Interferometric Synthetic Aperture Radar Results Research Articles

Application of Sentinel-1 InSAR to monitor tailings dams and predict geotechnical instability: practical considerations based on case study insights

Tailings storage facilities (TSFs) impound mining waste behind dams to ensure public safety, but failure incidents have prompted calls for more robust monitoring programs. Satellite-based interferometric synthetic aperture radar (InSAR) has grown in popularity due to its ability to remotely detect millimeter-scale displacements in most urban and some natural terrains. However, there remains a limited understanding of whether InSAR can be as accurate or representative as on-the-ground instruments, whether failures can be predicted in advance using InSAR, and what variables govern the quality and reliability of InSAR results. To address these gaps, we analyze open-source, medium-resolution Sentinel-1 data to undertake a ground-truth assessment at a test site and a forensic analysis of five failure cases. We use a commercial software with an automated Persistent Scatterer (PS) workflow (SARScape Analytics) for all case study sites except one and a proprietary algorithm (SqueeSAR) with a dual PS and Distributed Scatterer (DS) algorithm for the ground-truth site and one forensic case. The main goal is to deliver practical insights regarding the influence of algorithm/satellite selection, environmental conditions, site activity, coherence thresholds, satellite-dam geometry, and failure modes. We conclude that Sentinel-1 InSAR can serve as a hazard-screening tool to help guide where to undertake targeted investigations; however, most potential failure modes may not exhibit InSAR-detectable accelerations that could assist with time-of-failure prediction in real time. As such, long-term monitoring programs should ideally be integrated with a combination of remote sensing and field instrumentation to best support engineering practice and judgment.

The Detection and Control Factor Analysis of Active Landslides in Guizhou Province, China, Using Sentinel-1 SAR Imagery

Catastrophic landslides occur frequently in Guizhou Province, China, and the landslides in this area have special geomorphological, geological, and anthropogenic features. In order to detect and explore the distribution pattern and control factors of active landslides in Guizhou, firstly, a total of 693 active landslides throughout Guizhou Province were mapped based on the deformation rate, which was obtained by spatiotemporal filtering and Intermittent Small Baseline Subset (ISBAS) Interferometric Synthetic Aperture Radar (InSAR) techniques. Then, the relationships between the detected landslides and elevation, aspect, slope gradient, and stratigraphic lithology were analysed. Moreover, it was found that the landslides were mainly concentrated in three stratigraphic combinations, that is T1f~P2l−d, T1f~T1yn, and T2g~T1yn. Thereafter, the correlation coefficients between the landslide density and elevation and distance to the stratigraphic boundary were 0.54 and −0.19, indicating that the distribution of landslides was significantly controlled by the elevation and the boundary of specific stratigraphic combinations. Finally, we chose a typical landslide to explore how landslide development was controlled by the combined effects of elevation and stratigraphy by using ascending and descending InSAR results. We revealed that landslides occurred primarily in areas with a steep slope and a stratigraphy characterized by mudstone and sandstone.

Underground Gas Storage Monitoring Using Free and Open Source InSAR Data: A Case Study from Yela (Spain)

Gas consumption is subject to large seasonal fluctuations between the summer season (period with lower request) and the winter season (time with increased consumer demand). Underground gas storage applications (UGS) help to ensure a steady and reliable supply of natural gas, even during periods of peak demand, smoothing price fluctuations and providing a means of balancing the supply and demand of natural gas on a daily, weekly, or seasonal basis. However, UGS activities can induce vertical ground displacement, which is usually strictly associated with the injection and withdrawal of gas into/from the reservoir. It is necessary to carefully monitor and manage the potential impact of UGS activities on the subsurface and surface to ensure the stability and safety of the local environment. The Interferometric Synthetic Aperture Radar (InSAR) technique can provide a wide range of high-precision information on seasonal surface deformation associated with UGS activities useful for increasing the amount of information on ground deformation monitoring. This study introduces a unique and replicable approach to investigating freely available ground movement data for a fractured aquifer reservoir located in the Madrid Basin (Guadalajara, Spain), which is currently employed for seasonal underground gas storage applications. Notably, this study gives a comprehensive comparison of InSAR results of UGS activity in a deep aquifer, leveraging data that are entirely open-source and easily accessible. The Yela UGS project exploits a carbonate reservoir (dolomite) managed, since 2012, by Enagás, the Spanish main Transmission System Operator (TSO). InSAR data from 2015 to 2021 provided a full and coherent ground deformation pattern of the area. Based on this data, a fully integrated volumetric variation model was developed, elucidating the effects of gas storage activity. A significant correlation between the periodic injection/withdrawal rates of natural gas and InSAR ground deformation over time was identified.

Using InSAR and GPR Techniques to Detect Subsidence: Application to the Coastal Area of “A Xunqueira” (NW Spain)

Climate change represents an important cause of subsidence, especially in coastal cities affected by changes in surface water level and water table. This paper presents a complementary study of Interferometric Synthetic Aperture Radar (InSAR) and Ground Penetrating Radar (GPR) for the early detection of subsidence and sinkhole phenomena. The methodology was applied to a coastal urban area in Galicia, northwest Spain (humid region), showing apparent signs of subsidence and building settlement during the last two years. Two different InSAR methods are compared for the period from June 2021 to March 2022: PSI (Persistent Scatterer Interferometry) and SBAS (Small Baseline Subsets), and the average deformation velocities obtained resulted in −3.0 mm/yr and −4.1 mm/yr, respectively. Additional GPR data were collected in January 2022 to validate the InSAR results, which detected subsidence in agreement with the persistent scatters obtained from the PSI method. This is crucial information to plan preventive maintenance.

Genetic algorithm-based parameter inversion and pipeline subsidence prediction

To invert mine subsidence parameters and predict the timing of associated risk to underground pipelines passing through mining areas with incoherent subsidence information, this study proposes a model based on combining the advantages of interferometric synthetic aperture radar (InSAR) technology, the probability integral method (PIM), segmented Knothe time function, and genetic algorithm. Firstly, InSAR technology is used to analyze a time series of surface deformation in a mining area, circle the range of large-gradient deformation, and distinguish the subsidence edge from the subsidence center. In the case of the subsidence edge (small-scale deformation), InSAR results are retained, whereas in the case of the subsidence center (large-scale deformation), subsidence parameters, such as the subsidence coefficient and influence radius, are obtained via the genetic algorithm. The subsidence of the working face in the mining area is determined by combining InSAR information and the PIM parameter inversion-based basin model. This allows us to obtain continuous surface subsidence information, study surface subsidence trends over time, and predict future pipeline subsidence. The researchers subsequently test the efficacy of this model in the Qinchi mining area in Shanxi Province, China. Sentinel-1A images were used as the data source, combine the PIM and segmentation time function, and use the genetic algorithm to obtain the subsidence mining parameters. The inversion results show that the subsidence coefficient is 0.5917 (with an error of 2%), and the main influence angle tangent value is 1.927 (with an error of 2.18%), indicating high inversion accuracy. Based on this model, the study predict that subsidence in the Qinchi mining area will threaten the structural integrity and operation of the intersecting pipeline by November 2025.

Permafrost Stability Mapping on the Tibetan Plateau by Integrating Time-Series InSAR and the Random Forest Method

The ground deformation rate is an important index for evaluating the stability and degradation of permafrost. Due to limited accessibility, in-situ measurement of the ground deformation of permafrost areas on the Tibetan Plateau is a challenge. Thus, the technique of time-series interferometric synthetic aperture radar (InSAR) is often adopted for measuring the ground deformation rate of the permafrost area, the effectiveness of which is, however, degraded in areas with geometric distortions in synthetic aperture radar (SAR) images. In this study, a method that integrates InSAR and the random forest method is proposed for an improved permafrost stability mapping on the Tibetan Plateau; to demonstrate the application of the proposed method, the permafrost stability mapping in a small area located in the central region of the Tibetan Plateau is studied. First, the ground deformation rate in the concerned area is studied with InSAR, in which 67 Sentinel-1 scenes taken in the period from 2014 to 2020 are collected and analyzed. Second, the relationship between the environmental factors (i.e., topography, land cover, land surface temperature, and distance to road) and the permafrost stability is mapped with the random forest method based on the high-quality data extracted from the initial InSAR analysis. Third, the permafrost stability in the whole study area is mapped with the trained random forest model, and the issue of data scarcity in areas where the terrain visibility of SAR images is poor or InSAR results are not available in permafrost stability mapping can be overcome. Comparative analyses demonstrate that the integration of the InSAR and the random forest method yields a more effective permafrost stability mapping compared with the sole application of InSAR analysis.

Substantial carbon sequestration by peatlands in temperate areas revealed by InSAR

Peatlands are unique ecosystems that contain massive amounts of carbon. These ecosystems are incredibly vulnerable to human disturbance and climate change. This may cause the peatland carbon sink to shift to a carbon source. A change in the carbon storage of peatlands may result in surface deformation. This research uses the interferometric synthetic aperture radar (InSAR) technique to measure the deformation of the peatland’s surface in south Sweden in response to the seasonal and extreme weather conditions in recent years, including the unprecedented severe drought in the summer of 2018. The deformation map of the study area is generated through a time-series analysis of InSAR from June 2017 to November 2020. Monitoring the peatland areas in this region is very important as agricultural and human activities have already caused many peatlands to disappear. This further emphasizes the importance of preserving the remaining peat sites in this region. Based on the InSAR results, a method for calculating the carbon flux of the peat areas is proposed, which can be utilized as a regular monitoring approach for other remote areas. Despite the severe drought in the summer of 2018, our findings reveal a significant uplift in most of the investigated peat areas during the study period. Based on our estimations, 86% of the peatlands in the study area experienced an uplift corresponding to about 47 000 tons of carbon uptake per year. In comparison, the remaining 14% showed either subsidence or stable conditions corresponding to about 2300 tons of carbon emission per year during the study period. This emphasizes the importance of InSAR as an efficient and accurate technique to monitor the deformation rate of peatlands, which have a vital role in the global carbon cycle.

Iceland Kinematics From InSAR

AbstractLarge‐scale ground deformation in Iceland is dominated by extensional plate‐boundary deformation, where the Mid‐Atlantic Ridge crosses the island, and by uplift due to glacial isostatic adjustment (GIA) from thinning and retreat of glaciers. While this deformation is mostly steady over multiple years, it is modulated by smaller‐scale transient deformation associated with, for example, earthquakes, volcanic unrest, and geothermal exploitation. Here, we combine countrywide Sentinel‐1 interferometric synthetic aperture radar (InSAR) data (from six tracks) from 2015 to 2021 with continuous Global Navigation Satellite System observations to produce time series of displacements across Iceland. The InSAR results were improved in a two‐step tropospheric mitigation procedure, using (a) global atmospheric models to reduce long‐wavelength and topography‐correlated tropospheric signals, and (b) modeling of the stochastic properties of the residual troposphere. Our results significantly improve upon earlier countrywide InSAR results, which were based on InSAR stacking, as we use more data, better data weighting, and advanced InSAR corrections to produce time series of ground displacements instead of just velocities. We fuse the three ascending and three descending track results to estimate maps of East and Up velocities, which clearly show the large‐scale extension and GIA deformation. Using revised plate‐spreading and GIA models, based on these new ground velocity maps, we remove the large‐scale and steady deformation from the InSAR time series and analyze the remaining transient deformations. Our results demonstrate the importance of (a) mitigating InSAR tropospheric signals over Iceland and of (b) solving for time series of deformation, not just velocities, as multiple transient deformation processes are present.

Determination of periodic deformation from InSAR results using the FFT time series analysis method in Gediz Graben.

Permanent Scatterers (PS) point velocities obtained by the interferometric synthetic aperture radar (InSAR) method are generally determined using the linear regression model, which ignores periodic and seasonal effects. In this study, software was developed that can detect periodic effects by applying fast Fourier transformation (FFT) time series analysis to InSAR results. Using the FFT time series analysis, the periodic components of the surface movements at the PS points were determined, and then the annual velocity values free from periodic effects were obtained. The study area was chosen as the Gediz Graben, a tectonically active region where aseismic surface deformations have been observed in recent years. As a result, using the developed method, seasonal effects were successfully determined with the InSAR method at the PS points in the study area with a period of 384days and an average amplitude of 19mm. In addition, groundwater level changes of a water well in the region were modeled, and 0.93 correlation coefficient values were calculated between seasonal InSAR displacement values and water level changes. Thus, using the developed methodology, the relationship between the tectonic movement in the Gediz Graben in Turkey and the seasonal movements and the change in the groundwater level was determined.

Deformation Monitoring and Trend Analysis of Reservoir Bank Landslides by Combining Time-Series InSAR and Hurst Index

Landslides along the Three Gorges Reservoir in China pose a threat to coastal residents and waterway safety. To reduce false positive misjudgments caused by a sudden local change in the landslide deformation curve, in this paper, we propose an effective method for predicting the deformation trend of reservoir bank landslides. We take reservoir bank landslides in the Wanzhou District of the Three Gorges Reservoir area as the research object. The Time-Series Interferometric Synthetic Aperture Radar (InSAR) method and 62 Sentinel-1A images from 2018 to 2022 were selected for landslide deformation monitoring, and the Hurst index was calculated to characterize the deformation trend. Furthermore, we propose a method for predicting the deformation trend based on the statistical distribution of deformation rates and the physical significance of the Hurst index. After the field survey and Global Positioning System (GPS) verification, the Time-Series InSAR results are shown to be reliable. We take the Sifangbei landslide as a representative case to analyze the validation results. It is found that the determined Sifangbei landslide deformation trend is consistent with the conclusions for the region. In addition, the deformation trend of a reservoir bank slope has obvious spatial and temporal differences. Changes in the reservoir water level and concentrated rainfall play roles similar to those of catalysts. The proposed method, involving the combination of Time-Series InSAR and the Hurst index, can effectively monitor deformation and predict the stability trend of reservoir bank landslides. The presented research results provide new ideas and solutions for landslide prevention and risk mitigation in reservoir areas.

Ground Investigations and Detection and Monitoring of Landslides Using SAR Interferometry in Gangtok, Sikkim Himalaya

The Himalayan state of Sikkim is prone to some of the world’s largest landslides, which have caused catastrophic damage to lives, properties, and infrastructures in the region. The settlements along the steep valley sides are particularly subject to frequent rainfall-triggered landslide events during the monsoon season. The region has also experienced smaller rock slope failures (RSF) after the 2011 Sikkim earthquake. The surface displacement field is a critical observable for determining landslide depth and constraining failure mechanisms to develop effective mitigation techniques that minimise landslide damage. In the present study, the persistent scatterers InSAR (PSI) method is employed to process the series of Sentinel 1-A/B synthetic aperture radar (SAR) images acquired between 2015 and 2021 along ascending and descending orbits for the selected areas in Gangtok, Sikkim, to detect potentially active, landslide-prone areas. InSAR-derived ground surface displacements and their spatio-temporal evolutions are combined with field investigations to better understand the state of activity and landslide risk assessment. Field investigations confirm the ongoing ground surface displacements revealed by the InSAR results. Some urban areas have been completely abandoned due to the structural damage to residential housing, schools, and office buildings caused by displacement. This paper relates the geotechnical investigations carried out on the ground to the data obtained through interferometric synthetic aperture radar (InSAR), focusing on the triggering mechanisms. A strong correlation between seasonal rainfall and landslide acceleration, as well as predisposing geological-structural setting, suggest a causative mechanism of the landslides.

A preliminary analysis of the mining-induced rock movement characteristics in the Xinli deposit of the Sanshandao gold mine

Commensurate with economic globalization, the demand for mineral resources is increasing. With increased mining activity, problems related to ground subsidence and rock movement are becoming increasingly prominent, even affecting mining production activities. However, the physical mechanisms behind the ground subsidence phenomenon have been poorly studied, especially for metal mines with a steep dip. This paper applies the Interferometric Synthetic Aperture Radar (InSAR) technique and the numerical simulation method to deduce the characteristics of rock movement in the Xinli deposit of the steeply inclined Sanshandao gold mine. The InSAR results indicate that more subsidence has occurred in the southern part of the Xinli Village coastline area than in the northern part. This is also supported by the numerical simulation results obtained by the fast Lagrangian analysis of continua in three dimensions (FLAC3D). Notably, the range of ground subsidence obtained by numerical simulation shows an obvious asymmetry. The monitoring data of the No. 55 prospecting profile offer a plausible explanation for this, as the surrounding rock of the fault’s hanging wall has a wider range of rock movements. Furthermore, the sublevels of the No. 55 prospecting profile at different depths show different rock movement characteristics, and a logistic function can be well applied to the right part of the settlement curve; the parameter “a” in the function formula is very close to the maximum subsidence value for each sublevel. We defined the ratio “r” to measure the difference between the maximum subsidence value and the corresponding parameter “a” and found this value to be positively correlated with the fractal dimension value of deeper sublevels (−320 m, −400 m, −480 m, and −600 m) and negatively correlated with the fractal dimension value of lower sublevels (−200 m and −240 m).

Joint Use of Optical and Radar Remote Sensing Data for Characterizing the 2020 Aniangzhai Landslide Post-Failure Displacement

The ancient Aniangzhai (ANZ) landslide in Danba County, Sichuan Province of southwest China was reactivated after a series of complex hazard events that occurred in June 2020. Since then, and until June 2021, emergency engineering work was carried out to prevent the further failure of the reactivated landslide. This study investigates the potential of joint use of time series Interferometric Synthetic Aperture Radar (InSAR) and optical pixel offset tracking (POT) to assess deformation characteristic and spatial-temporal evolution of the reactivated ANZ landslide during the post-failure stage. The relationships between sun illumination differences, temporal baseline of correlation pairs and the uncertainties were deeply explored. Surface deformation along the line-of-sight (LoS) direction was retrieved by the time series InSAR processing with the two Sentinel-1 datasets, revealing a maximum deformation rate up to 190 mm/year. The large horizontal displacements were also detected from the POT processing using 11 optical images acquired by the PlanetScope satellite (3 m spatial resolution), showing a significant increase of about 24 m between 24 June 2020 and 11 June 2021. The time series analysis from the InSAR and optical POT results revealed that the reactivated ANZ landslide body is gradually slowing down to a steady deformation status since its occurrence in August 2020, indicating the effectiveness of engineering work on the prevention of further landslide. A slight acceleration was detected from both InSAR and optical POT time series analysis between May 2021 and June 2021, which could be caused by the increased rainfall in May 2021.

Landslide susceptibility evaluation integrating weight of evidence model and InSAR results, west of Hubei Province, China

Landslides are common geological hazards that take a heavy toll on human life and infrastructure every year, making it crucial to identify potential landslides. Landslide susceptibility (LS) mapping evaluates landslide proneness with the help of static data (e.g., topography, geology, and hydrology) that hardly change over decades; whereas the ground deformation map (GDM) produced by Interferometric Synthetic Aperture Radar (InSAR) works as a powerful reinforcement for determining landslide threats. The integration of the two could prompt the evaluation of the LS, yet the existing joint approaches exhibit certain defects. Therefore, a novel LS evaluation approach integrating the weight of evidence (WOE) model and InSAR results was proposed in this study. First, the GDM of the study area was obtained through InSAR process; meanwhile, an initial LS map was produced using the WOE model; subsequently, the LS map was coupled with GDM to develop a refined zoning and identification of landslide hazards. The proposed method was applied in Enshi, China, and achieved a higher AUC of 0.869. In addition, the accuracy of the susceptibility level of geological hazards found during field survey of the study area was improved, indicating that the LS map generated using the proposed method is more sensitive to landslide hazards and produces more accurate results.

Potential landslides identification based on temporal and spatial filtering of SBAS-InSAR results

Interferometric Synthetic Aperture Radar (InSAR) is an important method for acquiring surface deformation. Considering the difficulty of the identification work, the identification of landslides needs to be combined with the context of the pregnant disaster and the precipitating conditions. To identify potential landslides, we applied spatial and temporal filtering to the InSAR results, which consists of rainfall and landslide susceptibility mapping. In this paper, taking the Badong Ecological Barrier Zone of the Three Gorges reservoir area as the study area, the deformation aggregation areas in the study area were obtained by applying Small Baseline Subset InSAR (SBAS-InSAR) technology and spatial statistical analysis. We screened deformation aggregation areas by combining the susceptibility map and the correlation analysis of rainfall and deformation. Field verification and investigation were conducted on the suspected deformation areas, and 11 landslides were found to have signs of deformation, two of them are newly discovered landslides. In addition, we selected one of the landslides, the Songjiawuchang landslide, and compared the InSAR results with the GPS accumulated displacement to verify the reliability of the results. This research demonstrated the feasibility of combining InSAR results with spatial susceptibility maps and monthly rainfall factors for landslides identification methods. Key policy highlights Applied Spatial filtering and temporal filtering on the InSAR results. Evaluated in conjunction with geological hazards themselves. Landslide identification accuracy significantly improved.

Integrated coastal subsidence analysis using InSAR, LiDAR, and land cover data

Land subsidence is an important cause of relative sea-level rise along the Gulf Coast. There is a lack of effective monitoring of coastal subsidence with high accuracy and high spatial resolution for improving coastal risk assessment and mitigation. This study is the first attempt to integrate satellite interferometric synthetic aperture radar (InSAR) and airborne light detection and ranging (LiDAR) methods to investigate the spatiotemporal pattern of coastal subsidence. The study area is around Eagle Point, Texas, a region known for its fast rate of relative sea-level rise in recent decades. From 2006 to 2011, the line-of-sight velocities were up to −33 mm/year based on ascending ALOS-1 PALSAR-1 images. From 2016 to 2021, the vertical velocities were up to −34 mm/year based on ascending and descending Sentinel-1 images. Additional details of the subsidence pattern were revealed by incorporating the surface difference derived from 1-m airborne LiDAR results. Comparisons of the InSAR-derived velocities from image time series and the LiDAR-derived surface changes from time-lapsed observations were conducted at different spatial levels with linkages to land cover patterns and topography. The results showed that local subsidence rates could vary significantly below the spatial resolution of InSAR results, indicating a valuable role of airborne LiDAR results in extending InSAR results to parcel and building levels and explaining subpixel uncertainties. Also, subsidence appeared to be stronger in vegetated areas than in developed areas and negatively correlated with surface imperviousness. The magnitude of subsidence was not correlated with elevation along selected transect lines. Overall, this study demonstrated the benefits of combining InSAR results with other geospatial datasets to characterize coastal subsidence. In particular, the high vertical accuracy of InSAR results and the high spatial resolution of airborne LiDAR results could be complementary, highlighting the necessity of multi-resolution data fusion to support studies on coastal flood vulnerability, infrastructure reliability, and erosion control.

Landslide Detection and Mapping Based on SBAS-InSAR and PS-InSAR: A Case Study in Gongjue County, Tibet, China

The rock mass along the Jinsha River is relatively broken under complex geological action. Many ancient landslides were distributed along the Jinsha River in Gongjue County, which is very dangerous under the action of gravity, tectonic stress and river erosion. Efficient and accurate identification and monitoring of landslides is important for disaster monitoring and early warning. Interferometric synthetic aperture radar (InSAR) technology has been proved to be an effective technology for landslide hazard identification and mapping. However, great uncertainty inevitably exists due to the single deformation observation method, resulting in wrong judgment during the process of landslide detection. Therefore, to address the uncertainties arising from single observations, a cross-comparison method is put forward using SBAS-InSAR (small baseline subset InSAR) and PS-InSAR (permanent scatterers InSAR) technology. Comparative analysis of the spatial complementarity of interference points and temporal deformation refined the deformation characteristics and verified the reliability of the InSAR results, aiding in the comprehensive identification and further mapping of landslides. Landslides along the Jinsha River in Gongjue County were studied in this paper. Firstly, 14 landslides with a total area of 20 km2 were identified by using two time-series InSAR methods. Then, the deformation characteristics of these landslides were validated by UAV (unmanned aerial vehicle) images, multiresource remote sensing data and field investigation. Further, the precipitation data were introduced to analyze the temporal deformation characteristics of two large landslides. Lastly, the influence of fault activity on landslide formation is further discussed. Our results demonstrate that the cross-comparison of the time-series InSAR method can effectively verify the accuracy of landslide identification.

Evolution Assessment of Mining Subsidence Characteristics Using SBAS and PS Interferometry in Sanshandao Gold Mine, China

Ground subsidence is a common geological phenomenon occurring in mining areas. As an important Chinese gold mine, Sanshandao Gold Mine has a mining history of 25 years, with remarkable ground subsidence deformation. Mining development, life security, property security and ecological protection all require comprehension of the ground subsidence characteristics and evolution in the mining area. In this study, the mining subsidence phenomenon of the Sanshandao Gold Mine was investigated and analyzed based on Persistent Scatterer Interferometry (PSI) and small baseline subset (SBAS). The SAR (synthetic aperture radar) images covering the study area were acquired by the Sentinel-1A satellite between 2018 and 2021; 54 images (between 22 February 2018 and 25 May 2021) were processed using the PSI technique and 24 images (between 11 April 2018 and 12 July 2021) were processed using the SBAS technique. In addition, GACOS (generic atmospheric correction online service) data were adopted to eliminate the atmospheric error in both kinds of data processing. The interferometric synthetic aperture radar (InSAR) results showed a basically consistent subsidence area and a similar subsidence pattern. Both InSAR results indicated that the maximum LOS (line of sight) subsidence velocity is about 49 mm/year. The main subsidence zone is situated in the main mining area, extending in the northwest and southeast directions. According to the subsidence displacement of several representative sites in the mining area, we found that the PSI result has a higher subsidence displacement value compared to the SBAS result. Mining activities were accompanied by ground subsidence in the mining area: the ground subsidence phenomenon is exacerbated by the increasing mining quantity. Temporally, the mining subsidence lags behind the increase in mining quantity by about three months. In summary, the mining area has varying degrees of ground subsidence, monitored by two reliable time-series InSAR techniques. Further study of the subsidence mechanism is necessary to forecast ground subsidence and instruct mining activities.

Slow surface subsidence and its impact on shallow loess landslides in a coal mining area

Surface subsidence caused by underground coal mining affects the hillslope stability conditions. However, few studies have focused on the coupling relationship between slow surface subsidence and landslide occurrences. A detailed landslide and fissure inventory in a coal mining area in Shaanxi Province, China, was produced based on interpretation of multitemporal satellite images and unmanned aerial vehicle (UAV) surveys. We used the interferometric synthetic aperture radar (InSAR) technique and landslide and fissure spatiotemporal statistics to investigate the spreading process of the slow subsidence caused by underground mining and examined its impact on the occurrence of shallow landslides. The InSAR results indicate that the actual extent of the subsidence zone is larger than the range of underground mining, which formed a subsidence basin along the coal mining panels. The subsidence curves go through initial, accelerative, and slow subsidence stages and characterized by S-shaped, which can be adequately fitted with logistic regression. Moreover, subsidence does not cease after the end of coal exploitation. Logistic models predicted that the duration of residual subsidence reached about 2–3 years. Subsidence significantly increased the likelihood of landslide occurrences. The spatial pattern of landslides is associated with the actual coal mining. We also investigated the clustering phenomenon of landslides and fissures under the impacts of subsidence. The frequency ratio of landslides and fissures increased with the cumulative subsidence. Finally, we propose a schematic view for landslides caused by coal mining and precipitation. This study will be helpful for elucidating the spatial–temporal evolution of slow subsidence and its impact on loess landslides in coal mining area.

Strain Partitioning and Interseismic Fault Behavior Along the Caribbean‐South American Transform Plate Boundary

AbstractWe combine Global Positioning System and Interferometric Synthetic Aperture Radar (InSAR) data to characterize the interseismic behavior (i.e., locked or creeping), and strain partitioning for the faults along the Caribbean‐South American transform plate boundary. Interseismic strain is distributed mainly on three faults, the San Sebastian, El Pilar, and Central Range faults, but partitioning occurs across multiple faults in the west (San Sebastian and La Victoria faults) and east (Sub‐Tobago Terrane, Central Range, and South Coast faults). In northern Venezuela, slip is partitioned on the San Sebastian (16.4 ± 1.7 mm/yr) and La Victoria (4.3 ± 0.9 mm/yr) faults. In north‐eastern Venezuela, the El Pilar fault accommodates slip at a rate of 18.6 ± 1.8 mm/yr. In Trinidad and Tobago, slip is partitioned between the Sub‐Tobago Terrane (3.0 ± 0.1 mm/yr), Central Range (14.5 ± 2.0 mm/yr), and South Coast (3.0 ± 0.1 mm/yr) faults. The La Victoria, San Sebastian, the western El Pilar segment, and Sub‐Tobago Terrane faults are locked to depths of 16.2 ± 4.0 km, 7.7 ± 5.2 km, 6.7 ± 2.8 km, and 8.0 ± 0.2 km, respectively. The eastern segment of the El Pilar, the Central Range, and the South Coast faults all creep. Our new InSAR results indicate that the entire Central Range Fault is creeping. The locked western segment of this transform plate boundary is capable of producing a Mw 8 earthquake, which is a significant finding regarding seismic hazard and risk.