Surface Displacement Monitoring Research Articles

A stability evaluation method for deep-seated toppling in the upper Lancang river, Southwestern China

Deep-seated toppling in the upper reaches of the Lancang River, southwest China involves deformations exceeding 100 m in depth. The slope deformation is initiated by river downcutting and evolves distinctive characteristics with a depth of river incision. In this study, we propose a system for evaluating the stability of deep-seated toppled slopes in different evolutionary stages. This system contains identification criteria for each evolutionary stage and provides the corresponding stability evaluation methods. Based on the mechanical and kinematic analysis of slope blocks, the specific stage of slope movement can be identified in the field through outcrop mapping, in situ tests, surface displacement monitoring, and adit and borehole explorations. The stability evaluation methods are established based on the limiting equilibrium theory and the strain compatibility between the undisturbed zone and the toppled zone. Finally, several sample slopes in different evolution stages have been investigated to verify the applicability and accuracy of the proposed stability evaluation system. The results indicate that intense tectonic activity and rapid river incision lead to a maximum principal stress ratio exceeding 10 near the slope surface, thus triggering widespread toppling deformations along the river valley. When considering the losses of joint cohesion during the further rotation process, the safety factor of the slope drops by 7%–28%. The self-stabilization of toppling deformation can be recognized by the layer symmetry configuration after the free rotation of the deflected layers. Intensely toppled rock blocks mainly suffer sliding failures beyond the layer symmetry condition. The factor of safety of the K73 rockslide decreased from 1.17 to 0.87 by considering the development of the potential sliding surface and the toe-saturated zone.

An innovative approach to continuously monitor rail track surface displacement during freezing-thawing seasons

Large differential displacement as a result of freeze–thaw cycles (FTC) is a major issue affecting the safety and performance of railway tracks constructed in cold regions. Current track monitoring methods in winter are mainly based on visual inspection and manual measurements. The frequency of FTC is expected to increase under future climate and thus it is essential for railway operators to employ new methods of inspection that allow continuous and remote monitoring of railway tracks during the freeze–thaw period. While sensors are commonly used to measure localized track displacement, the advantages and limitations of using instruments that are capable of collecting data over a segment of track is not well understood. This paper investigates the use of a micro electro-mechanical sensor (MEMS) based instrument for monitoring surface displacement of railway tracks during FTC. The ShapeArray™ instrument, in this case the SAAX inclinometer, is a MEMS based sensor that was selected due to its ability to collect data over a segment of track (up to 150 m). Two sets of SAAX inclinometers were installed on a 50-metre section of track to measure data during two freezing-thawing periods. Analysis of the field data suggests that the main limitation of using MEMS-based sensors is their sensitivity to fluctuations of ambient temperature which may be confused with their responses to actual track displacement. A data analysis technique has been developed to remove the unwanted variations so that the instrument can be effectively used for monitoring track displacement during FTC. The comparison of the processed measurements with data collected from a digital level suggested that it provides a reasonably accurate measure of track surface displacement. Overall, the limited investigations in this project suggests that using MEMS-based sensor along with proper data processing techniques can provide useful information about the differential displacement over a segment of track, a key parameter for the safety of railway operation. The measurements can also be transferred through the cloud, enabling track engineers to remotely monitor track condition in near-real-time without the need to access the track and interrupt trains operations.

MAPPING AND PREDICTION OF LAND SUBSIDENCE

The exact location and timing of a land subsidence-related calamity cannot be foreseen with any degree of confidence. This is true for both progressive subsidence caused by fluid (groundwater, oil or gas) withdrawal and abrupt subsidence on surface caused by underground mine collapse. The best way to deal with these dangers is to mitigate them. In an ideal world, all regions prone to such risks would be well-known, and measures would be made to either prevent causing the problem if it is human-caused, or to avoid inhabiting such areas if they are prone to natural subsidence. Extensometers, levelling, hydrogeology modelling, and GPS are common methods for monitoring subsidence, although they require precise field data and are time-consuming. PSI (Persistent Scatterer Interferometry) is a strong radar-based remote sensing technique for measuring and monitoring surface displacements over time. The techniques of PSI using microwave sensors has made monitoring of earth deformation precisely more reliable and generates large number of Persistent Scatterer Candidates (PSC’s) or sampling points. Although, all the above techniques have their own merits and de-merits but mapping and prediction of susceptible subsidence prone zones is an issue. This paper deals with the application of the Exploratory Data Analysis (EDA), a powerful environment in Data Science provided a set of tools that made it easier to interpret PSI processed Big Data and also improved the capability of validation, management, visualization, and presentation of results with greater reliability.

Prediction of systolic displacement of tunnels by surface displacement

The method of surface displacement prediction of tunnel convergence displacement is used to make up for the failure of tunnel convergence displacement monitoring in the construction process, to supplement and verify the tunnel monitoring data, and to guide the construction. Firstly, some sets of systolic displacement and surface displacement data are obtained by field monitoring, which is used to calculate the parameter vector to be determined. The corresponding mathematical model is established and the systolic displacement of tunnel is predicted according to the monitoring data of surface displacement. Combined with field tunnel displacement monitoring and surface displacement monitoring, the correlation of displacement curve is analyzed, and the corresponding mathematical model is established. Combined with Matlab programming, the corresponding program language is written, the user interface is compiled, and the method of predicting tunnel convergence displacement by the ground displacement is realized.

Internet of Things Horizontal Platform Development for Expanded Application Scenarios and Use Cases

This paper presents the horizontal approach for the development of Internet of Things (IoT) platforms, based on a generic, multi-service, cloud-based IoT operational platform, called EMULSION, elaborated for the rapid development of mobile IoT systems and quick roll-out of corresponding IoT services. The platform is successfully used as a basis for the development of various IoT prototype systems for different IoT domains, such as smart environment control, smart health, smart electric appliances, smart water supply, etc. As an example of these, a ground surface displacement monitoring IoT system, operating in the area of smart environment control, is presented, along with aspects of the hardware design of the produced low-cost, small-size, global navigation satellite system (GNSS)-based sensor unit, utilized by it. The system architecture design is set out, supplemented by the presentation of initial test results.

Hysteresis effect and seasonal step-like creep deformation of the Jiuxianping landslide in the Three Gorges Reservoir region

Slow-moving landslides are common in the Three Gorges reservoir (TGR) region. It may evolve into massive landslide hazards due to reservoir level fluctuation and rainfall. The assessment of slow-moving reservoir landslides is critical for the prevention and control of geological hazards. A step-like deformation mechanism for slow-moving landslides is proposed. Here, we use various wavelet tools to process the time series of 16 years continuous monitoring surface displacement of the Jiuxianping landslide at TGR. Then, the methods are used to investigate the correlation and hysteresis between the trigger factors (rainfall and reservoir level fluctuation) and reservoir landslide creep displacement. Owing to the influence of reservoir level fluctuation and rainfall, the triggering factors of displacement in different regions differ and show prominent hysteresis characteristics. Furthermore, the contribution of GPS monitoring points and InSAR fusion technology to creep landslide assessment is discussed, which can effectively reduce the possibility false alarms in landslide prediction. These mechanisms can be used to explain why some sliding bodies can keep stable after very large and long-time deformation. Therefore, these results are crucial for effective and reasonable geological hazard prevention and control in the TGR region.

Slope monitoring optimization considering three-dimensional deformation and failure characteristics using the strength reduction method: A case study

The potential deformation and failure of a slope with typical 3D shapes involve 3D characteristics, such that these factors cannot be simulated using 2D methods. If 3D characteristics are not considered in expressway slope monitoring, an excessive number of monitoring points may be arranged in the stable/safe part, whereas insufficient monitoring points may be arranged in the unstable/dangerous part. In this study, the 3D deformation and failure characteristics of the Lijiazhai slope of the Shicheng–Ji'an Expressway in Jiangxi Province, China were analyzed by 3D numerical simulations using the strength reduction method. The potential 3D slope surface displacement trends, initial position of failure, and maximum depth of potential slip surface were simulated and discussed. The deformation of Slope A was generally small. The slope ranging from the third platform to the slope top was located in Region I, where the deformation was approximately equal to zero. The deformation of Slope B was located in Region V, where the displacement generally was larger than 2 cm in the range from the first–third platforms to the slope top, and the deformation of the trailing edge exceeded 5 cm. The surface displacement monitoring points should be arranged in Region V. Monitoring was then optimized considering the 3D characteristics of the deformation and failure of a slope. Accordingly, surface and deep displacement monitoring networks were effectively arranged in the unstable/dangerous part of the slope. Results may be used as references for similar projects.

Core versus Surface Sensors for Reinforced Concrete Structures: A Comparison of Fiber-Optic Strain Sensing to Conventional Instrumentation.

High-resolution distributed reinforcement strain measurements can provide invaluable information for developing and evaluating numerical and analytical models of reinforced concrete structures. A recent testing campaign conducted at UCLouvain in Belgium used fiber-optic sensors embedded along several longitudinal steel rebars of three reinforced concrete U-shaped walls. The resulting experimental dataset provides an opportunity to evaluate and compare, for different types of loading, the strain measurements obtained with the fiber-optic sensors in the confined core of the structural member against more conventional and state-of-the-practice sensors that monitor surface displacements and deformations. This work highlights the need to average strain measurements from digital image correlation techniques in order to obtain coherent results with the strains measured from fiber optics, and investigates proposals to achieve this relevant goal for research and engineering practices. The longitudinal strains measured by the fiber optics also provide additional detailed information on the behavior of these wall units compared to the more conventional instrumentation, such as strain penetration into the foundation and head of the wall units, which are studied in detail.

RFID Landslide Monitoring: Long-Term Outdoor Signal Processing and Phase Unwrapping

Localization of passive Radio-Frequency Identification (RFID) tags has been used to monitor landslide surface displacement since 5 years. This method, applied on slow displacements lower than 1cm per day, allows a high spatio-temporal resolution at a relatively low cost. With the feedback of the previous years, this paper proposes to summarize the various challenges encountered with the long-term outdoor RFID localization method, and presents data-processing solutions that were implemented to overcome these challenges. We propose a complex-smoothing unwrapping algorithm, a multi-frequency merging operation, as well as multi-tag and multi-antenna phase combining method. The concept of an unwrapping reference guide is presented and applied with groups of tags showing coherent displacements, or with absolute reference measurements. These approaches allow a higher data availability up to 38% for one site over multiple years, and a better phase unwrapping. Earth surface displacement monitoring with RFID proves to be a robust and accurate solution, with four equipped sites across France and Switzerland.

Feasibility of Terrestrial Laser Scanning System for Detecting and Monitoring Surface Displacement of Artificial Slopes on Forest Roads

Feasibility of Terrestrial Laser Scanning System for Detecting and Monitoring Surface Displacement of Artificial Slopes on Forest Roads

Selection and Optimization Mechanism of the Lower Return Roadway Layout in the near Residual Coal Pillar Area

Background: To optimize the layout position of the residual coal pillar return roadway when mining a close coal seam group and to clarify the optimization mechanism, a roadway optimization layout analysis was conducted on the Tashan coal mine. Methods: Surface displacement monitoring was conducted using field tests, and the main stress magnitude, plastic zone morphology, deformation variables, and connectivity between the plastic zone of the roadway and the plastic zone of the residual coal pillar were analyzed at different locations with the help of FLAC3D numerical simulation software. Results: It was found that, in the process of close coal seam group mining, the residual coal pillar of the overlying coal seam seriously affects the stress state and plastic zone distribution of the lower coal seam roadway. The roadway is arranged in a position that is relatively far away from the residual coal pillar, which could reduce the stress influence of the residual coal pillar on the roadway and guarantee the stability of the roadway. Conclusion: Since the Tashan Mine uses the top release method for mining, the stability of the roadway can be better ensured by placing the roadway in the middle and lower regions of the coal seam and using the layout method to retain small coal pillars.

Application of Machine Learning in Forecasting the Impact of Mining Deformation: A Case Study of Underground Copper Mines in Poland

Open access to SAR data from the Sentinel 1 missions allows analyses of long-term ground surface changes. The current data-acquisition frequency of 12 days facilitates the continuous monitoring of phenomena such as volcanic and tectonic activity or mining-related deformations. SAR data are increasingly also used as input data in forecasting phenomena on the basis of machine learning. This article presents the possibility of using selected machine learning algorithms in forecasting the influence of underground mining activity on the ground surface. The study was performed for a mining protective area with a surface of over 500 km2 and located in western Poland. The ground surface displacements were calculated for the period from November 2014 to July 2021, with the use of the Small Baseline Subset (SBAS) method. The forecasts were performed for a total of 22 identified subsidence troughs. Each of the troughs was provided with two profiles, with a total of more than 10,000 identified points. The selected algorithms served to prepare 180-day displacement forecasts. The best results (significantly better than the baseline) were obtained with the ARIMA and Holt models. Linear models also provided better results than the baseline and their performance was very good at up to 2 months forecasting. Tree-based models including their sophisticated ensemble versions: bagging (Random Forest, Extra Trees) and boosting (XGBoost, LightGBM, CatBoost, Gradient Boosting, Hist Gradient Boosting) cannot be used for this type of predictions since Decision Trees are not able to extrapolate and thus are not a valid stand-alone tool for forecasting in this type of problems. A combination of satellite remote sensing data and machine learning facilitated both the simultaneous quasi-permanent monitoring of ground surface displacements and their forecasting in a relatively long time period.

Influencing factors, deformation mechanism and failure process prediction for reservoir rock landslides: Tanjiahe landslide, three gorges reservoir area

Compared with terrestrial rock landslides, reservoir rock landslides are also affected by the rise and fall of the reservoir water level, and these landslides are more threatening. High-speed debris flows may form once they lose stability, and once they enter the water a surge is formed. This endangers the safe operation of reservoirs. This study explored the deformation characteristics and influencing factors of the Tanjiahe reservoir rock landslide in the Three Gorges Reservoir using field investigations, GPS surface displacement monitoring, and groundwater level monitoring. The discrete element system MatDEM was used to simulate failure motion, and predict the hazard area affected by the Tanjiahe landslide. The results show that within the reservoir water variation section (145–175 m), the Tanjiahe landslide mass was composed of surface soil (156–175 m) with low permeability and deep cataclastic rock (145–156 m) with high permeability. Due to the difference in permeability between the deep and surface layers, the response of landslide deformation to water level rise is not obvious. The high-level (175 m) operation of the reservoir and the decline in the reservoir water level (175–145 m) are key factors affecting the landslide deformation. Rainfall had a positive effect on landslide deformation. Under their combined action, the stability of the front gentle anti-sliding section of the landslide decreases, and the displacement of the middle and rear steeper sliding section increases under the driving force, which may lead to slope failure. The simulation results show that the upper part of the Tanjiahe landslide slides first and pushes the lower part to move, which is a typical of thrust load-caused failure. The speed of the sliding mass has three stages: rapid rise, rapid decline, and slow decline. The higher the slope angle, the higher the acceleration of the sliding mass in the direction parallel to the slope surface, the higher the speed peak value and the faster the sliding mass speed reaches the peak value. During the failure process, energy is transferred between sliding mass through collisions. Landslides can easily lead to debris flow. The maximum height of the first wave generated when the debris flow entered the water is 5.95 m, and the wave height that propagated to the opposite bank is 3.09 m. The landslide-induced waves propagated along the reservoir area for 30 km.

Remote Sensing Precursors Analysis for Giant Landslides

Monitoring and early warning systems for landslides are urgently needed worldwide to effectively reduce the losses of life and property caused by these natural disasters. Detecting the precursors of giant landslides constitutes the premise of landslide monitoring and early warning, and remote sensing is a powerful means to achieve this goal. In this work, we aim to summarize the basic types and evolutionary principles of giant landslide precursors, describe the remote sensing methods capable of identifying those precursors, and present typical cases of related sliding. Based on a review of the literature and an analysis of remote sensing imagery, the three main types of remote sensing techniques for capturing the geomorphological, geotechnical, and geoenvironmental precursors of giant landslides are optical, synthetic aperture radar (SAR), and thermal infrared methods, respectively. Time-series optical remote sensing data from medium-resolution satellites can be used to obtain abundant information on geomorphological changes, such as the extension of cracks and erosion ditches, and band algebraic analysis, image enhancement, and segmentation techniques are valuable for focusing on the locations of geomorphological landslide precursors. SAR sensors have the ability to monitor the slight slope deformation caused by unfavorable geological structures and can provide precursor information on imminent failure several days before a landslide; furthermore, persistent scatterer interferometric SAR has significant advantages in large-scale surface displacement monitoring. Thermal infrared imagery can identify landslide precursors by monitoring geoenvironmental information, especially in permafrost regions where glaciers are widely distributed; the reason may be that freeze–thaw cycles and snowmelt caused by increased temperatures affect the stability of the surface. Optical, SAR, and thermal remote sensing all exhibit unique advantages and play an essential role in the identification of giant landslide precursors. The combined application of these three remote sensing technologies to obtain the synthetic geomorphological, geotechnical, and geoenvironmental precursors of giant landslides would greatly promote the development of landslide early warning systems.

Stability trends of Jinpingzi landslide: A numerical study

The occurrence and development of creeping landslides lead to a gradual destruction of the affected environment; therefore, research into creeping landslide stability trends based on the monitoring of landslide data is of considerable practical value. We investigated the Jinpingzi landslide area II using strength subtraction to analyze the relationship between stress and strain at important points and the stability of the landslide. The results confirm the relationship between the internal failure pattern, safety factor, and key point displacement of creeping landslides. Furthermore, the results confirm the change rules of displacement, in addition to changes in the safety factor. By combining the surface displacement monitoring data of Jinpingzi landslide area II, its stability trend was analyzed based on the established relationship model between deformation displacement and internal failure characteristics of creeping landslides. The results demonstrate that the Jinpingzi landslide area II is in a stable damage deformation. The sliding surface formed in the landslide and the results obtained using the model of the Jinpingzi landslide area II are consistent with the actual situation determined by analysis in the field and exploring the geology.

Shallow Failure of Weak Slopes in Bayan Obo West Mine.

The slope stability of large open-pit mines has always been a concern and the analysis of large-scale slope landslides is a focus. However, shallow failure in soft rock slopes also has a serious impact on safe production. The northern slope of Baiyunebo West Mine has many shallow landslides in the final slope, resulting in damage of the maintenance channel of the belt transportation system, which has a serious impact on the safety of production. In order to reduce the shallow failure in weak rock slope, it is necessary to analyze the behavior and characteristics of shallow failure in weak rock. Firstly, the mechanical parameters of the intact rock were obtained by using the exploration data; secondly, through the analysis of blasting-damage range, the distribution characteristics of fractures after the failure of weak rock were obtained. Finally, through theoretical analysis, numerical simulation, surface displacement monitoring and on-site shallow-failure case analysis, the deformation and characteristics of shallow failure of weak rock slope in West Mine were obtained. It was found that the mechanical parameters of rock mass strength on the surface of weak rock slope and the original rock were quite different after mining disturbance. The mode of failure of shallow weak rock slope in the West Mine was creep-cracking; the numerical modelling analysis was carried out by using the assignment method of shallow lithology weakening and gradual change, which is more in line with the deformation characteristics of weak rock slope in West Mine. The lower deformation of the soft rock slope in West Mine is 3–5 times that of the upper deformation. The research results are helpful to understand the influence of blasting on the stability of soft rock slope. At present, West Mine has started to adjust blasting parameters according to the research results, so as to reduce the excessive damage of blasting to rock mass, so the stability of the slope is improved.

A safety management system for natural gas pipeline in subsidence area of coal mine

ABSTRACT As one of the main ways to transport natural gas, pipeline safety is of great significance to maintaining social stability and ensuring the national energy supply. Aiming at the safe operation of natural gas pipelines in subsidence areas of coal mine, this work proposes a safety management system for condition monitoring and control. This system contains three technical modules: the surface and pipeline displacement monitoring, the risk assessment index system, and early warning model. Firstly, the collected data of site topography and pipeline conditions are transmitted to the database remotely. Second, multi-source data are collected to form data reports and conduct in-depth analysis and mining. Then, according to the analysis results, the pattern of surface and pipeline displacement is explored, the risk assessment system of gas pipelines is constructed, and the pipeline strain is monitored. Real-time computing and other technologies are developed to form a safety management system for gas pipelines in subsidence areas. Taking Shanxi Province in China as an example, based on the system developed by the technical modules, the application of surface and pipeline displacement monitoring, risk assessment, and pipeline stress-strain monitoring technology in subsidence areas is achieved. The results show that the risk score of the area where the pipeline is located is 82, which is a high-risk level. In addition, in the process of strain monitoring, the measured stress at the most unfavorable position is 140.207 MPa, which meets the allowable stress requirements. This safety management system can provide important support for decision-making of risk prevention, assessment, and management of natural gas pipelines in subsidence areas of coal mine.

Assessment of safe exploitability of undermined objects of the Underground Ore Mining Department of the Mine Management of the PJSC “ArcelorMittal Kryvyi Rih”

The article is devoted to monitoring surface displacement and the condition of monitored objects. The object of research is the process of displacement of the earth’s surface and the state of protected objects of the “United” deposit of the mine department for underground mining of ores of PJSC “ArcelorMittal Kryvyi Rih”. The displacement process is monitored based on long-lasting instrumental observations to determine surface deformations and assess the safety of exploitation of the monitored objects within the mining allotment. The study findings enable ascertaining that in the southern and central parts of the minefield, the displacement process has stopped, but in the northern part, it is still developing, and mining will have no impact on the technological objects of the Mine Management in the next two years. Over the recent two years, actual subsidence rates in the railway area have not exceeded 2.7 mm/month, and they are significantly lower than the permissible values (100 mm/month). The road sections shifting and the base for the removal of the road continue to develop. Mining operations at the deposit “Obiednanyi” have no hazardous impact on the “Schistose Rocks” natural geological reserve, the settlement of Karnavatka and the cemetery “Zakhidne”. Displacement on road and road base sections is in progress. In the vicinity of the settlement of Zhukivka, the maximum relative deformations (3.2 mm/m) are still much lower than the permissible one (6 mm/m), and they will not reach their maximum permissible values in the nearest two three years. In the last year, deformation rates decreased and reached the 2018 figure. Therefore, all the monitored objects within the mining allotment can be safely exploited.

Monitoring analysis and environmental assessment of mine subsidence based on surface displacement monitoring

Over the past several years, a metal mine by block caving method has experienced a long-term and progressive surface deformation and fracturing, and then we start our investigation based on this background. The location of surface rupture was based on a series of mapping activities and the deformation data was collected by GPS from 2013 to 2016. In this paper, emphasis was put on the analysis of the fissures, deformation and stress of surface subsidence. Results reveal the diversity magnitude and structural features of surface deformation and ground fissures. In addition, the time dependent behavior is comprehended and the subsidence zone reflects different types of time-displacement curve – regressive phase, steady phase and progressive phase, all these achievements indicate the complexity and diversity of the subsidence zone. On the other hand, stress calculation which inspired from the mechanical model of the cracking of hole wall is carried out, it is meaningful to understand the relation between fracture features, displacement vectors and horizontal stress.

Potential and Limitation of PlanetScope Images for 2-D and 3-D Earth Surface Monitoring With Example of Applications to Glaciers and Earthquakes

The Planet PlanetScope cubesat constellation acquires high-resolution optical images which cover the entire surface of the Earth daily, enabling an unprecedented capability to monitor the Earth surface changes. However, our analysis reveals artifacts of the geometry of PlanetScope images related to the imaging system and processing issues, limiting the usability of these data for various earth science applications, including the monitoring of glaciers, dune motion, or the measurement of ground deformation due to earthquakes and landslides. Here we analyze these artifacts and propose ways to remediate them. We use two examples to evaluate the data and assess the performance of our proposed approaches. The first is the ground deformation caused by the 2019 Ridgecrest earthquake sequence, California, and the second is the 2018-2019 surge of the Shisper glacier in the Karakorum. Using an image correlation technique, we show that PlanetScope images exhibit several geometric artifacts, such as scene-to-scene misregistration, inconsistence geolocation accuracy between spectral bands, and topographic artifacts. Altogether these artifacts make a quantitative analysis of ground displacement difficult and inaccurate. We present a method that remediates most of these geometric artifacts. In addition, we propose a framework for selecting the most appropriate images and a procedure for refining the Rational Function Model (RFM) of unrectified images to monitor surface displacements and topography changes in 3D. These tools should enhance the use of PlanetScope images for Earth Science applications.