Highway Landslide Research Articles

A non-contact quantitative risk assessment framework for translational highway landslides: Integration of InSAR, geophysical inversion, and numerical simulation

A non-contact quantitative risk assessment framework for translational highway landslides: Integration of InSAR, geophysical inversion, and numerical simulation

Highway Landslide Hazards in Indiana—Construction and Analysis of a Landslide Inventory

Highway Landslide Hazards in Indiana—Construction and Analysis of a Landslide Inventory

A Computation to Generate 2D and 3D Vector Displacements Using InSAR Ascending and Descending Source Data (Case Studies: Landslides and Earthquake in Indonesia)

Interferometric Synthetic Aperture Radar (InSAR) is a radar technique to generate map of surface deformation using phase differences acquired at different times. The InSAR technique measures these phase differences in its line of sight (LOS). Regarding LOS projection to a ground coordinate system, the combination of SAR data from ascending and descending can estimate at least two dimensional fields which are vertical and east-west components and three dimensional fields with either an additional motion model or vector displacements from along-track direction. The purpose of this work is to generate 2D and 3D vector displacements from two different InSAR tracks (e.g. ascending and descending) with a calculation programme both for the mean velocity and time series data named as PS DISP. 2D mode is calculated in which the north-south component is neglected due to insensitive along the flight direction, thus, assuming to be zero (0). On the other hand, 3D mode is calculated with an assumption that the northsouth component moves along the elevation downward. The experimental results were conducted for the Puncak Pass and Puncak Highway landslides and the Lombok earthquake in Indonesia. For the landslide study, the computation generated the movement towards the slope surface in the 3D Cartesian coordinate (dU,dE, and dN (psuedo)) and found both the crown body and cumulative zone of the landslide. For the earthquake study, PS DISP decomposed 2D vectors (dU and dE). The area of earthquake rupture was lifted by 42 cm and other northern Lombok areas by 10 - 25 cm. Regarding the west-eastern motion, it shows that the west of northern Lombok was displaced ±5 cm toward the west direction, while the other side to the east direction. Keywords: InSAR, 2D and 3D displacements, slope aspect, ground motion, landslide, earthquake

Evaluation and analysis of statistical and coupling models for highway landslide susceptibility

Landslides have a great impact on the normal traffic of highway, and maintaining the normal traffic of highway is the foundation of economic development, so landslide susceptibility mapping is very important. In this study, four counties, which locate in the central Ganzi Tibetan Autonomous Prefecture, Sichuan Province, China, are taken as the research region. Based on the 190 historical landslide disaster points in the region, six factors-elevation, slope, aspect, plan curvature, profile curvature and TWI (Topographic Wetness Index) - are finally selected for calculation. A landslide disaster is evaluated by two single models of CF (Certainty Factors) and IV (Information Value) models and four coupling models of CF-AHP (Analytic Hierarchy Process), CF-LR (Logistic Regression), IV-AHP and IV-LR models. The accuracy of the six models is evaluated by the ROC (Receiver Operating Characteristic) curve and the Sridevi Jadi parameters. The IV-AHP model has the highest value of 0.9189, which indicates that the IV-AHP model is more appropriate for landslide disaster assessment in the whole region. In the Sridevi Jadi parameters, the IV model have the highest value of 0.8696, showing that the IV model have the highest accuracy in landslide susceptibility assessment in high- and very high-susceptibility regions.

Research on Fracture Mechanism and Stability of Slope with Tensile Cracks

Tensile cracks at the crest of slope will attenuate the stability of slope. The aim of this paper is to investigate the computation of safety factors acting on a clay slope when the slip surface consists of tensile crack and shear surface. Based on the theory of limit equilibrium, an analytical solution for safety factors containing three types of failure mechanisms is presented. The optimal crack depth was obtained by using the principle of minimum safety factor. In the solution, effects of parameters such as crack depth, slope angle, height, cohesion, and internal friction angle on slope stability were discussed. By comparing with the results of previous studies, the rationality of the proposed approach was verified. Results show that consideration of tensile cracks lead to a significant reduction in slope stability, and the safety factor decreases by about 10% compared with the slope without cracks. The law of safety factor varying with crack depth indicates that it first decreases as the crack depth is increased and then increases as the crack depth is further increased. Through the parametric analysis, it is found that the safety factor increases with an increase in cohesion and internal friction angle but decreases with the slope angle and height increase. It is important to note that the optimal crack depth does not exceed one-third of the slope height. Moreover, a highway landslide that occurred in the road running across the Yunnan and Tibet Province was investigated to verify the practicality of the present method.

Development Characteristics and Sensitivity Analysis of Expansive Soil Slope

According to laboratory tests of soil samples of Wangyan highway landslide, the mechanism of formation of landslide and the degree of sensitivity of various factors to slope stability are analyzed. It is found that the landslide is destroyed by the properties of expansive soil, the existence of water in the cracks, the loading of artificial filling, and the traction of old landslide. The soil samples were tested for SEM and MIP tests by lyophilization, and the particle morphology, the mode of combination, porosity, and connectivity of the sliding zone soil were observed by a scanning electron microscope. Results show that the sliding zone developed many microfissures and the clay minerals arranged tightly, the pore of size < 0.1 μm was 60% in undisturbed soil, and the pores of different sizes were distributed uniform in reconstituted soil. The undisturbed soil had typical nonlinear rheological property; The deformation rate of reconstituted was bigger; When the load was 50 kPa and 200 kPa, an expansion phenomena occurred in the sliding zone, which indicated that microstructure could influence the deformation. The strength attenuation of expansive soil slope due to the high content of montmorillonite in the sliding body and the high water content in the cracks are two major factors of the Wangyan highway landslide. Based on the results of previous studies, the a , n , and m values of fitting parameters of Fredlund-Xing soil-water characteristic curve are predicted by using the basic physical properties of soil. It is found that the air intake value and residual suction value of filled soil (loose and broken) and completely weathered sandstone are small, and the water holding capacity in the middle suction range is relatively good. Then, the finite difference software Flac3D was used to build a three-dimensional geological model. The influence of water content, highway load, filling weight, and slope angle on slope stability is considered comprehensively. The order of sensitivity of slope stability about various factors is as follows: water content > slope angle > highway load > filling weight . The results of research can provide a scientific basis for the treatment, protection, and reinforcement of the Wangyan highway landslide.

A Landslide Susceptibility Evaluation of Highway Disasters Based on the Frequency Ratio Coupling Model

A landslide disaster, especially a highway landslide, may greatly impact the transport capacity of nearby roads. Keeping highways open, in particular, is crucial for supporting the functioning of the economy, society and people. Therefore, evaluating the highway landslide susceptibility is particularly important. In this paper, the city of Laibin, in the Guangxi Zhuang Autonomous Region of China, was taken as the study zone. According to data on 641 highway landslide disaster points measured in the field and a basic evaluation of the study area, nine evaluation factors—the elevation, slope, aspect, height difference, plan curve, profile curve, precipitation, Topographic Wetness Index (TWI) and vegetation coverage—were selected. We coupled a Frequency Ratio (FR) model, Analytic Hierarchy Process (AHP), Logistic Regression (LR), Back Propagation Neural Network (BPNN) and Support Vector Machine (SVM) to evaluate the susceptibility to highway landslides, with a Receiver Operating Characteristic (ROC) curve used to analyze the precision of these models. The ROC curve showed that the accuracy of the five models was greater than 0.700 and thus had a certain reliability. Among them, the FR-LR model had the highest accuracy, at 0.804. The study protocol presented here can therefore provide a reference for evaluation studies on landslide susceptibility in other areas.

Research on application of GPS-based wireless communication system in highway landslide

Machine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and industrial process control. Deep learning has It is widely used in the field of wireless communication. Prediction of geological disasters (such as landslides) is currently a difficult problem. Because landslides are difficult to detect in the early stage, this paper proposes a GPS-based wireless communication continuous detection system and applies it to landslide deformation monitoring to achieve early treatment and prevention. This article introduces the GPS multi-antenna detection system based on deep learning wireless communication, and introduces the time series analysis method and its application. The test results show that the GPS multi-antenna detection system of the wireless communication network has great advantages in response time, with high accuracy and small error. The horizontal accuracy is controlled at 0–2 mm and the vertical accuracy is about 1 mm. The analysis method is simple and efficient, and can obtain good results for short-term deformation prediction.

Mechanism analysis and partition characteristics of a recent highway landslide in Southwest China based on a 3D multi-point deformation monitoring system

An increasing number of landslides are occurring during the construction of highways in mountainous areas all over the world. A recent highway landslide located in the mountainous region of Southwest China is taken as a representative example to carry out the initiation mechanism and deformation characteristics analysis, and study the intelligent partitioning method in this paper. The geological conditions of the landslide are obtained through detailed geological surveys and investigation. A three-dimensional (3D) monitoring network with a total of 72 multi-points, including 53 surface displacement monitoring points and 19 deep displacement monitoring holes, is established to examine the spatial deformation characteristics of the landslide for nearly 25 months. The monitoring results of the surface displacement show that the dynamic deformation of the landslide can be divided into three stages, namely initial deformation stage, accelerated deformation stage, and stabilization stage. Based on the strata distribution obtained by the borehole investigation and the results of deep displacement monitoring, the depth of the slip surface can be reliably determined. The smart contract method in blockchain technology combined with the multi-point monitoring dataset is novelty applied to realize the intelligent automatic partition of the highway landslide without any human involvement. This method can provide the basis for further independent analysis of different landslide zones. According to the investigation and analysis, the initiation mechanism for the highway landslides is attributed to both internal poor geological conditions and external intense precipitation and engineering excavation.

Retracted] Integration and Fusion of Geologic Hazard Data under Deep Learning and Big Data Analysis Technology

To discuss the analysis and evaluation of highway landslides, the application of data mining methods combined with deep learning frameworks in geologic hazard evaluation and monitoring is explored preliminarily. On the premise of optimizing the processing of landslide images, first, the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) based on the natural statistical characteristics of the spatial domain is introduced, which is initially combined with Super‐Resolution Convolutional Neural Network (SRCNN). Then, the AlexNet is fine‐tuned and applied to highway landslide monitoring and surveying. Finally, an entropy weight gray clustering evaluation method based on data mining analysis is proposed, and the performances of several methods are verified. The results show that the average score of the BRISQUE algorithm in Image Quality Assessment (IQA) is above 0.9, and the average running time is 0.1523 s. The combination of BRISQUE and SRCNN can improve the image quality significantly. After fine‐tuning, the recognition accuracy of AlexNet for landslide images can reach about 80%. The evaluation method based on gray clustering can effectively determine the correlation between soil moisture content and slope angle and thereby be applied to the analysis and evaluation of highway landslides. The results are beneficial to the judgment and assessment of highway landslide conditions, which can be extended to research on other geologic hazards.

Susceptibility mapping and zoning of highway landslide disasters in China.

Prominent regional differentiations of highway landslide disasters (HLDs) bring great difficulties in highway planning, designing and disaster mitigation, therefore, a comprehensive understanding of HLDs from the spatial perspective is a basis for reducing damages. Statistical prediction methods and machine learning methods have some defects in landslide susceptibility mapping (LSM), meanwhile, hybrid methods have been developed by combining the statistical prediction methods with machine learning methods in recent years, and some of them were reported to perform better than conventional methods. In view of this, the principal component analysis (PCA) method was used to extract the susceptibility evaluation indexes of HLDs; the particle swarm optimization-support vector machine (PSO-SVM) model and genetic algorithm-support vector machine (GA-SVM) model were implemented to the susceptibility mapping and zoning of HLDs in China. The research results show that the accumulative contribution rate of the four principal components is 92.050%; evaluation results of the PSO-SVM model are better than those of the GA-SVM model; micro dangerous areas, moderate dangerous areas, severe dangerous areas and extreme dangerous areas account for 24.24%, 19.49%, 36.53% and 19.74% of the total areas of China; among the 1543 disaster points in the HLDs inventory, there are 134, 182, 421 and 806 located in the above areas respectively.

Forecasting Disastrous Characteristics of Highway Landslides Using the Material Point Method: A Surcharge‐Induced Perspective

Precisely forecasting the disastrous characteristics of landslides can address the optimized preliminary design of the highway landslide stabilization. In this paper, taking the surcharge‐induced landslides as an example, we developed the models of the material point method (MPM), a novel meshless numerical method, to calculate the large deformation of the highway landslides, with the affordable computing power. After convincing verification of the MPM model to simulate a surcharge‐induced soil landslide, 32 typical postfailure scenarios were analyzed to obtain the highway landslide run‐out processes and disastrous characteristics, such as the sliding distance and speed of the leading edge and sliding body morphology. Moreover, linear regression equations of the maximal sliding distance and speed were deduced after verification, to forecast the reasonable avoiding distance. The maximal sliding distance and speed were found to be negatively linearly correlated with the internal frictional angle and cohesion of the soil, and positively linearly correlated with the surcharge and the slope angle, respectively. Optimized preliminary design, of the highways in the mountainous and hilly areas, can be performed based on those insights.

Analyze the Cause of Highway Landslide Constructed over the Sandy Area Affected by Underground Water and Treatment Design Solution

Analyze the Cause of Highway Landslide Constructed over the Sandy Area Affected by Underground Water and Treatment Design Solution

A new framework for characterizing landslide deformation: a case study of the Yu-Kai highway landslide in Guizhou, China

This paper presents a new framework for characterizing landslide deformation. Here, the deformation of a landslide is interpreted as a summation of three components: rigid deformation, within-mass deformation, and residual deformation. On the basis of the monitored data of the landslide deformation, these three components may be characterized separately: the rigid deformation is simulated by a summation of a trend term and a periodic term, the within-mass deformation is simulated by a high-order polynomial model, and the residual deformation is simulated by a conditional random field model. In particular, the characterization of the residual deformation, the third component of the landslide deformation, with the random field allows for a probabilistic assessment of the landslide deformation in the face of geological uncertainties. With the proposed framework, the evolution of landslide deformation in both geometric and time domains may be established, which allows for an assessment of the sliding mechanism of the landslide. Further, evolution in the geometric domain may allow for an assessment of the serviceability of infrastructures in the landslide area. To illustrate this new landslide deformation characterization framework, a case study of the Yu-Kai highway landslide in Guizhou, China is presented, through which the effectiveness of the proposed framework is demonstrated.

Improved plane layout of stabilizing piles based on the piecewise function expression of the irregular driving force

The paper presents an improved plane layout for stabilizing piles based on a proposed piecewise function expression for the irregular driving force. Based on the specific morphological characteristics of a highway landslide, the piecewise function is used to calculate the irregular driving force by dividing the landslide into several sub-areas. Furthermore, the reasonable layout range and pile spacing can be obtained based on the piecewise function expression of the irregular driving force and on relevant research results of the plane layout for stabilizing piles. Therefore, an improved plane layout of stabilizing piles is presented in consideration of a piecewise function expression of the irregular driving force. A highway landslide located in eastern Guizhou Province, China, is analyzed as a case study using the proposed method. The results demonstrate that the theory presented in this paper provides improved economic benefits and can reduce the required number of stabilizing piles by 28.6% compared with the conventional plane layout scheme.

Investigating the critical slip surface of soil slope based on an improved black hole algorithm

Analysing the stability of soil slopes and investigating critical slip surfaces present an important and very complicated optimisation problem. In this paper, we solve this problem by introducing and modifying a new global optimisation (black hole algorithm) technique to form a new global optimisation algorithm for continuous optimisation (the improved black hole algorithm). By combination with typical mature limit equilibrium analysis (the Spencer method and the Morgenstern-Price method), the improved black hole algorithm was used to find the critical slip surface of soil slope. Thus, this paper proposed a new method for finding the critical slip surface of soil slope. Finally, the proposed method was verified through two typical numerical soil slope cases and was compared with the black hole algorithm and other extant studies. The results indicated that the applicability, validity and effectiveness of the improved black hole algorithm showed an improvement over previous studies and over the black hole algorithm. Moreover, the proposed method was applied for one highway landslide, and the determined critical slip surface was well agreement with the real one.

Erratum to: Geotechnical and geophysical characterization of the Bouira-Algiers Highway (Ain Turck, Algeria) landslide

The Ain Turck (Bouira) landslide, in north-center Algeria, is one of the numerous instabilities recorded along the Lakhdaria-Bouira section of the 1200-km-long east-west Algerian highway. The locality of Ain Turck is known for its unstable slopes characterized by a very rough morphology with steep slopes (20 to 25%). This slide threatens the inhabitants of the Ibournanen village, located down the unstable slope, where parts of some houses have fallen into ruin, while others are cracked. It is characterized by an active movement extending over a more or less important slope, of the order of a hundred meters. The land mobilized by this movement corresponds to the layer of shale clays and clays overlaid by a backfill, placed there following the east-west highway works. Geological, geomorphologic, and geotechnical analysis allows determining the soil instability probably related to earthworks during the construction of the highway section a few years earlier, followed by a particularly rainy season in 2012. Acquisitions of ambient seismic noise and H/V ratio processing, as well as the acquisition of an electrical resistivity profile at the instability site, have reinforced our preliminary interpretations of depth and geometry of the sliding surface.

Geotechnical and geophysical characterization of the Bouira-Algiers Highway (Ain Turck, Algeria) landslide

Geotechnical and geophysical characterization of the Bouira-Algiers Highway (Ain Turck, Algeria) landslide

Inversion of Critical Slip Surface Parameters for a Landslide Disaster Using the Bionics Algorithm

AbstractTwo key issues in landslide forecasting are finding the critical slip surface and determining its parameters. Generally, these issues are two parts of one problem. To solve this problem, a new two-phase search method is proposed: a newly proposed inversion method to determine the critical slip surface parameters, using a new bionics algorithm (i.e., particle swarm optimization), and based on the measured slip surface and the critical slip surface-searching process. The proposed method is verified by using two typical numerical examples used by the Association for Computer Aided Design (Australia) and an engineering example of a highway landslide. The results indicate that when the search over a critical slip surface and the inversion of its parameters are performed simultaneously, the calculated factor of safety is in good agreement with that of the actual scenario, whereas the factor of safety computed on the basis of known parameters of a slide body will deviate from that of the physical scenario.

Correspondence Analysis of Soil around Micropile Composite Structures under Horizontal Load

The current approach, which is based on conformal transformation, is to map micropile holes in comparison with unit circle domain. The stress field of soil around a pile plane, as well as the plane strain solution to displacement field distribution, can be obtained by adopting complex variable functions of elastic mechanics. This paper proposes an approach based on Winkler Foundation Beam Model, with the assumption that the soil around the micropiles stemmed from a series of independent springs. The rigidity coefficient of the springs is to be obtained from the planar solution. Based on the deflection curve differential equation of Euler-Bernoulli beams, one can derive the pile deformation and internal force calculation method of micropile composite structures under horizontal load. In the end, we propose reinforcing highway landslides with micropile composite structure and conducting on-site pile pushing tests. The obtained results from the experiment were then compared with the theoretical approach. It has been indicated through validation analysis that the results obtained from the established theoretical approach display a reasonable degree of accuracy and reliability.