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Global climate change highlights the significance of renewable clean energy. Geothermal energy from oilfields is abundant and can be utilized for residential heating and oil transportation. However, unreasonable heat exchange methods lead to groundwater level decline. Differences and delays between water extraction and reinjection inevitably cause land subsidence, hindering the sustainable utilization of geothermal energy resources. It is crucial to effectively monitor large-scale ground surface deformation characteristics in geothermal fields. In the research, 55 Sentinel-1A images from October 2018 to May 2022 were collected, and the ground deformation of Caofeidian new district in Bohai Bay Basin, where Nanpu Oilfield is located, in North China, was inverted by short baseline subsets-interferometric synthetic aperture radar (SBAS-InSAR) technology. The maximum subsidence velocity in Caofeidian new district exceeded 50 mm/year. Since April 2019, there has been concentrated ground subsidence in the Caofeidian new district, with a maximum cumulative subsidence exceeding 50 mm. The maximum cumulative subsidence exceeded 150 mm by May 2022. Combined with pumping and recharging tests near heating project in Caofeidian new district, the temporal subsidence mechanisms were revealed. The water extraction from the thermal reservoir caused drainage consolidation of the strata, triggering rapid subsidence in November. In April, discrepancy between water extraction and reinjection flow rate in thermal reservoir caused drainage consolidation of the strata, further exacerbating the subsidence trend. During rainy seasons, despite water reinjection and groundwater replenishment from precipitation, the strata in the Caofeidian new district underwent irreversible plastic deformation, with a slow rebound process, lagging behind urban areas without geothermal development by one month. InSAR is a reliable technology for understanding the ground deformation process in geothermal fields. Clarifying the subsidence mechanisms guides the selection of water-heat exchange methods, ensuring the sustainable development of geothermal resources. [ABSTRACT FROM AUTHOR]

The joint action of human activities and environmental changes contributes to the frequent occurrence of landslide, causing major hazards. Using Interferometric Synthetic Aperture Radar (InSAR) technique enables the detailed detection of surface deformation, facilitating early landslide detection. The growing availability of SAR data and the development of artificial intelligence have spurred the integration of deep learning methods with InSAR for intelligent geological identification. However, existing studies using deep learning methods to detect landslides in InSAR deformation often rely on single InSAR data, which leads to the presence of other types of geological hazards in the identification results and limits the accuracy of landslide identification. Landslides are affected by many factors, especially topographic features. To enhance the accuracy of landslide identification, this study improves the existing geological hazard detection model and proposes a multi-source data fusion network termed MSFD-Net. MSFD-Net employs a pseudo-Siamese network without weight sharing, enabling the extraction of texture features from the wrapped deformation data and topographic features from topographic data, which are then fused in higher-level feature layers. We conducted comparative experiments on different networks and ablation experiments, and the results show that the proposed method achieved the best performance. We applied our method to the middle and upper reaches of the Yellow River in eastern Qinghai Province, China, and obtained deformation rates using Sentinel-1 SAR data from 2018 to 2020 in the region, ultimately identifying 254 landslides. Quantitative evaluations reveal that most detected landslides in the study area occurred at an elevation of 2500–3700 m with slope angles of 10–30°. The proposed landslide detection algorithm holds significant promise for quickly and accurately detecting wide-area landslides, facilitating timely preventive and control measures. [ABSTRACT FROM AUTHOR]

Nonlinear deformation is a dynamically changing pattern of multiple surface deformations caused by groundwater overexploitation, underground coal mining, landslides, urban construction, etc., which are often accompanied by severe damage to surface structures or lead to major geological disasters; therefore, the high-precision monitoring and prediction of nonlinear surface deformation is significant. Traditional deep learning methods encounter challenges such as long-term dependencies or difficulty capturing complex spatiotemporal patterns when predicting nonlinear deformations. In this study, we developed a dual-attention-mechanism CNN-LSTM network model (DACLnet) to monitor and accurately predict nonlinear surface deformations precisely. Using advanced time series InSAR results as input, the DACLnet integrates the spatial feature extraction capability of a convolutional neural network (CNN), the advantages of the time series learning of a long short-term memory (LSTM) network, and the enhanced focusing effect of the dual-attention mechanism on crucial information, significantly improving the prediction accuracy of nonlinear surface deformations. The groundwater overexploitation area of the Turpan Basin, China, is selected to test the nonlinear deformation prediction effect of the proposed DACLnet. The results demonstrate that the DACLnet accurately captures developmental trends in historical surface deformations and effectively predicts surface deformations for the next two months in the study area. Compared to traditional LSTM and CNN-LSTM methods, the root mean square error (RMSE) of the DACLnet improved by 85.09% and 68.57%, respectively. These research results can provide crucial technical support for the early warning and prevention of geological disasters and can serve as an effective alternative tool for short-term ground subsidence prediction in areas lacking hydrogeological and other related data. [ABSTRACT FROM AUTHOR]

The accurate prediction of landslide susceptibility relies on effectively handling landslide absence samples in machine learning (ML) models. However, existing research tends to generate these samples in feature space, posing challenges in field validation, or using physics-informed models, thereby limiting their applicability. The rapid progress of interferometric synthetic aperture radar (InSAR) technology may bridge this gap by offering satellite images with extensive area coverage and precise surface deformation measurements at millimeter scales. Here, we propose an InSAR-based sampling strategy to generate absence samples for landslide susceptibility mapping in the Badong–Zigui area near the Three Gorges Reservoir, China. We achieve this by employing a Small Baseline Subset (SBAS) InSAR to generate the annual average ground deformation. Subsequently, we select absence samples from slopes with very slow deformation. Logistic regression, support vector machine, and random forest models demonstrate improvement when using InSAR-based absence samples, indicating enhanced accuracy in reflecting non-landslide conditions. Furthermore, we compare different integration methods to integrate InSAR into ML models, including absence sampling, joint training, overlay weights, and their combination, finding that utilizing all three methods simultaneously optimally improves landslide susceptibility models. [ABSTRACT FROM AUTHOR]

Time series dynamic prediction of surface deformation in mining areas can provide reference data for coal mine safety and production, which has important impacts. The combination of interferometric synthetic aperture radar (InSAR) technology and the probability integral method (PIM) is commonly used for predicting deformation. However, most surface subsidence prediction in mining areas is based on the static PIM parameters, failing to achieve the three-dimensional (3D) dynamic deformation prediction. This paper proposed a 3D deformation dynamic prediction model (InSAR-3D-CTPIM) between InSAR deformation observations and dynamic coordinate-time PIM (CTPIM) parameters, which can realize the prediction of east–west, north–south, and vertical series deformation caused by mining. The method has been validated by simulation experiments and real experiments in the mining area of Jiansheng Coal Mine in Baisha Reservoir, Henan Province, China. The results showed that the modeling accuracy was improved by 34.3% compared to the traditional multi-rate model, and the accuracy was improved by 28.5% compared to the vertical deformation obtained by the traditional static PIM method. The InSAR-3D-CTPIM model can be used to predict the evolutionary history of basin-wide surface deformation dynamics in coal mining areas, and provide a reference for the early warning and prediction of geological hazards in coal mining areas. [ABSTRACT FROM AUTHOR]

In the early stages, uncontrolled groundwater extraction led to the Hangjiahu (HJH) Plain becoming one of the areas with the most severe land subsidence in China. Since the beginning of this century, comprehensive measures have been taken to control the continuous aggravation of large land subsidence patterns in some areas; however, urban land subsidence issues, influenced by various factors, still persist and exhibit complex geographical distribution characteristics. In this study, we utilized Sentinel-1A images and the SBAS-InSAR technique to capture surface deformation over the HJH Plain in Zhejiang from 16 March 2017 to 20 January 2023. Through a comparative analysis with geological conditions, changes in surface mass loading, rainfall and groundwater, and land use types, we discussed the contributions of natural and anthropogenic factors to land subsidence. Augmented with optical remote sensing images and field investigations, we conducted a correlation analysis of the land subsidence status. The preliminary findings suggest that changes in surface mass loading and short-term heavy rainfall under extreme weather conditions can lead to periodic land subsidence changes in the region. Additionally, extensive infrastructure construction triggered by urbanization has resulted in significant and sustained land subsidence deformation. The research findings play an important guiding role in formulating scientifically effective strategies for land subsidence prevention and control, as well as urban planning and construction. [ABSTRACT FROM AUTHOR]

To systematically and thoroughly analyze the sensitivity and reliability of the MSBAS regularization for the estimation of surface deformation over a mine in combination with an application example, this study processed 101 Sentinel-1A/B SAR images, constructed and solved the 2D deformation models using SVD and Tikhonov regularization methods with different orders and parameters, and estimated the vertical and east-west surface deformation time series in a mine of China. Then, this study collected the leveling-monitoring vertical surface deformation data on three leveling points, and compared and analyzed the sensitivity and reliability of the MSBAS regularization methods for estimating vertical surface deformation. The results indicate that different regularization orders and parameters can lead to thousands of times differences in condition numbers and significant differences in illposed degree of the deformation models. The zero-order Tikhonov regularized deformation model with regularization parameter of 0.1 has the minimum condition number and the equation is not ill-posed. The first-order Tikhonov regularized deformation model with regularization parameter of 0.001 has the maximum condition number and the equation is seriously illposed. As a result, the estimates of 2D surface deformation models with different parameters and orders are also different in terms of numerical values and accuracy. Compared with the leveling-monitoring data, the first- and second-order MSBAS regularization methods with parameter 0.1 have the minimum fluctuation and the maximum correlation coefficients between the estimated values and the leveling-monitoring values, and are also closest to the leveling-monitoring results with the highest accuracy. [ABSTRACT FROM AUTHOR]

Characterizing the coseismic slip behaviors of earthquakes could offer a better understanding of regional crustal deformation and future seismic potential assessments. On 18 December 2023, an Mw 6.0 earthquake occurred on the Lajishan–Jishishan fault system (LJFS) in the northeastern Tibetan Plateau, causing serious damage and casualties. The seismogenic fault hosting this earthquake is not well constrained, as no surface rupture was identified in the field. To address this issue, in this study, we use Interferometric Synthetic Aperture Radar (InSAR) data to investigate the coseismic surface deformation of this earthquake and invert both ascending and descending line-of-sight observations to probe the seismogenic fault and its slip characteristics. The InSAR observations show up to ~6 cm surface uplift caused by the Jishishan earthquake, which is consistent with the thrust-dominated focal mechanism. A Bayesian-based dislocation modeling indicates that two fault models, with eastern and western dip orientations, could reasonably fit the InSAR observations. By calculating the coseismic Coulomb failure stress changes (∆CFS) induced by both fault models, we find that the east-dipping fault scenario could reasonably explain the aftershock distributions under the framework of stress triggering, while the west-dipping fault scenario produced a negative ∆CFS in the region of dense aftershocks. Integrating regional geological structures, we suggest that the seismogenic fault of the Jishishan earthquake, which strikes NNE with a dip of 56° to the east, may be either the Jishishan western margin fault or a secondary buried branch. The optimal finite-fault slip modeling shows that the coseismic slip was dominated by reverse slip and confined to a depth range between ~5 and 15 km. The released seismic moment is 1.61 × 1018 N·m, which is equivalent to an Mw 6.07 earthquake. While the Jishishan earthquake ruptured a fault segment of approximately 20 km, it only released a small part of the seismic moment that was accumulated along the 220 km long Lajishan–Jishishan fault system. The remaining segments of the Lajishan–Jishishan fault system still have the capability to generate moderate-to-large earthquakes in the future. [ABSTRACT FROM AUTHOR]

To solve the problems of large prediction error, slow convergence speed, and poor generalisation ability of traditional models in predicting surface deformation of open-pit mine slopes, this paper proposes a new intelligent prediction model based on the Mayfly algorithm-optimised support vector machine (MA-SVM). In this method, the MA is used to optimise the SVM parameters to reduce the uncertainty of the model and avoid time-consuming parameter adjustment. To evaluate the proposed prediction model, real-world deformation data of the north slope of the Anjialing open-pit mine in Pingshuo city, China, are collected using the microdeformation monitoring radar and used to investigate the deformation prediction performance of the proposed method. The results of the analysis demonstrate that the proposed method is able to accurately predict the deformation of the surface of the mine slope and outperforms three existing popular methods, including SVM, genetic algorithm (GA)-SVM, and particle swarm optimisation (PSO)-SVM). The mean absolute error (MAE) of the proposed MA⁃SVM is 2.52 % while 6.56 %, 4.95 %, and 5.16 % for the SVM, GA-SVM, and PSO-SVM, respectively; the root mean square error (RMSE) of the proposed MA⁃SVM is 10.21 % while 30.79 %, 17.38 %, and 22.54 % for the other three methods. Because the proposed MA⁃SVM model is able to predict slope deformation using actual monitoring data, it is of practical importance in real-world applications for early warning on landslides of mine slopes. [ABSTRACT FROM AUTHOR]

The Fenwei Basin, covered by loess, experiences severe ground fissure disasters. These disasters disrupt the continuity of the loess and pose significant threats to engineering construction safety along transportation routes. Nevertheless, the crack characteristics and the influence zone of ground fissures in the loess layer remain inadequately investigated. To effectively prevent and control ground fissure disasters, physical model tests and the PFC (particle flow code) numerical simulation method are used to investigate the crack mechanism of buried ground fissures in the loess layer. The results show that there are two main cracks in the layer profile, which have a Y-shape morphology. As the dip angle of the preset cracks increased from 60° to 90°, the main deformation zone at the surface gradually shifted towards the footwall. The process of crack propagation from depth to surface is divided into five stages. Additionally, the results confirm the accuracy of the width of the rupture zone d2 in the footwall calculated by the cantilever beam theory. These findings can offer theoretical guidance for determining the avoidance distance of ground fissures in loess regions, as well as for implementing disaster prevention and corresponding control measures for various stages of buried ground fissure propagation. [ABSTRACT FROM AUTHOR]

The study of shield tunnel segment flotation is crucial for controlling the precision of underground excavation projects. Based on Winkler's beam foundation theory, the load structure method, and the equivalent continuous beam model, and by considering the mechanical and spatial conditions that cause segment flotation, a novel theoretical calculation method for cumulative flotation is proposed using a simplified equivalent stiffness model of the tunnel. Additionally, a new concept of "equivalent flotation force" is introduced. The rationality and applicability of this theoretical calculation method are verified by comparing it with on-site construction data from the Yuanjiang River Crossing Tunnel Project in Changde, Hunan Province, China. The experimental results demonstrate that the theoretical calculation closely approximates the surface deformation monitoring data of the tunnel alignment in the eastern section of the project, and their deformation patterns are similar. Near the starting shaft, there is significant settlement influenced by stratum loss due to smaller tunnel flotation, with greater settlement occurring in the upper part. However, at approximately 45 m into both sections, they enter a deformation stability zone showing significant correlation in longitudinal deformation. Through comparison and verification of on-site experiments and theoretical model analysis, we preliminarily elucidate the feasibility of this innovative cumulative flotation theoretical calculation method which provides an important theoretical basis for assessing segment flotation issues in subsequent tunnel shield construction evaluations. [ABSTRACT FROM AUTHOR]

The establishment of a quantitative relationship between land subsidence and its influencing factors is a crucial task in developing prevention strategies of land subsidence in specific areas. In this study we examined the dynamic patterns of land subsidence before and after establishing the South-to-North Water Division Project (SNWDP) in the Tianjin Plain (TJP) that aims to reduce groundwater extractions in certain areas. Statistical analyses were used to determine the key attributing factors contributing to land subsidence that were subsequently used to derive the so-called 'critical water level of land subsidence'(CWLS), which were used to manage groundwater extractions with the objective of minimizing further land subsidence. The main results obtained were as follows: under the influence of the SNWDP, the groundwater level in the TJP stopped declining and the water level rose in most areas. The area of 'strong' subsidence, defined as the area with a subsidence rate greater than 50 mm a−1, decreased from 16.0% before the SNWDP to 2.5% after. The results of the multi-scale geographically weighted regression (MGWR) model revealed that groundwater drawdown in the second and third confined aquifer was the main contributor to the areas classified as 'strong' and 'medium' land subsidence areas. Following the reduction in groundwater extractions, the behaviour of surface deformation can be grouped into two categories: first, a rebound in surface elevation; and, second, continuous compression with a lower subsidence rate. The first mode occurs mainly in the area of 'medium' and 'weak' subsidence, and the second mode occurs mainly in the 'strong' subsidence area. Supplementary material: The result of the MGWR model is available at https://doi.org/10.6084/m9.figshare.c.7103611 [ABSTRACT FROM AUTHOR]

Major earthquakes can cause extensive landsliding that poses a major threat to both property and human lives. In addition to co‐seismically triggered ground failure, the earthquake‐affected region remains vulnerable to landslides due to loosened and unstable materials and structures. Many researchers have studied landslide distributions and their controlling factors after earthquakes, but the function of ground motion is unclear. To investigate the connection in a strike‐slip earthquake, we analyzed the 5 September 2022 Luding earthquake (Mw 6.6) in Sichuan Province, China. We interpreted remote‐sensing images to obtain the landslide distribution before and after the earthquake, calculated surface deformation from D‐InSAR data (pre‐ and post‐earthquake), utilized a point‐source model for the focal mechanism inversion, and then constructed a finite fault model for the rupture slip. There are clear differences in the landslide distributions on the two sides of the fault before and after the earthquake. The density of co‐seismic landslides on the west side of the fault exceeded that on the east side. The patterns of surface deformation and ground motion indicated that the areas with larger deformation and motion were associated with more landslides. Furthermore, the landslide size decreased with distance from the fault. A new finding is that co‐seismic landslides induced by strike‐slip earthquakes result in high landslide concentration on both sides of the fault, while previous studies find that co‐seismic landslides triggered by thrust earthquakes present a hanging wall concentrated distribution pattern. These findings contribute to a more comprehensive understanding of the connection between ground movement patterns and landslide distributions. Plain Language Summary: Our research focused on the 5 September 2022 Luding earthquake in Sichuan Province, China. The study identified distinct disparities in the distribution of landslides on either side of the fault, both landslides that happen before, during, and shortly after an earthquake. The western side of the fault exhibited a higher density of landslides following seismic activity compared with the eastern side during the Luding earthquake. The areas experiencing more significant deformation and motion during the earthquake were more prone to landslides. Moreover, landslides induced by strike‐slip earthquakes displayed high landslide concentrations on both sides of the fault. In contrast, landslides triggered by thrust earthquakes predominantly exhibited a concentrated hanging wall distribution pattern. Key Points: The type of fault is a primary controller of the landslide distribution patternMore landslides occurred in areas with more deformation and greater ground motion [ABSTRACT FROM AUTHOR]

Geometric complexities play an important role in the nucleation, propagation, and termination of strike-slip earthquake ruptures. The 2021 Mw7.4 Maduo earthquake rupture initiated at a large releasing stepover with a complex fault intersection. In the epicentral region, we conducted detailed mapping and classification of the surface ruptures and slip measurements associated with the earthquake, combining high-resolution uncrewed aerial vehicle (UAV) images and optical image correlation with field investigations. Our findings indicate that the coseismic ruptures present discontinuous patterns mixed with numerous lateral spreadings due to strong ground shaking. The discontinuous surface ruptures are uncharacteristic in slip to account for the large and clear displacements of offset landforms in the epicentral region. Within the releasing stepovers, the deformation zone revealed from the optical image correlation map indicates that a fault may cut diagonally across the pull-apart basin at depth. The left-lateral horizontal coseismic displacements from field measurements are typically ≤0.6 m, significantly lower than the 1–2.7 m measured from the optical image correlation map. Such a discrepancy indicates a significant proportion of off-fault deformation or the possibility that the rupture stopped at a shallow depth during its initiation phase instead of extending to the surface. The fault network and multi-fault junctions west and south of the epicenter suggest a possible complex path, which retarded the westward propagation at the initial phase of rupture growth. A hampered initiation might enhance the seismic ground motion and the complex ground deformation features at the surface, including widespread shaking-related fissures. [ABSTRACT FROM AUTHOR]

A considerable number of coal mines employed room and pillar mining in the last century in northern China, where the goaf remained stable for a period of time; however, with the increased exposure of coal pillars, their collapse may gradually increase. The stability assessment of these old rooms and pillar goafs is challenging due to their concealment, irregular mining patterns, and the long passage of time. The methodology developed in this study, based on "space-sky-earth" remote sensing such as InSAR to trace historical deformation, the UAV observation of current surface damage, and comparison of mining spaces, can rapidly detect on a large scale the collapse of old goafs and the trend of damage. This study is conducted with an example of a coal mine in Yulin, Northern China, where obtained quantitative surface deformation values were integrated with qualitative surface damage interpretation results, followed by a yearly analysis of the overlying rock movement in accordance with the underground coal mining process. The results show that from 2007 to 2021, corresponding surface deformation and damage occurred following mining progress. However, the room and pillar goaf areas had not undergone any surface deformation, nor had there been incidents of landslides or ground fissures; therefore, it was speculated that no roof collapse had occurred in this region. The surface deformation and damage associated with underground coal mining are complex and influenced by the coal seam occurrence, mining methods, strata lithology, terrain slope, temporal evolution, and anthropogenic modifications. These phenomena are representative of the coal mining area, and this methodology can provide a reference for similar endeavors. [ABSTRACT FROM AUTHOR]

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To attain precise forecasts of surface displacements and deformations in goaf areas (a void or cavity that remains underground after the extraction of mineral resources) following coal extraction, this study based on the limitations of individual time function models, conducted a thorough analysis of how the parameters of the model impact subsidence curves. Parameter estimation was conducted using the trust-region reflective algorithm (TRF), and the time function models were identified. Then we utilized a combined model approach and introduced the sliding window mechanism to assign variable weights to the model. Based on this, the combined model was used for prediction, followed by the application of this composite prediction to engineering scenarios for the dynamic forecasting of surface movements and deformations. The results indicated that, in comparison with DE, GA, PSO algorithms, the TRF exhibited superior stability and convergence. The parameter models obtained using this method demonstrated a higher level of predictive accuracy. Moreover, the predictive precision of the variable-weight time function combined model surpassed that of corresponding individual time function models. When employing six different variable-weight combination prediction models for point C22, the Weibull-MMF model demonstrated the most favorable fitting performance, featuring a root mean square error (RMSE) of 32.98 mm, a mean absolute error (MAE) of 25.66 mm, a mean absolute percentage error (MAPE) of 7.67%; the correlation coefficient R2 reached 0.99937. These metrics consistently outperformed their respective individual time function models. Additionally, in the validation process of the combined model at point C16, the residuals were notably smaller than those of individual models. This reaffirmed the accuracy and reliability of the proposed variable-weight combined model. Given that the variable-weight combination model was an evolution from individual time function models, its applicability extends to a broader range, offering valuable guidance for the dynamic prediction of surface movement and deformation in mining areas. [ABSTRACT FROM AUTHOR]

Mountainous landscapes affected by strong earthquakes typically exhibit higher landslide susceptibility in post‐seismic periods compared to pre‐seismic conditions. This concept is referred to as the earthquake legacy effect, which needs to be better understood to develop an accurate post‐seismic landslide hazard assessment. The earthquake legacy effect is mainly assessed by monitoring either rapid landslide occurrences or slow‐moving landslides over time. However, landslide inventories provide discrete information both in spatial and temporal domains, whereas monitoring only selected slow‐moving landslides discards the response of hillslopes exposed to a given earthquake. Therefore, to provide a more comprehensive understanding of the concept, this research focuses on post‐seismic hillslope evolution by examining the deformation time series generated from the Interferometric Synthetic Aperture Radar technique over the area affected by the 2017 Mw 6.4 Nyingchi earthquake, China. We also analyse factors controlling these InSAR‐derived hillslope deformations. Our results show a high coherence between hydrologic conditions (i.e., precipitation and terrestrial water storage) and surface deformation in pre‐ and post‐seismic periods. The earthquake disturbs this strong correlation for a while (~2 years) right after the seismic tremor, and then, a seasonal deformation pattern depending on hydrologic conditions appears again. Our findings show that the average post‐seismic hillslope deformation is still higher than its pre‐seismic counterpart approximately four and a half years after the earthquake. These findings trigger further research questions regarding whether hillslopes could fully recover after a major earthquake or gain a new level of hillslope susceptibility caused by intense ground shaking. [ABSTRACT FROM AUTHOR]

Landslides are a common geological disaster, which cause many economic losses and casualties in the world each year. Drawing up a landslide list and monitoring their deformations is crucial to prevent landslide disasters. Interferometric synthetic aperture radar (InSAR) can obtain millimeter-level surface deformations and provide data support for landslide deformation monitoring. However, some landslides are difficult to detect due to the low-coherence caused by vegetation cover in mountainous areas and the difficulty of phase unwrapping caused by large landslide deformations. In this paper, a method based on multi-direction phase gradient stacking is proposed. It employs the differential interferograms of small baseline sets to directly obtain the abnormal region, thereby avoiding the problem where part of landslide cannot be detected due to a phase unwrapping error. In this study, the Sentinel-1 satellite ascending and descending data from 2018 to 2020 are used to detect landslides around Zhouqu County, China. A total of 26 active landslides were detected in ascending data and 32 active landslides in the descending data using the method in this paper, while the SBAS-InSAR detected 19 active landslides in the ascending data and 25 active landslides in the descending data. The method in this paper can successfully detect landslides in areas that are difficult for the SBAS-InSAR to detect. In addition, the proposed method does not require phase unwrapping, so a significant amount of data processing time can be saved. [ABSTRACT FROM AUTHOR]

The Loess Plateau is an important grain-producing area and energy base in China and is an area featuring dramatic changes in both surface and underground processes. However, the associations between surface deformation and groundwater storage changes in different landscape types in the region are still unclear. Based on Sentinel-1 and GRACE (Gravity Recovery and Climate Experiment) data, this study monitored and verified the surface deformation and groundwater storage changes in different landscape types, such as those of the Kubuqi Desert, Hetao Irrigation District, Jinbei Mining Area, and Shendong Mining Area, in the Loess Plateau of China from 2020 to 2021. Through time series and cumulative analysis using the same spatial and temporal resolution, the associations between these two changes in different regions are discussed. The results show that: (1) the surface deformation rates in different landscape types differ significantly. The minimum surface deformation rate in the Kubuqi Desert is −5~5 mm/yr, while the surface deformation rates in the Hetao Irrigation District, the open-pit mine recovery area in the Jinbei Mining Area, and the Shendong Mining Area are −60~25 mm/yr, −25~25 mm/yr, and −95.33~26 mm/yr, respectively. (2) The regional groundwater reserves all showed a decreasing trend, with the Kubuqi Desert, Hetao Irrigation District, Jinbei Mining Area, and Shendong Mining Area declining by 359.42 mm, 103.30 mm, 45.60 mm, and 691.72 mm, respectively. (3) The surface elasticity deformation had the same trend as the temporal fluctuation in groundwater storage, and the diversion activity was the main reason why the temporal surface deformation in the Hetao Irrigation District lagged behind the change in groundwater storage by 1~2 months. The measure of "underground water reservoirs in coal mines" slows down the rate of collapse of coal mine roof formations, resulting in the strongest time-series correlation between mild deformation of the surface of the Shendong mine and changes in the amount of groundwater reserves (R = 0.73). This study analyzes the associations between surface deformation and groundwater storage changes in different landscape areas of the Loess Plateau of China and provides new approaches to analyzing the dynamic associations between the two and the causes of changes in both variables. [ABSTRACT FROM AUTHOR]

The Lancang River flows through the alpine canyon region of southwest China, an area that has experienced frequent geological disasters over the years. Early monitoring of geological hazards is essential for disaster prevention and mitigation. However, traditional ground monitoring techniques are limited by the complex terrain conditions in high-altitude valley regions. In contrast, interferometric synthetic aperture radar (InSAR) technology can provide a high-precision, wide-range monitoring of slow rock-slope deformation, making it an effective tool for studying geological hazards. Within the study area, multiple synthetic aperture radar (SAR) images from the Sentinel-1A satellite were collected, and surface deformation was obtained using the small baseline subset InSAR (SBAS-InSAR). The results demonstrate that combining ascending and descending orbit images can be successfully applied to landslide monitoring in complex mountainous areas. Over 30 potential landslides were identified by combining InSAR results with optical images. The Line-Of-Sight (LOS) direction deformation features and their relationship with precipitation were analyzed based on two typical landslides, and two-dimensional/three-dimensional (2D/3D) deformation decomposition was carried out to reveal its motion characteristics. It was found that the cumulative deformation fluctuation amplitude was higher during the rainy season, and the main movement direction of the landslide was east–west. In addition, based on the spatial distribution and statistical analysis of deformation points along with meteorological data, geological elements, human activities, and topographic conditions, it is inferred that factors such as low vegetation coverage, tectonic movements, human activities, and high-altitude glacier thawing may contribute to the occurrence of disasters. And it was found that areas with high vegetation cover, high rainfall, and snow cover exhibit lower coherence coefficients. This study offers valuable insights for investigating large-scale geological in alpine canyon regions. [ABSTRACT FROM AUTHOR]

Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas. [ABSTRACT FROM AUTHOR]

The existing prediction methods have complex model application, high requirements for data parameters, and are limited to the prediction of a single observation point. To address this problem, this paper proposes a deep learning-based surface subsidence prediction method. Taking Hefei City of China as the research area, the time-series surface deformation results of this area are obtained by using SBAS-InSAR, and then the SFLA intelligent algorithm and Elman neural network model are combined to predict the surface deformation of key urban areas, and the prediction results are compared and analyzed.The experimental results show that the prediction model proposed in this paper can not only accurately predict a single deformation point, but also predict regional land subsidence, and can be used for auxiliary decision-making of urban spatial planning, early warning of geological hazards and hazard mitigation. [ABSTRACT FROM AUTHOR]

Backfill coal mining technology has drawn widespread attention due to its benefits of "controlling surface deformation and subsidence, reducing mining-induced disturbance in the stope, and recycling solid mine wastes". However, the backfill coal mining technology is still progressing slowly in China. The geological environment of China's mining areas is complex and highly diversified, and backfill coal mining is expected to fulfill different goals in a wide range of engineering scenarios. These facts explain the poor reproducibility of backfill coal mining projects. This study reviews the existing backfill coal mining systems in China. Based on findings from a survey of engineering cases, we summarize five types of new backfill coal mining methods classified by deployment style; namely, borehole grouting backfill, roadway backfill, borehole–roadway backfill, in situ backfill, and roadway-in-situ backfill. A total of 15 backfill coal mining methods falling into the above five categories are described. An engineering design workflow for backfill coal mining consisting of five steps is proposed; namely, identifying the targets of backfill, analyzing the feasibility of deploying the backfill system, comparing the engineering quantities of different engineering schemes, estimating the economic efficiency of backfill, and backfill performance tracking and monitoring. Real cases of backfill engineering design are analyzed to inform the fast and reasonable design of backfill strategy for specific working faces in certain coal mines. [ABSTRACT FROM AUTHOR]

The coal industry is a crucial component of China's energy sector. However, the persistent exploitation of coal resources has gravely impacted the ecological environment. While the Remote Sensing Ecology Index (RSEI) is predominantly used for assessing ecological quality, its primary focus has been urban or aquatic environments. There is limited research focused on the evaluation of the ecological environment quality in mining areas. Moreover, the information regarding surface deformation caused by coal mining extraction is an essential factor in the ecological monitoring of mining areas. Therefore, this study proposed the Modified Remote Sensing Ecology Index (MRSEI). This enhanced model merges active and passive remote sensing techniques and incorporates a deformation factor (Surface Deformation Index, SDI) to provide a holistic evaluation of mining area ecologies. Furthermore, for comparative verification, we developed the Eco-environmental Quality Index (EQI) model by selecting 12 ecological parameters and employing a hierarchical analysis. The Juye mining area in Shandong Province was selected as the region of study. MRSEI results from 2015 to 2021 indicate a decline in the ecological quality of the Juye mining area, with MRSEI values registering at 0.691, 0.644, and 0.617. The EQI model mirrors this decreasing trend over the same period. Despite MRSEI using fewer indicators, its assessments align closely with the multi-indicator EQI method. This validates the accuracy of the MRSEI method, providing reliable technical support for the monitoring and evaluation of ecological environment quality in mining areas. [ABSTRACT FROM AUTHOR]

SBAS InSAR has long been used to monitor the mining surface deformation, and its research has been of great interest to researchers worldwide. For the unsatisfactory accuracy of SBAS InSAR-monitored mining surface deformation results, a new corrected model is proposed by integrating SBAS InSAR and Logistic Function. Firstly, the time series deformation results of the mining area were obtained by SBAS InSAR, and the variation law of the differences between SBAS InSAR- and leveling-monitored deformation values was statistically analyzed. Subsequently, the corrected model was constructed using the logistic linear regression analysis function and solved using the Levenberg-Marquardt algorithm. Finally, the corrected high-precision time series deformation results in the mining area were obtained. A mining area in Shandong Province of China was taken as the research object, and the practical application effect of the proposed corrected model was verified. Results showed that the Logistic Function could describe the variation law of the differences relatively accurately, and the corrected results were significantly better than the SBAS InSAR-monitored results, and the RMSEs of the corrected results were improved by 33–58%. The accuracy of SBAS InSAR-monitored mining surface deformation was effectively improved. [ABSTRACT FROM AUTHOR]

Landslide susceptibility mapping based on static influence factors often exhibits issues of low accuracy and classification errors. To enhance the accuracy of susceptibility mapping, this study proposes a refined approach that integrates categorical boosting (CatBoost) with small baseline subset interferometric synthetic-aperture radar (SBAS-InSAR) results, achieving more precise and detailed susceptibility mapping. We utilized optical remote sensing images, the information value (IV) model, and fourteen influencing factors (elevation, slope, aspect, roughness, profile curvature, plane curvature, lithology, distance to faults, land use type, normalized difference vegetation index (NDVI), topographic wetness index (TWI), distance to rivers, distance to roads, and annual precipitation) to establish the IV-CatBoost landslide susceptibility mapping method. Subsequently, the Sentinel-1A ascending data from January 2021 to March 2023 were utilized to derive the deformation rates within the city of Lishui in the southern region of China. Based on the outcomes derived from IV-CatBoost and SBAS-InSAR, a discernment matrix was formulated to rectify inaccuracies in the partitioned regions, leading to the creation of a refined information value CatBoost integration (IVCI) landslide susceptibility mapping model. In the end, we utilized optical remote sensing interpretations alongside surface deformations obtained from SBAS-InSAR to cross-verify the excellence and accuracy of IVCI. Research findings indicate a distinct enhancement in susceptibility levels across 165,784 grids (149.20 km2) following the integration of SBAS-InSAR correction. The enhanced susceptibility classes and the spectral characteristics of remote sensing images closely correspond to the trends of SBAS-InSAR cumulative deformation, reflecting a high level of consistency with field-based conditions. These improved classifications effectively enhance the refinement of landslide susceptibility mapping. The refined susceptibility mapping approach proposed in this paper effectively enhances landslide prediction accuracy, providing valuable technical reference for landslide hazard prevention and control in the Lishui region. [ABSTRACT FROM AUTHOR]

In order to alleviate the conflict between populations and land resource, Tianjin adopted multi-phase reclamation projects to the formed large-scale artificial reclamation land. The reclamation areas, however, are prone to subsidence, which poses a significant threat to infrastructure as well as the safety and assets of the residents. The SBAS-InSAR was used to acquire surface deformation of Tianjin Binhai New Area from January 2017 to December 2022, analyze in depth the response relationship between land subsidence, reclamation project time, and land-use type. There is a strong correlation between surface deformation and reclamation time. Severe land subsidence occurred over newly reclaimed areas. In the offshore direction, the deformation values of the Nangang Industrial Zone, the Lingang Industrial Zone, and Hangu Harbor were −98 mm to −890 mm, 45 mm to −580 mm, and −140 mm to −290 mm, respectively. Significant differences in deformation were detected among different land-use types where reclamation projects were completed in the same time. Subsidence was positively correlated with surface load; in areas with higher surface loads, the surface settlement was also more severe. The average surface settlement for the heavy shipyard, with 67 grain storage tanks and 27 grain storage tanks, road, and bare land were −201 mm, −166 mm, −107 mm, −64 mm, and −43 mm, respectively. This study reveals significant differences of surface deformation in the reclamation completed at different times, and determines that the load is the main driving factor of settlement difference in the reclamation land completed at the same time. This has important guiding significance for preventing and controlling geological disasters in the reclamation area and later development planning. [ABSTRACT FROM AUTHOR]

The ground surface deformation induced by shield tunnels passing through enclosure structures of existing tunnels is a particular underground construction scenario that has been encountered in Wuhan Metro Line 12 engineering cases in China. Timely ground deformation prediction is important to keep shield tunneling safe. However, the classic ground deformation theory is difficult to accurately predict for this ground deformation. This paper develops a semi-analytical method to predict ground heave considering the space effect in this engineering condition. Based on the improved ground deformation theory, a novel deformation prediction method for the ground and enclosure structure is derived and combined with Kirchhoff plate theory. Comparing with field deformation measurements, the maximum difference between the measured and calculated deformation is 14.6%, which demonstrates that the proposed method can be used to predict the ground heave induced by shield tunnels passing through the enclosure structure of existing tunnels. The parameters of the underground diaphragm wall used in Wuhan Metro Line 12 are further studied in detail. The results show that the ground heaves have a positive correlation with the embedded ratio of the diaphragm wall, but a negative correlation with its elastic modulus and thickness. However, the thickness and embedded ratio have a limited effect on ground heaves. This study provides a technical reference for optimizing the setting of enclosure structures in order to protect existing buildings. [ABSTRACT FROM AUTHOR]

The Xiaolangdi Dam is a key project for the control and development of the Yellow River. It bears the functions of flood control, controlling water and sediment in the lower reaches, ice prevention, industrial and agricultural water supply, power generation, and so on. Its safety is related to people's life and property safety and local economic and social development. It is of great significance to carry out comprehensive and regular deformation monitoring for dams since the deformation is an important evaluation index for dam safety. Interferometric Synthetic Aperture Radar (InSAR) technology has been a rapidly evolving technology in the field of space geodesy in recent years. It offers advantages such as high monitoring precision, extensive coverage, and high monitoring point density, making it a powerful tool for monitoring deformations in hydraulic engineering projects. Based on Sentinel-1 data covering the Xiaolangdi Dam from September 2020 to November 2022, the PS-InSAR technique was used to obtain the surface deformation of the Xiaolangdi Dam, and reservoir water level data on image acquisition dates were obtained for joint analysis. The results show that there is a large deformation in the center of the dam crest of the Xiaolangdi Dam, while both sides of the slope and downstream dam foot are relatively stable. The time series deformation of the dam body is closely related to the reservoir water level change. When the water level increases, the dam body tends to deform downstream; when the water level decreases, the dam body tends to deform upstream. The deformation and water level of the Xiaolangdi Dam exhibit a clear negative correlation. There is no significant cumulative deformation on the dam slopes or at the base of the dam. However, cumulative deformation occurs over time in the central area of the dam's crest. The deformation process at the central area of the dam's crest follows a continuous and non-disruptive pattern, which is consistent with the typical deformation behavior of the Xiaolangdi earth–rock dam structure. Therefore, it is judged that the current deformation of the Xiaolangdi Dam does not impact the safe operation of the dam. InSAR technology enables the rapid acquisition of high-precision, high-density deformation information on the surfaces of reservoir dams. With an increasing number of radar satellites in various frequency bands, such as Sentinel-1 and TerraSAR-X, there is now an ample supply of available data sources for InSAR applications. Consequently, InSAR technology can be extended to routine monitoring applications for reservoir dam deformations, especially for small and medium-sized reservoirs that may not be equipped with ground measurement tools like GNSS. This holds significant importance and potential for enhancing the safety monitoring of such reservoirs. [ABSTRACT FROM AUTHOR]

Measuring surface deformation is crucial for a better understanding of spatial-temporal evolution and the mechanism of mining-induced deformation, thus effectively assessing the mining-related geohazards, such as landslides or damage to surface infrastructures. This study proposes a method of retrieving surface deformation by combining multi-temporal digital surface models (DSMs) with image homonymous features using China's ZY-3 satellite stereo imagery. DSM is generated from three-line-array images of ZY-3 satellite using a rational function model (RFM) as the imaging geometric model. Then, elevation changes in deformation are extracted using the difference of DSMs acquired at different times, while planar displacements of deformation are calculated using image homonymous features extracted from multi-temporal digital orthographic maps (DOMs). Scale invariant feature transform (SIFT) points and line band descriptor (LBD) lines are selected as two kinds of salient features for image homonymous features generation. Cross profiles are also extracted for deformation in typical regions. Four sets of stereo imagery acquired in 2012 to 2022 are used for deformation extraction and analysis in the Fushun coalfield of China, where surface deformation is quite distinct and coupled with rising and descending elevation together. The results show that 21.60% of the surface in the study area was deformed from 2012 to 2017, while a decline from 2017 to 2022 meant that 17.19% of the surface was deformed with a 95% confidence interval. Moreover, the ratio of descending area was reduced to 6.44% between 2017 and 2022, which is lower than the ratios in other years. The slip deformation area in the west open pit mine is about 1.22 km2 and the displacement on the south slope is large, reaching an average of 26.89 m and sliding from south to north to the bottom of the pit between 2012 and 2017, but elevations are increased by an average of about 16.35 m, involving an area of about 0.86 km2 between 2017 and 2022 due to the restoration of the open pit. The results demonstrate that more quantitative features and specific surface deformation can be retrieved in mining areas by combining image features with DSMs derived from ZY-3 satellite stereo imagery. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accurate prediction of surface subsidence is of significance for analyzing the pattern of mining-induced surface subsidence, and for mining under buildings, railways, and water bodies. To address the problem that the existing prediction models ignore the correlation between subsidence points, resulting in large prediction errors, a Multi-point Relationship Fusion prediction model based on Graph Convolutional Networks (MRF-GCN) for mining-induced subsidence was proposed. Taking the surface subsidence in 82/83 mining area of Yuandian No. 2 Mine in Anhui Province in eastern China as an example, the surface deformation data obtained from 250 InSAR images captured by Sentinel-1A satellite from 2018 to 2022, combined with GNSS observation data, were used for modeling. The deformation pattern of each single observation point was obtained by feeding their deformation observation data into the LSTM encoder, after that, the relationship graph was created based on the correlation between points in the observation network and MRF-GCN was established. Then the prediction results came out through a nonlinear activation function of neural network. The research shows that the R2R2 value of MRF-GCN model was 0.865 0, much larger than that of Long-Short Term Memory (LSTM) and other conventional models, while mean square error (MSE) of MRF-GCN model was 1.59 899, much smaller than that of LSTM and other conventional models. Therefore, the MRF-GCN model has better prediction accuracy than other models and can be applied to predicting surface subsidence in large areas. [ABSTRACT FROM AUTHOR]

Against the background of global warming, permafrost areas are facing increasing thawing, and the threat to the surface of the Qinghai–Tibet Engineering Corridor (QTEC) is serious. It is imperative to understand the current surface deformation and analyze the changes spatiotemporal characteristics for future warnings. At present, observation of a long time series and overall coverage of vertical ground deformation in QTEC are lacking. This paper takes the permafrost deformation of the QTEC as its research object. It uses the pretreated LiCSAR product and combines it with the LiCSBAS package to obtain monitoring results of the long time series deformation of the engineering corridor's surface. The SAR image acquisition date is taken as the constraint, the results covering the whole processing area are selected, and then the vertical deformation information covering the entire engineering corridor area by ignoring the north–south displacement is calculated. The results show that the surface of the study area, as a whole, slightly subsided between May 2017 and March 2022, and the vertical deformation rate was mostly distributed at −27.068 mm/yr − 18.586 mm/yr, with an average of −1.06 mm/yr. Vertical deformation dominated at 52.84 percent of the study area, of which settlement accounted for 27.57 percent and uplift accounted for 25.27 percent. According to the statistics of the normal distribution of deformation velocity per pixel, a total of 77% of the engineering corridor was stable, with a vertical deformation rate between −6.964 mm/yr and −4.844 mm/yr, and 17.7% of the region was sub-stable, with a settling rate of −12.868 mm/yr − –6.964 mm/yr. The unstable regions included areas with settlement rates greater than 12.868 mm/yr and uplift rates greater than 10.748 mm/yr, representing 4.4 percent and 0.9 percent of the total area, respectively, for a total of 5.3 percent. The results of this paper can be used as the theoretical basis and as basic data for decision making and scientific research in various departments, and they are of great significance for surface stability assessment and early warnings along engineering corridors and traffic projects. [ABSTRACT FROM AUTHOR]

The underground hole pile excavation method causes a large vertical displacement in a weak stratum, which affects the safety of structures. For the first time, the hole pile excavation method is being used to construct a subway station in South China, and the settlement law of the area is not clear. It is important to clarify the deformation law of the hole pile excavation method in weak strata and the effect achieved by appropriate reinforcement measures. In this paper, by establishing a three-dimensional finite element model of the structure–soil contact element and combining it with the field monitoring data, the law of surface settlement caused by the hole pile excavation method with different thicknesses of the weak stratum has been studied. In order to improve the stability of the surrounding rock and reduce the vertical deformation of the surface, the Metro Jet System (MJS) is used to form inclined piles in the area of large surface deformation, and the effect after reinforcement was evaluated. The results show that as the weak layer thickness ratio increases, the surface settlement also increases. In the case of no reinforcement, a vertical settlement of 116 mm can be achieved when the thickness of the weak layer is 14 m. The vault of the tunnel is in the weak layer and the deformation is obvious. When the vault is not in the weak layer, the settlement is obviously reduced. After MJS pile reinforcement, under the action of soil extrusion, the self-stability of the surrounding rock is strengthened, and the oblique jet grouted pile forms a stable 'triangle'. The vertical settlement value is basically stable at around 30 mm, which meets the requirements of the regulations. If the tunnel is not reinforced, the self-stability of the surrounding rock above the tunnel arch is poor and the maximum settlement is at the surface. After MJS reinforcement, the maximum settlement is at the vault. The vertical settlement of the ground surface can be effectively controlled by using the MJS pile forming technology in the middle of the tunnel pile driving method. [ABSTRACT FROM AUTHOR]

Land motions are significantly widespread in the Yellow River delta (YRD). There is, however, a lack of understanding of the delta-wide comprehensive deformation mode and its dynamic mechanism, especially triggered by groundwater extraction. This paper adopts an integrated analysis of multidisciplinary data of image geodesy, geophysics, geology and hydrogeology to provide insights into Earth surface displacement patterns and dynamics in the YRD. Delta-scale land motions were measured for the first time using L-band ALOS images processed using multi-temporal InSAR, illustrating multiple obvious surface sinking regions and a maximum annual subsidence velocity of up to 130 mm. Then, the InSAR-constrained distributed point source model with optimal kernel parameters, a smoothness factor of 10 and a model grid size of 300 m was established and confirmed to be rational, reliable and accurate for modeling analysis over the YRD. Remarkable horizontal surface displacements, moving towards and converging on a sinking center, were recovered by means of modeling and measured using InSAR, with a maximum rate of up to 60 mm per year, which can trigger significant disasters, such as ground fissures and building damage. In addition, the annual total water storage variation at the delta scale, the most meaningful outcome, can be calculated and reaches a total of approximately 12,010 × 103 m3 in Guangrao city, efficiently filling the gap of GRACE and in situ investigations for delta-wide aquifer monitoring. Finally, a comparative analysis of time series InSAR measurements, modeling outcomes, and fault and groundwater data was conducted, and the strong agreement demonstrates that faults control aquifer distribution and hence the spatial distribution of groundwater-withdrawal-related regional land subsidence. Moreover, the obvious asymmetric displacements, demonstrating a northeasterly displacement trend, further reveal that faults control aquifer distribution and Earth surface deformation. These findings are useful for understanding the land motion patterns and dynamics, helping to sustainably manage groundwater and control disasters in the YRD and elsewhere worldwide. [ABSTRACT FROM AUTHOR]

Most dams in China have been operating for a long time and are products of the economic and technical limitations at the time of construction. Due to decades of aging engineering and ancillary problems, these reservoirs pose great threats to the safety of local people and the development of the surrounding economy. In this study, the surface deformation information for the Banqiao Reservoir is monitored with the small baseline subset–synthetic aperture radar interferometry (SBAS-InSAR) method using 80 Sentinel-1A images acquired from 3 January 2020 to 20 August 2022. Additionally, ground measurements from the BeiDou ground-based deformation monitoring stations were collected to validate the InSAR results. Based on the InSAR results, the spatiotemporal deformation features of the dam were analyzed in detail. The results show that the deformation in most areas, including the dam in the study area, is relatively stable, and the regional deformation velocity of the Banqiao Reservoir dam and other hydraulic engineering facilities varies between −1 mm/y and −4 mm/y. The Ru River area has a relatively obvious subsidence trend, and the maximum subsidence velocity reaches 30 mm/y. The InSAR monitoring results are consistent with the change trend in the BeiDou ground-based deformation measurement results. The monitoring results for the reservoir dam area provide a reference for local sustainable development and geological disaster prevention. [ABSTRACT FROM AUTHOR]

During the postconstruction operation period, the engineering structure and operation safety of a pipe-jacking tunnel are more likely to be threatened by the surrounding environment and groundwater when it is located in a soft clay stratum. Surface settlement data related to the construction of 24 rectangular pipe-jacking tunnels in a soft clay stratum in China were collected and analyzed to determine the effect of pipe-jacking tunnel engineering on its deformation based on factors such as structural section form, geotechnical condition, groundwater condition, and buried depth. The postmaximum surface settlement and postformation loss rate were obtained, the correlation coefficients between the postsurface deformation of soft clay strata and various influencing factors were calculated using a software for correlation analysis, and the variation rules for each influencing factor were explored in depth. Subsequently, multiple linear regression methods were used to predict the maximum surface deformation of the pipe-jacking tunnel project in soft clay strata during the postoperation period, and actual engineering cases were verified and analyzed. The results show that the relative buried depth of the pipe-jacking tunnel in soft clay stratum has the greatest influence on the postmaximum ground settlement, followed by the section area of the pipe-jacking tunnel, and the relative height coefficient of groundwater level has the least influence. Under the reduction coefficient of 0.937 − 0.846, a new prediction formula for surface settlement deformation after the construction of the soft clay layer was derived. The error between the formula and the measured data was 9.05%, which can be used as a reference for controlling design parameters to predict the settlement after construction of pipe-jacking engineering. [ABSTRACT FROM AUTHOR]

The Ordos Block in China experiences tectonic activity and frequent earthquakes due to compression from the Tibetan Plateau and extension from the North China Block. This has prompted the construction of a high-resolution three-dimensional (3D) deformation field to better understand the region's crustal movement. Considering the limitations of the existing geodetic observations, we used InSAR, GPS, and leveling observations to create a high-precision 3D deformation field for the Ordos Block. Spherical wavelet decomposition was used to separate tectonic and non-tectonic deformation signals. Short-wavelength non-tectonic deformation fields revealed complex surface deformation patterns caused by groundwater, oil, gas extraction, and coal mining. Long-wavelength tectonic deformation fields showed subsidence in the southern margin of the block, while the interior and northeastern margins were uplifted. By combining imaging results from the seismic velocity structure and magnetotellurics, we infer that the upwelling of deep materials beneath the northeastern margin leads to surface uplift with tensile strain rates. The crustal uplift in the area south of 38°N matches the thickening of the lower crust. The weak subsidence and eastward horizontal movement disappearing near 108°E at the southern margin support the existence of asthenosphere flow beneath the Qinling orogenic belt. [ABSTRACT FROM AUTHOR]

The LuTan-1(LT-1), known as the L-band differential interferometric synthetic aperture radar (SAR) satellite system, is an essential piece of civil infrastructure in China, providing extensive applications such as surface deformation monitoring and topographic mapping. To achieve high-resolution and wide-swath (HRWS) observation abilities, the LT-1 takes the dual receiving antenna (DRA) imaging mode as its working mode. However, amplitude and phase errors between channels lead to a mismatch between the reconstruction filter and the multichannel echo signal, worsen the reconstructed azimuth spectrum, and introduce ambiguity targets in the final imaging results, seriously affecting the final imaging quality. In order to better evaluate the channel error and azimuth ambiguity performance of the LT-1 system, this paper proposed an advanced channel consistency correction method and conducted many measured data experiments. The experimental results show that the proposed method is effective, and the LT-1 system has excellent channel error control and azimuth ambiguity performance. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Interferometric synthetic aperture radar (InSAR) has developed rapidly over the past years and is considered as an important method for surface deformation monitoring, benefiting from growing data quantities and improving data quality. However, the handing of SAR big data poses significant challenges for related algorithms and pipeline, particularly in large-scale SAR data processing. In addition, InSAR algorithms are highly complex, and their task dependencies are intricate. There is a lack of efficient optimization models and task scheduling for InSAR pipeline. In this paper, we design parallel time-series InSAR processing models based on multi-thread technology for high efficiency in processing InSAR big data. These models concentrate on parallelizing critical algorithms that have high complexity, with a focus on deconstructing two computationally intensive algorithms through loop unrolling. Our parallel models have shown a significant improvement of 10–20 times in performance. We have also developed a parallel optimization tool, Simultaneous Task Automatic Runtime (STAR), which utilizes a data flow optimization strategy with thread pool technology to address the problem of low CPU utilization resulting from multiple modules and task dependencies in the InSAR processing pipeline. STAR provides a data-driven pipeline and enables concurrent execution of multiple tasks, with greater flexibility to keep the CPU busy and further improve CPU utilization through predetermined task flow. Additionally, a supercomputing-based system has been constructed for processing massive InSAR scientific big data and providing technical support for nationwide surface deformation measurement, in accordance with the framework of time series InSAR data processing. Using this system, we processed InSAR data with the volumes of 500 TB and 700 TB in 5 and 7 days, respectively. Finally we generated two maps of land surface deformation all over China. [ABSTRACT FROM AUTHOR]

The small pipe–roof–beam method has better adaptability to ultra-shallow buried subway stations. Five groups of similar model tests were carried out to explore the pipe–roof deformation, surface settlement, and beam strain caused by excavation using this method. Based on the test results, a 3D numerical model was established to study the pipe–roof deformation under different cases. The following conclusions were obtained: as the height-to-span ratio increases, the pipe–roof deformation, and surface settlement increase and, afterward, decrease. Increasing the number of beams can significantly reduce the pipe–roof deformation and surface settlement, and has a greater effect on the surface settlement. The soil-arching effect occurs above the pipe–roof during excavation, and is strengthened with an increase of height-to-span ratios. The difference between the pipe–roof deformation caused by excavation is within 2% in two cases: free at both ends and fixed at only one end. It is not recommended to add support to only one end in actual construction. Adding support at both ends can reduce the pipe–roof deformation by about 40%. The research conclusions have guiding significance for the development of the small pipe–roof–beam method. The development of subway construction has gradually become one of the themes of urban development. Finding ways to build subway stations quickly, economically, and safely has gradually become the focus of attention. The pipe–roof method is a method of constructing urban underground space, which is widely used throughout the world. However, there are many shortcomings in the existing pipe–roof method. This paper proposes the small pipe–roof–beam method that can save the construction period on the premise of ensuring safety, which is currently being applied to Shifu Road Station of Shenyang Metro Line 4 in China. In this paper, the law of surface settlement and pipe–roof deformation caused by excavation is obtained by combining the method of laboratory test and numerical simulation. The research can be the theoretical basis for the subsequent application of this method. The matching relationship between the pipe–roof and the beam will be investigated in the next study, which will provide guidance for the optimal design of subway stations. [ABSTRACT FROM AUTHOR]

The bearing stratum of high-rise and ultra-high-rise buildings in southwest China has inevitably faced moderately weathered red mudstone. It was a waste of the potential bearing stratum calculated according to the specification, as the bearing stratum obtained from laboratory and in situ tests was much higher than the values suggested by the specification. Rock mass surface deformation detection is of great significance in the safety management of a foundation project. Some correlation between surface deformation and failure characteristics may exist that could help to understand the bearing stratum of the moderately weathered red mudstone. This research was conducted to study the progressive failure characteristics of the moderately weathered red mudstone through surface deformation. In situ load, triaxial, and binocular visual technology were employed for data acquisition. The proposed conjecture was illustrated and verified by a group of experiments from three construction sites. Five stages could be described as the progressive failure of the moderately weathered red mudstone: compaction, elasticity, elastoplasticity, plasticity, and failure. Furthermore, the surface displacement increment fluctuates with the loading time and fades into the distance. Therefore, this research could provide a robust, practical application for analyzing the progressive failure of moderately weathered red mudstone. [ABSTRACT FROM AUTHOR]

To study the influencing factors of surface subsidence by the backfilling of a mined-out area on thick and loose loess layers, a mechanical model on synergic deformation and surface subsidence is constructed taking the case of a sedimentary bauxite mine in China's Shanxi province as an example. Backfill state is classified based on the position of the protective roof and the backfill body. The influence of different filling ratios, the thickness of overlying loess, and the stope span on surface subsidence are quantitatively analyzed. The results reveal that: (1) When the thickness of the overlying loess Hg and the stope span s are constant, surface subsidence ωmax is negatively correlated with the filling ratio η. When η reaches the state III inflection point, the amplitude of surface subsidence ωmax declines sharply and eventually tends to be stable. (2) When the filling ratio η and stope span s are constant, surface subsidence ωmax is negatively correlated with the thickness of the overlying loess Hg, and the growth ratio decreases continuously. (3) When η and Hg are constant, surface subsidence ωmax is positively correlated with s, and the growth ratio increases continuously. In the end, the validity of the theoretical calculation is verified by numerical simulation and an engineering case example. [ABSTRACT FROM AUTHOR]

In China, gas and oil reserves are very scarce, but coal resources are abundant in the energy architecture, which decides that coal will remain the dominant energy source for a long time in the future. The accurate prediction of the size and extent of surface movement after coal seam mining is of great significance for the safe promotion of production activities in the mine area and the safety of people's lives and properties in the mine area. The surface movement deformation under thick loose seam conditions indicates the phenomenon of a large subsidence value and influence range. To predict the size and range of surface movement deformation under thick loose layer conditions accurately, a hyperbolic secant model is constructed based on the hyperbolic secant function. For high nonlinearity of the model parameters, the adaptive step fruit fly algorithm (ASFOA) is introduced into the process of solving the model parameters. Simulation experiments are conducted in three aspects: monitoring point antideficiency, antigross error, and parameter stability. The simulation results show that the ASFOA algorithm achieves high accuracy in finding the parameters of the hyperbolic secant model. The hyperbolic secant model was applied to the 11111 working face under the mining conditions of thick loose layer geology in the Huainan mine. The engineering application results indicate that the hyperbolic secant model performs well on the prediction of surface movement deformation under thick loose layer conditions. [ABSTRACT FROM AUTHOR]

The lack of resources on islands leads to their extremely rapid development, and this can result in frequent geological disasters involving island subsidence. These disasters not only destroy the ecological environment and landscape of islands but also pose massive threats to the safety of residents' lives and property and can even affect the country's maritime rights and interests. To meet the demands of island stability and safety monitoring, in this study, we propose a large-area, full-coverage deformation monitoring method using InSAR technology to assess island subsidence based on a comprehensive analysis of conventional monitoring techniques. The working principle and unique advantages of InSAR data are introduced, and the SBAS InSAR key interpretation processing flow are described in detail. The GPU-assisted InSAR processing method is used to improve the processing efficiency. The monitoring results showed that the southern island group of the Miaodao Archipelago was relatively stable overall, with an annual average deformation rate of 3 mm. Only a few areas experienced large-magnitude surface deformation, and the maximum annual deformation magnitude was 45 mm. The time series deformation results of the characteristic points of the five inhabited islands in the southern island group showed that the subsidence trends of the two selected points on Beichangshan Island (P1 and P2) were slowly declining. The P3 point on Nanchangshan Island experienced a large deformation, while the P4 point experienced a relatively small deformation. The selected points (P5, P6 and P7) on Miaodao Island, Xiaoheishan Island and Daheishan Island were stable during the monitoring period. InSAR data can be used to accurately identify the millimetre-scale microdeformations experienced by island groups, thus demonstrating the high-precision deformation monitoring capability of these data. In addition, the accuracy of these data can meet the needs of island and archipelago subsidence monitoring, and the proposed method is an effective means to monitor the spatial deformation of island targets. This study is conducive to further enriching and improving island stability and safety monitoring technology systems in China and to providing data and technical support for identifying and mastering potential island risks, protecting and utilizing islands and preventing and reducing disasters. [ABSTRACT FROM AUTHOR]

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Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)