Data

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.