Landslides and resultant barrier lakes are significant threats to human lives and infrastructures. Three-dimensional (3D) surface displacements can give vital clues to the exploration of internal ...structure of landslides, but they are difficult to be retrieved from spaceborne Synthetic Aperture Radar (SAR) observations due to the intrinsic limitation of SAR imaging geometry. Meanwhile, studies on predicting slope failure based on SAR-measured displacements are rarely seen. Here, we used SAR pixel offset tracking to investigate the Baige landslide before the collapse on 10 October 2018. 3D surface displacements retrieved by combining satellite SAR and optical observations revealed heterogeneous spatial patterns within the landslide complex. We observed linear secondary creep and accelerating tertiary creep prior to the failure from multi-sensor SAR data. The possibility of forecasting the failure was demonstrated by applying an inverse velocity method to the time-series displacements measured by Sentinel-1 during the tertiary creep, which is valuable for risk evaluation and disaster early warning.
•We retrieved 3D displacement field by combining SAR and optical observations.•The 3D displacement field revealed the spatial complexity of the Baige landslide.•We derived historic displacements of the Baige landslide from three SAR data stacks.•Creep evolution from linear to accelerating was shown by time-series displacements.•We demonstrated the possibility of landslide early warning with SAR measurements.
Landslides are natural phenomena, causing serious fatalities and negative impacts on socioeconomic. The Three Gorges Reservoir (TGR) area of China is characterized by more prone to landslides for the ...rainfall and variation of reservoir level. Prediction of landslide displacement is favorable for the establishment of early geohazard warning system. Conventional machine learning methods as forecasting models often suffer gradient disappearance and explosion, or training is slow. Hence, a dynamic method for displacement prediction of the step-wise landslide is provided, which is based on gated recurrent unit (GRU) model with time series analysis. The establishment process of this method is interpreted and applied to Erdaohe landslide induced by multi-factors in TGR area: the accumulative displacements of landslide are obtained by the global positioning system; the measured accumulative displacements is decomposed into the trend and periodic displacements by moving average method; the predictive trend displacement is fitted by a cubic polynomial; and the periodic displacement is obtained by the GRU model training. And the support vector machine (SVM) model and GRU model are used as comparisons. It is verified that the proposed method can quite accurately predict the displacement of the landslide, which benefits for effective early geological hazards warning system. Moreover, the proposed method has higher prediction accuracy than the SVM model.
•A damage model based on microseismic data is developed.•Structurally-controlled displacements are predicted in 3D continuum framework.•Geological structures in numerical model can be specifically ...ignored.•Reasonable scope of potential failure region is revealed.
Large displacements controlled by the motion of layered rock strata usually pose a high hazard to the stability of high sidewalls of the underground caverns in bedded rock mass. Timely and accurate prediction of structurally controlled displacement can provide more reasonable guidelines for supporting measures during cavern excavation. In this study, an approach integrating the continuum modeling and microseismic (MS) monitoring data, was proposed to quantitatively predict the structurally controlled displacements in bedded rock masses surrounding large-scale underground caverns. First, a comprehensive method based on the MS data was adopted for judging the fracture type of bedded rock mass, and this method was validated by field surveys. Second, the damage scope of the bedded rock mass caused by each MS event was determined on the basis of fracture types. A damage model based on the MS data was successfully developed to be embedded into three-dimensional continuum modeling. Finally, our proposed method was verified by comparing its predictions with the actual data. Good agreements indicated that the large deformations induced by the rotation of layered rock strata with long deformed length, can be fully predicted using the damage model. Complicated geological structures can even be ignored when establishing the three-dimensional continuum model. The reasonable scope of potential failure region can be revealed by the predicted deformation mode, which verified the damage scope corresponding to each MS event.
Evaluation of mode I fracture characteristics, such as critical opening displacement and process-zone length, is fundamental for the analysis and prediction of crack growth. To identify deformation ...with micron-scale resolution, experiments were performed using digital image correlation, where displacement is determined through a comparison of a pair of digital images by matching a small area from the image before deformation to the image after deformation. The matching process uses a cross-correlation algorithm, and within this study, the correlation is based on a Fast Fourier Transform method. Mode I fracture tests were performed on Berea sandstone using three-point bending. Twelve specimens, of three types, were fabricated: six center notch (0.5mm radius), three smooth boundary, and three reduced-section (6 or 12mm radius notch). The characteristics of tensile fracture, namely opening displacement and crack length, were extracted from detailed displacement measurements. At the onset of unstable propagation (peak load) for the center notch specimens, the critical opening displacement ωc=30μm at the notch tip, and as the crack propagated, the known position of ωc allowed the identification of the process zone throughout the post-peak response. Incremental displacement contours established the tip of the effective crack, and the length of the process zone lp=5–7mm, about 10 times the maximum grain size. In addition, it was observed that the process zone maintained a constant length with constant critical opening for all tests.
► Digital image correlation is used to characterize fracture processes in Berea sandstone. ► Three types of specimens, including center notch (0.5mm radius), smooth boundary, and reduced-section (6 or 12mm radius notch) are tested in the experiments. ► The detailed information involves critical opening displacement ωc=30μm and the length of the process zone lp=5–7mm, about 10 times the grain size.
Optical flow computation is a key component in many computer vision systems designed for tasks such as action detection or activity recognition. However, despite several major advances over the last ...decade, handling large displacement in optical flow remains an open problem. Inspired by the large displacement optical flow of Brox and Malik, our approach, termed Deep Flow, blends a matching algorithm with a variational approach for optical flow. We propose a descriptor matching algorithm, tailored to the optical flow problem, that allows to boost performance on fast motions. The matching algorithm builds upon a multi-stage architecture with 6 layers, interleaving convolutions and max-pooling, a construction akin to deep convolutional nets. Using dense sampling, it allows to efficiently retrieve quasi-dense correspondences, and enjoys a built-in smoothing effect on descriptors matches, a valuable asset for integration into an energy minimization framework for optical flow estimation. Deep Flow efficiently handles large displacements occurring in realistic videos, and shows competitive performance on optical flow benchmarks. Furthermore, it sets a new state-of-the-art on the MPI-Sintel dataset.
•Development of a robust algorithm displacement calculation using computer vision algorithms.•Explanation of modifications to action cameras to enable long distance monitoring of ...structures.•Verification of system through intensive laboratory trials with industry leading technology.•Field application of system in uncontrolled conditions with load identification and validation.
This paper describes development of a contactless, low cost vision-based system for displacement measurement of civil structures. Displacement measurements provide a valuable insight into the structural condition and service behaviour of bridges under live loading. Conventional displacement gauges or GPS based systems have limitations in terms of access to the infrastructure and accuracy. The system introduced in this paper provides a low cost durable alternative which is rapidly deployable in the field and does not require direct contact or access to the infrastructure or its vicinity. A commercial action camera was modified to facilitate the use of a telescopic lens and paired with the development of robust displacement identification algorithms based on pattern matching. Performance was evaluated first in a series of controlled laboratory tests and validated against displacement measurements obtained using a fibre optic displacement gauge. The efficiency of the system for field applications was then demonstrated by capturing the validated bridge response of two structures under live loading including the iconic peace bridge. Located in the City of Derry, Northern Ireland, the Peace Bridge is a 310 m curved self-anchored suspension pedestrian bridge structure. The vision-based results of the field experiment were confirmed against displacements calculated from measured accelerations during a dynamic assessment of the structure under crowd loading. In field applications the developed system can achieve a root mean square error (RMSE) of 0.03 mm against verified measurements.
Optical methods that give displacement or strain fields are now widely used in experimental mechanics. Some of the methods can only measure in-plane displacements/strains on planar specimens and some ...of them can give both in-plane and out-of-plane displacement/strain fields on any kind of specimen (planar or not). In the present paper, the stereovision technique that uses two cameras to measure 3-D displacement/strain fields on any 3-D object is presented. Additionally, a quite inclusive list of references on applications of stereovision (and 3-D DIC) to experimental mechanics is given at the end of the paper.
Summary
For slope condition of ground surface, the asymmetrical deformation about the vertical center line and the horizontal center line of the tunnel cross section can be formed. A unified ...displacement function expressed by the Fourier series is presented to express the asymmetrical deformation of the tunnel cross section. Five basic deformation modes corresponding to the expansion order 2 are a complete deformation mode to reflect deformation behaviors of the tunnel cross section under slope boundary. Such this complete displacement mode is implemented into the complex variable solution for analytically predicting tunneling‐induced ground deformation under slope boundary. All of these analytical solutions are verified by good agreements of the comparison between the analytical solutions and finite element method results. A parameter study is carried out to investigate the influence of deformation modes of the tunnel cross section, geometrical conditions of the tunnel and the slope angle, and “Buoyancy effect” on the displacement field. Finally, the proposed method is consistent with measured data of the Hejie tunnel in China qualitatively. The presented solution can provide a simplified indication for evaluating the ground deformation under slope condition of ground surface.
Although massive flank failure is fairly common in the evolution of volcanoes, measurements of flank movement indicative of instability are rare. Here 3‐D displacements from airborne radar amplitude ...images derived using an amplitude image pixel offset tracking technique show that the west and southwest flanks of Pacaya Volcano in Guatemala experienced large (~4 m), discrete landsliding that was ultimately aborted. Pixel offset tracking improved measurement recovery by nearly 50% over classic interferometric synthetic aperture radar techniques, providing unique measurements at the event. The 3‐D displacement field shows that the flank moved coherently downslope along a complex failure surface involving both rotational and along‐slope movement. Notably, the lack of continuous movement of the slide in the years leading up to the event emphasizes that active movement should not always be expected at volcanoes for which triggering factors (e.g., magmatic intrusions and eruptions) could precipitate sudden major flank instability.
Key Points
Three‐dimensional displacements of a volcanic landslide created using pixel offset measurements between two synthetic aperture radar amplitude images
Four meters of flank movement at Pacaya Volcano suggest serious instability hazard
Episodic movement initiated by rapid triggers may promote volcano edifice instability without timely warning
On 28 September 2018, a strike‐slip earthquake occurred in Palu, Indonesia, and was followed by a series of tsunami waves that devastated the coast of Palu Bay. The tsunami was recorded at the ...Pantoloan tide gauge station with a peak amplitude of ~2 m above the water level and struck at high tide. We use the Pantoloan tsunami waveform and synthetic aperture rada displacement data in a joint inversion to estimate the vertical displacement around the narrow bay. Our inversion result suggests that the middle of the bay was uplifted up to 0.8 m, while the other parts of the bay subsided by up to 1 m. However, this seafloor displacement model alone cannot fully explain the observed tsunami inundation. The observed tsunami inundation heights and extents could be reproduced by a tsunami inundation simulation with a source model that combined the estimated vertical displacement with multiple subaerial‐submarine landslides.
Plain Language Summary
The tsunami that devastated Palu and other coastal towns inside Palu Bay on 28 September 2018 was recorded at a sea level monitoring station in Pantoloan. The recorded tsunami wave data are used in an inversion method to estimate the source of the tsunami in the form of an initial seafloor displacement. We found that the seafloor displacement was the main cause of the large tsunami. Satellite images and field survey data suggest that landslides around multiple river deltas also generated local tsunami waves. Our numerical simulations of the tsunami inundation show that the disaster was caused by a combination of the sudden ground and seafloor changes from the earthquake, landslides, and the high tide at the time of the event.
Key Points
The series of tsunami waves that created the disaster in Palu was caused by a combination of seafloor uplift and multiple landslides
The seafloor vertical displacement was estimated using tsunami waveform and SAR data and is evaluated to be the source the largest tsunami
Ground subsidence of up to 1 m and a tide level of 1 m during the event enhanced the tsunami impact in Palu city
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