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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]

The collapse of open-pit coal mine slopes is a kind of severe geological hazard that may cause resource waste, economic loss, and casualties. On 22 February 2023, a large-scale collapse occurred at the Xinjing Open-Pit Mine in Inner Mongolia, China, leading to the loss of 53 lives. Thus, monitoring of the slope stability is important for preventing similar potential damage. It is difficult to fully obtain the temporal and spatial information of the whole mining area using conventional ground monitoring technologies. Therefore, in this study, multi-source remote sensing methods, combined with local geological conditions, are employed to monitor the open-pit mine and analyze the causes of the accident. Firstly, based on GF-2 data, remote sensing interpretation methods are used to locate and analyze the collapse area. The results indicate that high-resolution remote sensing can delineate the collapse boundary, supporting the post-disaster rescue. Subsequently, multi-temporal Radarsat-2 and Sentinel-1A satellite data, covering the period from mining to collapse, are integrated with D-InSAR and DS-InSAR technologies to monitor the deformation of both the collapse areas and the potential risk to dump slopes. The D-InSAR result suggests that high-intensity open-pit mining may be the dominant factor affecting deformation. Furthermore, the boundary between the collapse trailing edge and the non-collapse area could be found in the DS-InSAR result. Moreover, various data sources, including DEM and geological data, are combined to analyze the causes and trends of the deformation. The results suggest that the dump slopes are stable. Meanwhile, the deformation trends of the collapse slope indicate that there may be faults or joint surfaces of the collapse trailing edge boundary. The slope angle exceeding the designed value during the mining is the main cause of the collapse. In addition, the thawing of soil moisture caused by the increase in temperature and the reduction in the mechanical properties of the rock and soil due to underground voids and coal fires also contributed to the accident. This study demonstrates that multi-source remote sensing technologies can quickly and accurately identify potential high-risk areas, which is of great significance for pre-disaster warning and post-disaster rescue. [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]

Underground coal mining will inevitably cause serious ground deformation, and therefore, preventive mining-induced deformation analysis (MIDA) is of great importance in assisting mining planning and decision-making. Current web-based Geographic Information System (webGIS)-based applications usually use 2D GIS data and lack a holistic framework. This study presents a multi-scalar oblique photogrammetry-supported unified 3D webGIS framework for MIDA applications to fill this gap. The developed web platform uses multiple open-source JavaScript libraries, and the prototype system provides user-friendly interfaces for GIS data collecting and corresponding database establishment, geo-visualization and query, dynamic prediction, and spatial overlapping analysis within the same framework. The proposed framework was tested and evaluated in the Qianyingzi mining area in eastern China. The results demonstrated that multi-scalar oblique photogrammetry balances data quality and acquisition efficiency and provides a good source of GIS datasets, and the web-based platform has a good absolute and relative spatial accuracy verified by two types of validation data. Practical application results proved the feasibility and reliability of the system. The developed web-based MIDA prototype system attains an appealing performance and can be easily extended to similar geoscience applications. [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.)

The Xiaolangdi Basin of the Yellow River, located between Mengjin County and Jiyuan City in Henan Province, is composed of a reservoir, a barrage dam, flood discharge buildings, and a water diversion and power generation system, among which, the Xiaolangdi project is the only control project in the lower reaches of the Yellow River that has a large storage capacity. In this study, distributed scatterers InSAR (DS-InSAR) deformation analysis was used to process 27 images of ESA Sentinel-1A data for the period between September 10, 2018, and July 19, 2019. Using the generalized likelihood ratio test (GLRT) to select the statistical homogeneous pixels (SHP) and the eigenvalue decomposition method to optimize the interference phase, the time series surface deformation of the study area was obtained. The results showed that the maximum deformation rate in the study area was − 40.71 mm/year, the maximum deformation rate of the Xiaolangdi project was − 10.09 mm/year, and the larger deformation rates in the area around the Xiaolangdi Reservoir were mostly within the range − 35 to − 20 mm/year. Furthermore, small baseline subset (SBAS) InSAR and DS-InSAR are used for verification and analysis, and the monitoring results have high consistency. Therefore, to sum up, the time series deformation of low coherence areas may be monitored using DS-InSAR. [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.)

• 3D deformation monitoring of surface subsidence caused by underground mining in mining areas. • Local Flat Point Extraction (LFPE) algorithm based on point cloud features to calculate accurate subsidence. • DCT transform subsidence model denoising. • Sub-pixel correlation; horizontal displacement acquisition. • Determining the potential of UAV LiDAR technology for monitoring 3D deformation. Western China is the world's major coal-producing area, accounting for 1/3 of global coal production. Large-scale underground coal mining has led to serious ground deformation that has unique spatial and temporal characteristics. However, there are obvious engineering limitations to using GNSS, InSAR, and other common measurement techniques for monitoring mining subsidence. In recent years, researchers have attempted to use UAV LiDAR to monitor subsidence in mining areas. Point clouds are obtained through periodic ground scanning. Surface subsidence information is extracted through the filtering, modeling, and superposition processes. Conventional point cloud processing usually produces subsidence models that are too noisy and only provide information on surface subsidence. This means that it is unable to capture the horizontal ground displacement accompanying subsidence in mining areas, which hinders the practical application of this technology. A local flat point extraction (LFPE) algorithm based on geomorphic features is proposed. The algorithm extracts flat surface point clouds from the scan data and calculates the precise subsidence value of the ground by superposition to facilitate deformation monitoring. The obtained subsidence volume is spatially interpolated based on the unique spatial distribution characteristics of the mining subsidence basin to generate the initial surface subsidence model. By denoising this model, we can obtain a fine surface subsidence model that avoids significant noise caused by non-ground point clouds participating in modeling and superposition in common processing methods. On this basis, we successfully extracted the horizontal displacement information accompanying subsidence by employing sub-pixel correlation using the surface feature images before and after subsidence. The proposed technical pathway was validated by applying it to a coal mining subsidence area in the Yushen mining area in western China. Results demonstrate that, compared to conventional treatments, the proposed subsidence modeling method using laser scanning point clouds improves monitoring accuracy by over 50% while also obtaining the necessary horizontal displacement information for engineering requirements. These findings confirm the efficiency and accuracy of the proposed method for acquiring 3D surface deformation in mining areas. [ABSTRACT FROM AUTHOR]

Understanding the characteristics of different human-induced coastal surface deformation will improve our understanding of recent temporal-spatial evolution trends of the coastal terrain, and help better predict the risks of coastal disasters. However, few surface deformation studies have focused on the distinction between different types of anthropogenic ground deformation. Based on Sentinel-1 Synthetic Aperture Radar (SAR) data, this study employs the hybrid multi-temporal Interferometric Synthetic Aperture Radar (InSAR) method to extract the surface deformation of Chaoshan Plain from 2015 to 2020, with a spatial resolution of 30 m × 30 m. A series of historical optical satellite images and groundwater extraction data are used to help distinguish different types of human activities that have induced surface deformation. The characteristics of ground deformation induced by different types of anthropogenic activities are explored in the space and time dimensions. Results show that InSAR ground deformation in the study area is mainly caused by three types of human activities: groundwater extraction, land reclamation, and construction. Groundwater extraction has impacted >50% of the regional surface deformation by area. The interannual variability of the surface deformation rate corresponds well to that of groundwater extraction, and the subsidence effect can last for more than five years with seasonal variability. The maximum surface subsidence rate in land reclamation areas reaches ~100 mm/year, with a linear decreasing trend against time. Without extra compaction, the reclamation area can continue to deform almost at the same rate for several years. The rapid increase of overlying loads caused by construction in the reclamation area has led to a sharp decrease in the deformation rate within 2–3 years after the completion of the construction. In areas absent of other human-induced deformation, construction activities are shown to cause surface subsidence of 10–20 mm/year in a relatively short period. In areas experiencing a combination of construction and groundwater extraction, land subsidence rates of >50 mm/year are observed. This study shows that the spatial and temporal analysis of the correlations between human activities and InSAR surface deformation is an effective way to attribute the driven factors of coastal plain deformation. • Human-induced land deformation can be interpreted by satellite time-series images. • Groundwater exploitation deformation shows the seasonal and interannual variation. • Deformation in reclaimed area largely due to surface loading and soil compaction • Construction complicates InSAR surface deformation patterns in tempo-spatially. [ABSTRACT FROM AUTHOR]

In response to the problem that the actual extent of coal mining impacts on the surface in thick loose layer mines significantly exceeds the theoretical predictions, based on the literature study, the form of influence of thick loose layer on the predicted parameters of the probability integral method is summarized and analyzed; taking into account the influence of the subsidence coefficient, the sine modification formula of the major influence radius and the logistic modification formula of the subsidence coefficient are established, respectively, and based on the characteristics of the major influence radius, a new subsidence basin demarcation point is proposed and a novel probability integral method segmental parameter modified prediction model is constructed. The simulated experiment and real data experiment results prove that the constructed probability integral method segmented parameter modified model can both reduce the convergence of surface subsidence basin edge better and take into account the predicted accuracy inside the subsidence basin. The research achievements provide scientific data support for disaster warning, pollution management, ecological restoration, and coordination between coal mining and surface city construction in thick loose layer mining areas., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Due to the rapid economic development and urban construction and the high exploitation rate of groundwater and geothermal resource, Jimo district existed a potential threat of surface deformation. To clarify the characteristics and causations of surface deformation, this study firstly used SBAS-InSAR (Small Baseline Subset-Interferometric Synthetic Aperture Radar) technology to analyze the surface defor-mation distribution in the whole research area. Then, three areas with different surface cover conditions were selected to analyze the causations of surface deformation. Lastly, taking central urban area as the key research area, surface deformation causations were analyzed in detail based on PS-InSAR (Persistent Scatter-Interferometric Synthetic Aperture Radar) technology. The study found that, in coastal mollisol area, farmland area, and hot spring area, the maximum subsidence velocity reached up to 46.8 mm/a, 24 mm/a, and 19.1 mm/a, respectively. The factors, including surface loading, precipitation, and the groundwater level, were the causations of surface deformation in different research areas. The trend of the surface deformation curve was consistent with that of the groundwater level curve in the central urban area, but the response time of surface deformation lagged behind the change of groundwater level by approximately 4 months., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Mass redistribution of the Earth causes variable loading that deforms the solid Earth. While most recent studies using geodetic techniques focus on regions (such as the Amazon basin and the Nepal Himalayas) with large seasonal deformation amplitudes on the order of 1-4 cm due to hydrologic loading, few such studies have been conducted on the regions where the seasonal deformation amplitude is half as large. Here, we use joint GPS and GRACE data to investigate the vertical deformation due to hydrologic loading in the North China Plain, where significant groundwater depletion has been reported. We found that the GPS- and GRACE-derived secular trends and seasonal signals are in good agreement, with an uplift magnitude of 1-2 mm/year and a correlation of 85.0%-98.5%, respectively. This uplift rate is consistent with groundwater depletion rate estimated from GRACE data and in-situ groundwater measurements from earlier report studies; whereas the seasonal hydrologic variation reflects human behavior of groundwater pumping for agriculture irrigation in spring, leading to less water storage in summer than that in the winter season. However, less than 20% of weighted root-mean-squared (WRMS) reductions were detected for all the selected GPS stations when GRACE-derived seasonal deformations were removed from detrended GPS height time series. This discrepancy is probably because the GRACE-derived seasonal signals are large-scale, while the GPS-derived signals are local point measurements. [ABSTRACT FROM AUTHOR]

The large earthquake measuring 7.1 on the Richter scale that occurred in Yushu County, Qinghai Province, China, on April 14, 2010, caused a huge loss of life and major damage to people's properties. Using three modal synthetic-aperture radar (SAR) datasets, wide-swath SAR, interferometric SAR and polarimetric SAR, the following studies were conducted: (1) From Radarsat-2 wide swath SAR data, the regional geological structures and lithologic distribution characteristics of the Yushu earthquake were analyzed. (2) Using advanced land observing satellite/phased array L-band interferometric SAR data, the coseismic deformation field of the Yushu earthquake was obtained, and the size and spatial distribution of deformation were studied combining with the result of regional geological background analysis. (3) From Radarsat-2 polarimetric SAR data, the H-α-ρ method was used to extract the spatial distribution of building collapse caused by the earthquake in the Yushu urban area, and the reasons for the severe earthquake damage to buildings are also discussed and assessed. The study results demonstrate the effectiveness and important potential of using multimodal SAR data for synergic analysis and assessment of earthquake disasters. [ABSTRACT FROM AUTHOR]