Deformation Monitoring Research Articles

Analyzing the effects of critical active waveguide parameters on acoustic emission characteristics for soil slope deformation monitoring

Analyzing the effects of critical active waveguide parameters on acoustic emission characteristics for soil slope deformation monitoring

Accurate Deformation Retrieval of the 2023 Turkey–Syria Earthquakes Using Multi-Track InSAR Data and a Spatio-Temporal Correlation Analysis with the ICA Method

Multi-track synthetic aperture radar interferometry (InSAR) provides a good approach for the monitoring of long-term multi-dimensional earthquake deformation, including pre-, co-, and post-seismic data. However, the removal of atmospheric errors in both single- and multi-track InSAR data presents significant challenges. In this paper, a method of spatio-temporal correlation analysis using independent component analysis (ICA) is proposed, which can extract multi-track deformation components for the accurate retrieval of earthquake deformation time series. Sentinel-1 data covering the double earthquakes in Turkey and Syria in 2023 are used to demonstrate the effectiveness of the proposed method. The results show that co-seismic displacement in the east–west and up–down directions ranged from −114.7 cm to 82.8 cm and from −87.0 cm to 63.9 cm, respectively. Additionally, the deformation rates during the monitoring period ranged from −137.9 cm/year to 123.3 cm/year in the east–west direction and from −51.8 cm/year to 45.7 cm/year in the up–down direction. A comparative validation experiment was conducted using three GPS stations. Compared with the results of the original MSBAS method, the proposed method provides results that are smoother and closer to those of the GPS data, and the average optimization efficiency is 43.08% higher. The experiments demonstrated that the proposed method could provide accurate two-dimensional deformation time series for studying the pre-, co-, and post-earthquake events of the 2023 Turkey–Syria Earthquakes.

A multipoint prediction model for the deformation of concrete dams considering climatic features of high-altitude regions

High-altitude regions are characterized by natural climatic features such as low temperatures and high radiation. Concrete dams built in these regions face more complex operating conditions. Traditional single-output deformation prediction models ignore the correlations between different monitoring points, making it difficult to assess the overall deformation behavior of concrete dams. The black-box nature of some machine learning models can lead to a lack of interpretability, affecting the practical application. Therefore, a multipoint prediction model (MPM) is proposed to analyze the deformation behavior of concrete dams in high-altitude regions. Firstly, the deformation monitoring points are divided based on the climatic features of high-altitude regions. Subsequently, the MPM is constructed using the multi-output CatBoost model and Quasi-Monte Carlo algorithm to achieve deformation prediction across different partitioned monitoring points. Finally, the elucidation of the MPM optimization procedure in a transparent manner alongside the quantification of the influence exerted by input variables on output outcomes notably augments the interpretive capacity of the MPM. The proposed model is validated using monitoring data from a concrete dam in a high-altitude region. The disparities in chaotic and entropy variation features among deformation monitoring points in different zones corroborate the appropriateness of the zoning in this study. Comparisons between the single-output CatBoost model and MPM verify the feasibility and efficiency of multipoint predictions. Comparisons with other multi-output prediction models validate the superior predictive performance of the MPM. Additionally, the proposed model's generalization performance is validated using data from another concrete arch dam in high-altitude regions.

Ground subsidence in major Philippine metropolitan cities from 2014 to 2020

Land subsidence is recognized as one of the hazards that threaten Metro Manila, Philippines, and other major urban areas worldwide. It has become a significant global issue caused by excessive groundwater extraction, rapid urbanization, and natural sediment compaction, exacerbated by climate change through rising sea levels. This paper presents vertical ground motion rates in Philippine metropolitan cities using Sentinel-1 InSAR time series analysis from 2014 to 2020 through UK COMET’s LiCSAR products and the LiCSBAS package of Morishita et al. (2020). The results revealed a maximum subsidence rate of 109 mm/yr in Bulacan Province in Greater Manila. For the first time, this paper also presents ground motion estimates and the following maximum subsidence rates for other Philippine metropolitan cities: 11 mm/yr in Metro Cebu, 38 mm/yr in Metro Davao, 9 mm/yr in Metro Iloilo, and 29 mm/yr in Legazpi City. Areas with remarkably high subsidence rates are observed as circular to elliptical deformation features in vertical motion maps. Sinking areas mostly coincide with industrial and commercial complexes evident as a contiguous distribution of large and expansive man-made structures with distinct radar reflections. Monitoring this hazard is crucial as it increases the risk of floods, building and infrastructure damage, and economic loss, and exposes residents along the coast to worsening tidal incursions and storm surges due to climate change. InSAR is proposed here as a targeted, long-term deformation monitoring tool, especially related to groundwater usage.

Evaluation of sensor-enabled piezoelectric geoelectric cable in cyclic shear tests of subgrade soil under vertical cyclic loads

Of late, deformation of subgrade soil has led to an increasing number of road subsidence diseases. Real-time monitoring of subgrade deformation is critical to ensure the safety of subgrade operations. In this paper, a sensor-enabled piezoelectric geoelectric cable (SPGC) with impedance strain effect and piezoelectric effect is tested. The SPGC impedance and voltage signals obtained by cyclic shear test under vertical static load and cyclic shear test under vertical cyclic load are used to evaluate the monitoring effect. The results showed that normal stress had the greatest effect on the shear strength of the soil, whereas the normal stress and horizontal shear displacement amplitude significantly influenced the strain in the soil. Varying the normal and horizontal shear frequencies had little effect on the shear strength and strain of the soil. The normalized impedance and voltage of the SPGC, respectively, decreased and increased rapidly during the initial stage of the shear cycle; these changes were relatively small during the middle and late stages of the shear cycle. The SPGC voltage waveform revealed the changes in the shear stress and vertical displacement under different normal and horizontal shear frequencies, from which the stability of the subgrade soil under the aforementioned conditions could be evaluated. The variations in the SPGC impedance and effective voltage from the cyclic shear tests under both vertical static and vertical cyclic loads remained essentially consistent with the number of cycles. However, there was a difference in that the trough of the SPGC impedance under the vertical cyclic load was larger than that under the vertical static load; likewise, the effective SPGC voltage under the cyclic load was larger than that under the static load. Through an analysis of the SPGC impedance and voltage signals in the subgrade soil, the consistency of the SPGC-normalized impedance and effective voltage with shear stress was clarified; this helped us evaluate the health of the subgrade and monitor the characteristics of the precursor signals before a slide were to occur, thereby affording us an opportunity to issue timely warnings.

3D surface change detection of slope using 3D point cloud based on construction of double surface

Aiming at the complex geological conditions of slopes and the difficulty of manual investigation, this paper proposes a method of constructing double surface based on 3D point cloud data to estimate the depth of slope deformation and disaster analysis. Terrestrial Laser Scanner is utilized to collect the slope point cloud data. Through the construction of double surface to simulate the original slope, the deformation depth is estimated and the depth data are fused into the point cloud to realize the automatic identification of slope deformation disaster and the calculation of deformation depth, and provide the deformation depth map. The shortcomings of the traditional Multiscale Model and Model Point Cloud Comparison (M3C2) algorithm, which needs to capture multiple time periods of point cloud data for calculation can be overcome. And there is no need to recognize the segmentation of the slope point cloud. The study results show that the maximum relative error of slope deformation is 10.82% in slope deformation. The proposed method is suitable for detecting slope hazards in various scenarios, providing a basis for further analysis and the development of effective erosion control measures. It introduces a new technology for daily monitoring of slope deformations and can be extended to drone-based LiDAR applications.

A dual-base station constraint method to improve deformation monitoring precision consistency in strip regions

The precision of deformation monitoring with Global Navigation Satellite System (GNSS) relative positioning is significantly influenced by the distance between the monitoring and base stations. In long strip regions, the considerable differences in station spacing lead to inconsistent monitoring precision among multiple stations. This presents a challenge to accurately model and predict the deformation pattern. To tackle this issue, this paper introduces a novel dual-base station constraint method. This method integrates the baseline length constraint between two base stations into the conventional relative positioning model. The formulae of the proposed method are first derived in detail. Then the data collected at eight monitoring stations in two strip regions of 6 km and 8 km over a 28-day period are used to validate the effectiveness of the proposed method. The quantitative analysis of monitoring precision consistency indicators and hypothesis testing on the correlation between monitoring precision and station spacing are conducted. The results show that: (1) median values of the East, North, and Up consistency indicators are reduced from 2.14, 1.41, and 1.83 to 0.91, 0.67, and 0.55 and from 1.85, 1.85, and 2.32 to 0.69, 1.00, and 0.87, respectively, indicating monitoring precision consistency improvement for two case studies; (2) the absolute values of the correlation coefficients between monitoring precision and station spacing decrease from 0.99, 0.94, and 0.98 to 0.09, 0.36, and 0.32. Using the t-test with a significant level of 0.01, it is demonstrated that there is no significant correlation between monitoring precision and station spacing when employing the proposed method.

Real-Time Simulation of Tube Hydroforming by Integrating Finite-Element Method and Machine Learning

The real-time, full-field simulation of the tube hydroforming process is crucial for deformation monitoring and the timely prediction of defects. However, this is rather difficult for finite-element simulation due to its time-consuming nature. To overcome this drawback, in this paper, a surrogate model framework was proposed by integrating the finite-element method (FEM) and machine learning (ML), in which the basic methodology involved interrupting the computational workflow of the FEM and reassembling it with ML. Specifically, the displacement field, as the primary unknown quantity to be solved using the FEM, was mapped onto the displacement boundary conditions of the tube component with ML. To this end, the titanium tube material as well as the hydroforming process was investigated, and a fairly accurate FEM model was developed based on the CPB06 yield criterion coupled with a simplified Kim–Tuan hardening model. Numerous FEM simulations were performed by varying the loading conditions to generate the training database for ML. Then, a random forest algorithm was applied and trained to develop the surrogate model, in which the grid search method was employed to obtain the optimal combination of the hyperparameters. Sequentially, the principal strain, the effective strain/stress, as well as the wall thickness was derived according to continuum mechanics theories. Although further improvements were required in certain aspects, the developed FEM-ML surrogate model delivered extraordinary accuracy and instantaneity in reproducing multi-physical fields, especially the displacement field and wall-thickness distribution, manifesting its feasibility in the real-time, full-field simulation and monitoring of deformation states.

Study on InSAR deformation information extraction and stress state assessment in a railway tunnel in a plateau area

Introduction: The study proposes a method for evaluating stress distribution in high-altitude Tibetan Plateau railway tunnels using high-precision radar satellite time-series interferometric synthetic aperture radar technology.Methods: To effectively monitor and prevent geological hazards during the construction process, this method i employed, as it serves as a component of advanced geological prediction and surrounding rock deformation monitoring technology for high-altitude tunnels, particularly in the Dongelu Tunnel of the China–Tibet Railway. The study utilizes time-series interferometric synthetic aperture radar to obtain deformation information for Dongelu Tunnel area between 2022 and 2023 from Sentinel- 1A orbit images. This quantitatively investigates the upper mountain body and line-of-sight direction along the tunnel. The deformation characteristics are correlated with high-frequency and high-precision automated vertical displacement monitoring results, determining the spatiotemporal distribution of tunnel deformation. In this study, a model that determines the vertical stress state of the Dongelu Tunnel under loading near the entrance and evaluates its health status was established.Results: The results show that the surface deformation of the mountain above the tunnel axis develops slowly and is relatively small, with a maximum vertical deformation rate of 1–3 mm/year. The average stress on the tunnel arch is 5.54 MPa, with a fluctuation range of 0.01 MPa. Temporal Q9 changes in various parts of the tunnel are periodic, with maximum fluctuations observed in December 2022. The study reveals inconsistent surface settlement of the tunnel arch and mountain above it, causing minor vertical stress changes. As the tunnel construction progresses, vertical stress variation shows periodicity because of an initial imbalance in internal stress within the mountain. Stress fluctuations near the tunnel entrance occur during the initial excavation phase, gradually diminishing as the project progresses and internal stress stabilizes.Discussion: The proposed tunnel monitoring and stability assessment method can reduce its impact on engineering construction and provide guidance for advanced geological prediction.

Non-linear ground deformation detection and monitoring using time series InSAR along the coastal urban areas of Pakistan.

Conventional geodetic methods rely on point measurements, which have drawbacks for detecting and tracking geologic disasters at specific locations. In this study, the time series Interferometric Synthetic Aperture Radar (InSAR) approach was incorporated to estimate non-linear surface deformation caused by tectonic, shoreline reclamation, and other anthropogenic activities in economically important urban regions of Pakistan's southern coast, which possesses around 270km. The shoreline is extended from the low-populated area on the premises of the Hub River in the west to the highly populated Karachi City and Eastern Industrial Zone, where we collected the Sentinel-1A C-band data from 2017 to 2023 to address urban security and threats to human life and property. The main advantage of opting for the non-linear persistent scatterer interferometric SAR (PSInSAR) approach for this study is that it exposes minute movements without any prior consideration of conventional monitoring techniques, making it valid in continuously varying regions. An average vertical displacement range of - 170 to + 82mm per year was found, which was used to investigate the potential correlation with the most effective causative parameters of deformation. The densely populated areas of the study area experience an annual subsidence of 170mm, and the less populated western region experiences an uplift of 82mm annually. Land deformation varies along the coast of the study area, where the eastern region is highly reclaimed and is affected by erosion. Groundwater table-depleting regions experienced high levels of land subsidence, and tectonic activities controlled vertical displacement in the region. Major variation was detected after an earthquake occurred along fault lines. This study was designed because a non-linear approach is required to address ground movement activities acutely, and it will make it possible to plan surface infrastructure and handle issues brought on by subsidence more effectively.

Methods and research for deformation monitoring of earth and rock dams based on close-range photogrammetry

Abstract Traditional means of monitoring deformation in earth and rock dams encounter challenges such as low monitoring efficiency and limited coverage. Despite the potential of emerging technologies such as GPS and three-dimensional laser scanning, their adoption is expensive and hard to promote. This paper presents a deformation monitoring method for earth and rock dams based on the close-range photogrammetry technique. The proposed approach focuses on analytical algorithm the design and deployment of monitoring points, photographic schemes, camera checking and calibration, as well as deformation analysis methods. Initially, based on the analysis of the parsing algorithms’ applicability, they are fused to address the shortcomings of common image parsing methods in meeting the requirements of high precision and multi-image processing for deformation monitoring of earth and rock dams. Subsequently, the fused algorithm is introduced to analyze the acquired image data for 3D reconstruction, and the deformation in earth and rock dams is assessed based on the generated dense point cloud model. The proposed deformation monitoring method is applied to Pine Bridge Reservoir Dam, and the results demonstrated its capacity to comprehensively analyze the deformation. Furthermore, the required equipment is simple and easy to operate, aligning with the requirements for deformation monitoring accuracy of earth and rock dams.

CORS station for synergistic monitoring of multivariate surface parameters in expansive soils

Expansive soils cause frequent surface deformation due to their expansion and contraction, which is a serious engineering hazard, and long-term subsidence monitoring is a prerequisite for preventing and controlling expansive soil disasters. Currently, the conventional monitoring methods for the above issue include Interferometric Synthetic Aperture Radar (InSAR) technology, but InSAR is not suitable for uninterrupted monitoring of surface deformation and has low sensitivity. Meanwhile, it can’t obtain multiple surface environmental parameters around the station. The Global Navigation Satellite System (GNSS), a system that can directly acquire surface deformation, has been widely used in landslide disaster monitoring, and in recent years, this technology has also been applied to the field of expansive soil disaster monitoring. At the same time, GNSS can also provide a constant stream of L-band microwave signals to obtain ground environmental information such as precipitable rainfall and soil moisture around the station. In previous studies of expansive soil hazards, GNSS technology has been mainly used to provide surface deformation information without exploring its potential to invert ground environmental information around stations. This paper proposes a ground-based GNSS remote sensing integrated monitoring system that integrates expanding land surface parameters such as “precipitable rainfall, soil moisture, and three-dimensional deformation” and analyses the ability of ground-based GNSS to be used for integrated monitoring of expanding soil hazards by combining ten years of consecutive observational data from GNSS stations along the coastal area of Houston. The experimental results show that the GNSS is capable of providing highly accurate time-series characterization of deformation, and inelastic subsidence in recent years has resulted in a cumulative permanent elevation loss of 2 cm along the Houston coast. The correlation coefficient between soil moisture extracted by the fifth-generation European reanalysis data (ERA5) and soil moisture inverted by ground-based GNSS is 0.514. At the same time, the GNSS was also able to monitor the zenithal precipitable water vapor (PWV) and soil moisture changes around the GNSS station and further analyze the response relationship among the three parameters, which could comprehensively evaluate the stability of expansive soils, avoiding the unreliability of relying on a single piece of monitoring information to assess the stability of expansive soils. We hope to construct a more comprehensive ground-based GNSS remote sensing monitoring system to better monitor expansive soil hazards.

Monitoring ground temperature and deformation of the cast-in-place footings in permafrost regions on the Qinghai‒Tibet Plateau

The long-term stability of the cast-in-place footings in permafrost regions has received much attention due to its climate sensitivity. The current research lacks long-term data validation, especially in the context of climate change. Based on the 13-year (2011–2023) temperature and deformation monitoring data from the Qinghai‒Tibet Power Transmission Line, this study investigates the characteristics of permafrost variation and its impact on the stability of tower footings under the cooling effect from thermosyphons. The results reveal that the thermosyphons effectively reduce the ground temperature around the footings. After the first freeze‒thaw cycle, the soil around the tower footings completed refreezing and maintained a frozen state. In the following 13 years, the ground temperature continued to decrease due to the cooling effect of thermosyphons. The duration notably exceeded the previously predicted 5 years. The temperature reduction at the base of the footings corresponded well with the frost jacking of the tower footings and could be divided into three distinct phases. In phase 1, the ground temperature around the footings rapidly reduced, approaching that of the natural field, while the footings experienced pronounced deformation. In phase 2, the ground temperature decreased at a faster rate, and the deformation rate of the footings slowed down. In phase 3, the frost jacking of the footings gradually retarded with the decrease in base temperature. Additionally, the ground temperature differences of over 1 °C were observed among different tower footings, which may lead to the differential deformation among the tower footings. The ground temperature differentiation is attributed to the difference in solar radiation intensity, which is shaded by the tower structure from different directions. This study provides theoretical support and empirical accumulation for the construction and maintenance of tower footings in permafrost regions.

Novel sensorized additive manufacturing-based enlighted tooling concepts for aeronautical parts

This paper presents lightweight tooling concepts based on additive manufacturing, with the aim of developing advanced tooling systems as well as installing sensors for real-time monitoring and control during the anchoring and manufacturing of aeronautical parts. Leveraging additive manufacturing techniques in the production of tooling yields benefits in manufacturing flexibility and material usage. These concepts transform traditional tooling systems into active, intelligent tools, improving the manufacturing process and part quality. Integrated sensors measure variables such as displacement, humidity and temperature allowing data analysis and correlation with process quality variables such as accuracy errors, tolerances achieved and surface finish. In addition to sensor integration, additive manufacturing by directed energy arc and wire deposition (DED-arc) has been selected for part manufacturing. The research includes the mechanical characterisation of the material and the microstructure of the material once manufactured by DED-arc. Design for additive manufacturing" principles guide the design process to effectively exploit the capabilities of DED-arc. These turrets, equipped with sensors, allow real-time monitoring and control of turret deformation during clamping and manufacturing of aeronautical parts. As a first step, deformation monitoring is carried out within the defined tolerance of ± 0.15, which allows a control point to be established in the turret. Future analysis of the sensor data will allow correlations with process quality variables to be established. Remarkably, the optimised version of the turret after applying DED technology weighed only 2.2 kg, significantly lighter than the original 6 kg version. Additive manufacturing and the use of lightweight structures for fixture fabrication, followed by the addition of sensors, provide valuable information and control, improving process efficiency and part quality. This research contributes to the development of intelligent and efficient tool systems for aeronautical applications.

Monitoring of Channel Deformations of the Lower Dniester Using Topographic Maps and Satellite Imagery with the Implementation of GIS Technologies

Rivers are one of the most complex formations on the Earth’s surface; they are connected with the deep structure of the Earth, the landscape environment, and unpredictable weather cataclysms. The study aims to investigate the peculiarities of the geological structure and tectonics of the Lower Dniester region, examine the types of meanders, determine the horizontal displacements of the riverbed, and assess the impact of anthropogenic factors on the riverbed and riparian areas. The methodology is based on the use of tectonic maps, geological maps of Quaternary deposits, historical topographic maps, and satellite images to determine the long-term horizontal displacements of the riverbed, identify meander types, and study the meandering characteristics and their relationships with tectonic structures. Horizontal riverbed displacements were measured at 76 points using data from the 1980 map and a Sentinel-2 image obtained in 2020. For the purpose of studying the types of meanders and their analysis, it is proposed to use the characteristics of meanders and their relationships. This approach will allow for more efficient analysis and prediction of changes in channel processes under the influence of natural and anthropogenic factors across various temporal scales. The research shows that the Lower Dniester region is influenced by the tectonics of internal structures and the seismically active Vrancea zone in Romania. Additionally, a comparison of cartographic data from 1880 and 1980 and satellite images from 2020 allows us to assess how the territory of the Lower Dniester riparian area has changed under the influence of anthropogenic factors.

The failure mechanism of the Baishi landslide in Beichuan County, Sichuan, China

The Baishi landslide was located in the western part of Beichuan County, Sichuan Province, China. The landslide experienced multiple minor collapses at the front part, accompanying with numerous tensile cracks. To comprehensively grasp the stability conditions and predict the moment of failure of the landslide, deformation monitoring of the landslide has been carried out from the moment that the landslide was reported until it failed. This study analyzed the different phases of landslide deformation and its failure mechanism through the analysis of monitoring data. The result showed that the failure manifests both the retrogressive and advancing features. The landslide was divided into several zones based on the spatial variation of the deformation characteristics. Moreover, the improved tangential angle criterion is applied to categorize the deformation phases of a landslide. Investigating the surface displacement vectors and vector angles of landslides plays a significant role for ascertaining the failure and sliding mechanism. The monitoring results revealed that the front part of the landslide played a key role in the stability of the landslide. Therefore, the monitoring data from this zone were crucial for predicting the moment of complete landslide failure.

Retrospect on the Ground Deformation Process and Potential Triggering Mechanism of the Traditional Steel Production Base in Laiwu with ALOS PALSAR and Sentinel-1 SAR Sensors.

The realization of a harmonious relationship between the natural environment and economic development has always been the unremitting pursuit of traditional mineral resource-based cities. With rich reserves of iron and coal ore resources, Laiwu has become an important steel production base in Shandong Province in China, after several decades of industrial development. However, some serious environmental problems have occurred with the quick development of local steel industries, with ground subsidence and consequent secondary disasters as the most representative ones. To better evaluate possible ground collapse risk, comprehensive approaches incorporating the common deformation monitoring with small-baseline subset (SBAS)-synthetic aperture radar interferometry (InSAR) technique, environmental factors analysis, and risk evaluation are designed here with ALOS PALSAR and Sentinel-1 SAR observations. A retrospect on the ground deformation process indicates that ground deformation has largely decreased by around 51.57% in area but increased on average by around -5.4 mm/year in magnitude over the observation period of Sentinel-1 (30 July 2015 to 22 August 2022), compared to that of ALOS PALSAR (17 January 2007 to 28 October 2010). To better reveal the potential triggering mechanism, environmental factors are also utilized and conjointly analyzed with the ground deformation time series. These analysis results indicate that the ground deformation signals are highly correlated with human industrial activities, such underground mining, and the operation of manual infrastructures (landfill, tailing pond, and so on). In addition, the evaluation demonstrates that the area with potential collapse risk (levels of medium, high, and extremely high) occupies around 8.19 km2, approximately 0.86% of the whole study region. This study sheds a bright light on the safety guarantee for the industrial operation and the ecologically friendly urban development of traditional steel production industrial cities in China.

A stretchable and self-powered strain sensor with elastomeric electret

Stretchable deformation sensors play an important role in the perception and autonomy of soft robots. While various sensors have been reported, the mechanical sensor with self-powered capability and stretchability to suit extreme environment is urgently required. In this study, a stretchable, self-powered, sensitivity adjustable, and long-term stability strain sensor based on the stretchable electret is researched for deformation monitoring. This stretchable and self-powered sensor is composed of the dielectric elastomer with designed elastic modulus gradient and the stretchable electret with elastomeric and Nano-particles. The electro-mechanical capability of this designed sensor is researched and optimized by multi-objective optimization approach. The sensor exhibits self-powered capability, stretchability (tensile strain from 0% to 20%), tunable sensitivity (optimized from 5.7 to 5.9 pC mm−1), and stability, where electromechanical performance remains stable after 8000 stretching cycles. The feasibility of its autonomous sensing which promotes a wide range of potential application in soft robotics is demonstrated. This elastic modulus gradient-induced and net charge design significantly broadened the potential applications with large deformation and low-attached stiffness.

Landslide Hazard Prediction Based on Small Baseline Subset–Interferometric Synthetic-Aperture Radar Technology Combined with Land-Use Dynamic Change and Hydrological Conditions (Sichuan, China)

Le’an Town, located in the southwest of Qingchuan County, Guangyuan City, Sichuan Province, boasts a unique geographical position. The town’s terrain is complex, and its geological environment is fragile. Multiple phases of tectonic movements have resulted in numerous cracks and faults, making the area prone to landslides, debris flows, and other disasters. Additionally, heavy rainfall and fluctuating groundwater levels further exacerbate the instability of the mountains. Human activities, such as overdevelopment and deforestation, have significantly increased the risk of geological disasters. Currently, the methods for landslide prediction in Le’an Town are limited; traditional techniques cannot provide precise forecasts, and the study area is largely covered by tall vegetation. Therefore, this paper proposes a method that combines SBAS-InSAR technology with dynamic changes in land use and hydrological conditions. SBAS-InSAR technology is used to obtain surface deformation information, while land-use changes and hydrological condition data are incorporated to analyze the dynamic characteristics and potential influencing factors of landslide areas. The innovation of this method lies in its high-precision surface deformation monitoring capability and the integration of multi-source data, which can more comprehensively reveal the geological environmental characteristics of the study area, thereby achieving accurate predictions of landslide development. The study results indicate that the annual subsidence rate in most deformation areas of Le’an Town ranges from −10 to 0 mm, indicating slow subsidence. In some areas, the subsidence rate exceeds −50 mm per year, showing significant slope aspect differences, reflecting the combined effects of geological structures, climatic conditions, and human activities. It is evident that land-use changes and hydrological conditions have a significant impact on the occurrence and development of landslides. Therefore, by utilizing SBAS-InSAR technology and cross-verifying it with other techniques, the consistency of identified landslide deformation areas can be enhanced, thereby improving results. This method provides a scientific basis for the monitoring and early warning of landslide disasters and has important practical application value.

Study on Deformation Control of Road-Deep Foundation Pit Passing under Elevated Subway Bridge

This paper focuses on the application of pile foundation underpinning technology in a deep foundation pit of a subway Viaduct Project in Beijing. The study aims to address the engineering characteristics of the project, including a large number of new piles, a wide span of underpinning abutment, a long length of deep foundation pit, and a wide range of influences. This research utilizes field monitoring and numerical simulation methods to investigate the pile foundation underpinnings. The impact and management of road-deep foundation pit construction are considered, as well as their combined effect on subway viaducts and track structures. The primary accomplishments are as follows: (1) By analyzing the data from on-site deformation monitoring, it is evident that the pier exhibits maximum vertical deformation and maximum transverse deformation at the same location. The measuring locations are specifically situated on Pier 7# at the pile foundation underpinning. The maximum vertical and transverse deformations of the track are directly proportional to the maximum deformation of the pier. (2) By comparing the numerical simulation results with the field monitoring data, it is observed that although there is some discrepancy between the two, the deformation trend is largely consistent. This suggests that the numerical simulation analysis method is effective in reflecting the deformation of the bridge and track. (3) Through the numerical model and changing the values of the retaining structure parameters, the sensitivity of the pier deformation near the road foundation pit to the retaining structure parameters is systematically analyzed. The sensitivity of the pier deformation to the foundation pit parameters is as follows: the embedded depth insertion ratio of the retaining pile > the diameter of the retaining pile > the pile spacing.