Control Of Geological Disasters Research Articles

A Multiscale Attention Segment Network-Based Semantic Segmentation Model for Landslide Remote Sensing Images

Landslide disasters have garnered significant attention due to their extensive devastating impact, leading to a growing emphasis on the prompt and precise identification and detection of landslides as a prominent area of research. Previous research has primarily relied on human–computer interactions and visual interpretation from remote sensing to identify landslides. However, these methods are time-consuming, labor-intensive, subjective, and have a low level of accuracy in extracting data. An essential task in deep learning, semantic segmentation, has been crucial to automated remote sensing image recognition tasks because of its end-to-end pixel-level classification capability. In this study, to mitigate the disadvantages of existing landslide detection methods, we propose a multiscale attention segment network (MsASNet) that acquires different scales of remote sensing image features, designs an encoder–decoder structure to strengthen the landslide boundary, and combines the channel attention mechanism to strengthen the feature extraction capability. The MsASNet model exhibited an average accuracy of 95.13% on the test set from Bijie’s landslide dataset, a mean accuracy of 91.45% on the test set from Chongqing’s landslide dataset, and a mean accuracy of 90.17% on the test set from Tianshui‘s landslide dataset, signifying its ability to extract landslide information efficiently and accurately in real time. Our proposed model may be used in efforts toward the prevention and control of geological disasters.

Investigation on the behaviors of water infiltration in the unsaturated loess

Introduction: Surface water from precipitation or irrigation is the sole contributor to groundwater replenishment in the Loess Plateau of China. The occurrence of landslides in the Loess Plateau is closely related to the infiltration process of surface water, and the frequent occurrence of landslides in the Loess Plateau in recent years has seriously affected the economic development and security of the Loess Plateau.Methods: To investigate the loess infiltration in deeper soil, the process of moisture infiltration in unsaturated loess is studied by field observation, theoretical analysis, and numerical simulation.Results and discussion: The research results indicated that the interstitial flow in loess could be divided into three different zones: the active zone, the stable zone (2–94 m), and the saturated zone (below 97 m); based on the matric suction and water content calculations, the L1 soil stable water content is 24.4%, which corresponds to the moisture sensor measurement of L1 loess 4 m and 7 m of stable zone data; the numerical simulation results show that whether the infiltration is continuous or intermittent, the infiltration law is the same. After 20 years, there will be a stable water content zone in the 1–8 m soil layer with a water content of 31%. The numerical results well confirm the theoretical calculation results. The research results explain the process of surface water infiltration into groundwater through thick loess and can provide an important reference for the prevention and control of geological disasters caused by water infiltration in loess areas.

Experimental study of soil erosion on moraine-consolidated slopes under heavy rainfall

Surface subsidence pits formed by mining disturbance are highly susceptible to slope instability under rainfall erosion, inducing underground debris flow disasters. To prevent and control underground debris flow disasters in a subsidence area, a test model of subsidence pit slope was established in accordance with the principle of similar simulation, and the erosion-resistant performance of moraine-cured slopes with different soil–slurry ratios and the law of runoff and sand production were investigated through the simulation of artificial rainfall and a simulation test of grouting. Results show that the initial rainfall production time increases exponentially with increasing soil-slurry ratio, while sediment production intensity decreases linearly with increasing rainfall duration. The evolution of soil erosion can be divided into five stages: impact infiltration, water-filled softening, stripping cutting, migration crossing, and steady flow equilibrium. Compared with in situ moraine, moraine particles after grouting between the generation of large amounts of Si–O–Si and Si–OH hydration products become loose and porous soil medium is transformed into a dense cemented structure. The soil-slurry ratio is 5:1, the sand-fixing effect increases by 28.8 times, the resistance of permeability increases by 11.3 times, and the grouting curing effect is remarkable. This study can provide technical support for the prevention and control of geological disasters in subsidence pits.

Land subsidence prediction in Zhengzhou's main urban area using the GTWR and LSTM models combined with the Attention Mechanism

In recent years, due to urbanization and human activities, groundwater overexploitation has become increasingly severe, resulting in some degrees of land subsidence and, consequently, causing a series of geological disasters and other environmental issues. Therefore, large-scale and high-precision land subsidence prediction is of great importance for the prevention and control of geological disasters. However, the existing prediction models and methods ignore the effects of the spatiotemporal non-stationary relationships between the influencing factors and the accumulated land subsidence, causing the poor accuracy of the predicted land subsidence results. In this context, a Geographically and Temporally Weighted Regression combined with the Long Short-Term Memory (LSTM)-multivariable and Attention Mechanism (AM) (GTWR-LSTMm-AM) was proposed to more accurately predict the deformation of time series land subsidence in this study. The small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) was used to reveal the temporal deformation information of Zhengzhou's main urban area, then the GTWR model was used to assess the spatiotemporal non-stationarity relationships between the accumulated land subsidence and its influencing factors monthly groundwater stability level, monthly precipitation and Normalized Difference Vegetation Index (NDVI) data, and to determine the corresponding weight matrix. In addition, we introduced an LSTM model with AM to extract key information from the time-series land subsidence data and adjusted the dynamic weights of the three selected influencing factors to predict the land subsidence in Zhengzhou's main urban area. The prediction accuracy R2 of the GTWR-LSTMm-AM model reaches 0.972, which is higher than 0.929 of the LSTMm model. The prediction accuracy RMSE is less than 3 mm and reaches 2.403 mm. In addition, we determined the importance of the impact factor on the subsidence results by randomly interrupting the impact factor time series, disclosuring that the monthly groundwater level contributed the most to the land subsidence in Zhengzhou's main urban area.

Surface Subsidence Monitoring of Mining Areas in Hunan Province Based on Sentinel-1A and DS-InSAR.

Monitoring the surface subsidence in mining areas is conducive to the prevention and control of geological disasters, and the prediction and early warning of accidents. Hunan Province is located in South China. The mineral resource reserves are abundant; however, large and medium-sized mines account for a low proportion of the total, and the concentration of mineral resource distribution is low, meaning that traditional mining monitoring struggles to meet the needs of large-scale monitoring of mining areas in the province. The advantages of Interferometric Synthetic Aperture Radar (InSAR) technology in large-scale deformation monitoring were applied to identify and monitor the surface subsidence of coal mining fields in Hunan Province based on a Sentinel-1A dataset of 86 images taken from 2018 to 2020, and the process of developing surface subsidence was inverted by selecting typical mining areas. The results show that there are 14 places of surface subsidence in the study area, and accidents have occurred in 2 mining areas. In addition, the railway passing through the mining area of Zhouyuan Mountain is affected by the surface subsidence, presenting a potential safety hazard.

Analysis on the Spatial-Temporal Distribution Patterns of Major Mine Debris Flows in China

In order to provide more accurate data support for the prevention and control of geological disasters in mines, the article counts the major mine debris flow accidents in China from 1954 to 2019; studies the distribution of debris flow disasters in each province; reveals the intra-annual and inter-annual variation patterns of the number of mine debris flow disasters; analyzes the distribution of mine debris flows under different geoenvironmental backgrounds; and combines AHP hierarchical analysis with a comprehensive regional evaluation of the likelihood of mine debris flows. The results of the study show that from 1954 to 2019, the number of major mine debris flow disasters first increased and then decreased. The proportion of mine debris flow disasters to the total number of debris flow disasters also showed a trend of first increasing and then decreasing, with the southwestern region being the area of high occurrence of mine debris flow, and the geoenvironmental areas of middle and low hills and middle and high mountains being the topographic areas of high occurrence of mine debris flow. More than 90% of the major mine debris flow disasters occurred from May to September, with the largest number of disasters occurring in July. A comprehensive evaluation of the regional nature of mine debris flow distribution based on the regional evaluation score is derived.

Research on geological environment protection and geological disasters control countermeasures in China

Geological disasters in mines, ecological environment and geology and geomorphology are closely bound up with each other. To reduce or avoid economic loss and to decrease the threat degree of geological disasters to life safety, the protection of geological environment are formulated in this study. Specifically, this includes taking mines that are dominated by thin bedded carbonate as the research objects. The goals of this study include prevention and control of geological disasters and protection of geological environment. The data are based on characteristics of geological strata in mines collected by the exploration, and combined with the characteristics of geomorphic environment, relevant rules aiming at the prevention and control of geological disasters. Then, pursuant to the selection of indicators, an evaluation system is constructed to verify the effectiveness of measures and strategies proposed, in which the score value is converted into the corresponding level to test the implementation effect of the measures and strategies proposed. Through comparing the changes of the utility levels before and after the implementation of measures and strategies proposed, it can be seen that the geological disaster levels of the five mining areas in the study region are respectively improved from the non-ideal levels V, IV, V, V, IV to II, I, I, II, II, with the tailings pond leakage times less than 4 times and collapse volume less than 5m3. And, the levels of geological environment are upgraded from levels IV, IV, IV, V, V to ideal levels II, II, II, I, II, accomplished by the vegetation coverage rate of the mine reaching more than 35%, as well as the recovery rate of exploitation and utilization rate of tailings both exceeding 85%, which indicates that the protection strategy proposed in this paper has good practicality and feasibility.

Detection of former goaf and analysis of deformation characteristics of overburden in Dameidong coal mine

In order to analyze the deformation of the old goaf in Dameidong Coal Mine and its influence on the surrounding rock and soil layer, it provides guidance for the prevention and control of geological disasters in the region. In this paper, the transient electromagnetic method and numerical simulation method were used to study the deformation law of the overlying strata in the mining area. The results of transient electromagnetic detection showed that the subsidence area of the goaf in Dameidong Coal Mine was within the range of the elliptical water-rich area, and the average buried depth of the goaf was expected to be 90 m. The model was established by discrete element numerical simulation to study the variation law of mining overburden rock. The results showed that the stress change in coal mining was mainly reflected at both ends of the goaf, which was a stress concentration phenomenon. Overburden rock deformation changed with the mining process. The stress concentration area and the displacement change area were highly coincident, consisted with the displacement monitoring map, showing a “U”-type distribution. The results proved that the numerical simulation results do have theoretical guidance for mining subsidence control.

Landslide susceptibility mapping in Three Gorges Reservoir area based on GIS and boosting decision tree model

As one of the most destructive geological disasters, a myriad of landslides has revived and developed in the Three Gorges Reservoir area under the combined action of various detrimental factors. Therefore, the pertinently regional landslide susceptibility mapping (LSM) is of great significance for disaster prevention and mitigation. In this study, LSM is prepared by using a boosting-C5.0 decision tree model. Under the landslide verification of on-site investigations, the study area is divided into accumulation and rock areas, and a total of 12 impact factors are selected. TOL and VIF are employed to determine the multicollinearity among the impact factors. The independent training (80%) and validation (20%) datasets are constructed by random sampling for LSM. ANN, C5.0, and SVM are selected for comparative analysis. The results show that there is no rigorous multicollinearity among the impact factors proposed in this paper. The landslide susceptibility in the study area is divided into low, moderate, high, and very high. The highest susceptibility area distributes along the riverside where the landslide ratio is 37.05% in boosting-C5.0 model. Then the ROCs are expropriated to infer the accuracy of each model. The boosting-C5.0 performs the best with the largest area under the curve in both accumulation and rock areas, reaching at 0.991 and 0.990 in the validation sets, respectively. Finally, the composite modification of the 5 validation sets shows that the uncertainty of boosting-C5.0 is concentrated in the intermediate probability areas of susceptibility. This study reveals the feasibility of machine learning in landslide susceptibility assessment, which could provide a basis for the risk management and control of geological disasters.

Thinking on Effective Methods of Successful Prediction of Geological Hazards in Shaanxi, China

In the process of human survival and development, it is inevitable to transform the original state of the world, thus forming a contradiction between the earth and the earth. The violent form of this contradiction is geological disasters. Geological disasters pose a threat to human life and property, and cause damage caused by natural or human factors, often causing casualties. The destruction process of geological disasters is usually a gradual process, showing many pre-disaster symptoms, such as local landslides, surface cracks, building deformation, tree skew, and ground sound. Evacuation can be avoided in advance according to the disaster precursors, so as to avoid casualties and achieve successful prediction. By reviewing the general situation of geological disasters in Shaanxi Province and the casualties in 2020, the difficulties in the prevention and control of geological disasters are summarized. In view of these difficulties, an on-site investigation, visit and analysis of geological disaster points and successful forecast points in Shaanxi Province in 2020 were conducted. In addition, combined with actual cases and years of work experience, the successful prediction experience of geological disasters was discussed from 8 aspects. Finally, the “Regulations on the Reward for Successful Geological Disaster Forecasting in Shaanxi Province” was revised in order to improve the successful prediction ability of geological disasters in Shaanxi Province and even the whole country, provide reference for future prevention and control of geological disasters, and effectively protect the safety of people’s lives and property.

Evaluation of Geological Disaster Sensitivity in Shuicheng District Based on the WOE-RF Model

To improve the prevention and control of geological disasters in Shuicheng District, 10 environmental factors—slope, slope direction, curvature, NDVI, stratum lithology, distance from fault, distance from river system, annual average rainfall, distance from road and land use—were selected as evaluation indicators by integrating factors such as landform, basic geology, hydrometeorology and engineering activities. Based on the weight of evidence, random forest, support vector machine and BP neural network algorithms were introduced to build WOE-RF, WOE-SVM and WOE-BPNN models. The sensitivity of Shuicheng District to geological disasters was evaluated using the GIS platform, and the region was divided into areas of extremely high, high, medium, low and extremely low sensitivity to geological disasters. By comparing and analyzing the ROC curve and the distribution law of the sensitivity index, the AUC evaluation accuracy of the WOE-RF, WOE-SVM and WOE-BPNN models was 0.836, 0.807 and 0.753, respectively; the WOE-RF model was shown to be the most effective. In the WOE-RF model, the extremely high-, high-, medium-, low- and extremely low-sensitivity areas accounted for 15.9%, 16.9%, 19.3%, 21.0% and 26.9% of the study area, respectively. The extremely high- and high-sensitivity areas are mainly concentrated in areas with large slopes, broken rock masses, river systems and intensive human engineering activity. These research results are consistent with the actual situation and can provide a reference for the prevention and control of geological disasters in this and similar mountainous areas.

RISK ASSESSMENT OF GEOLOGICAL DISASTERS ALONG THE G213 MAOXIAN-WENCHUAN SECTION BASED ON GF-6 DATA

Abstract. China is a country prone to natural disasters, and roads are easily damaged in natural disasters. As the infrastructure of people's production and life and the lifeline of post-disaster rescue, roads play a very important role. There are many previous studies on geological disasters risk assessment, but few special researches on highway geological disasters risk assessment, especially quantitative risk assessment combined with remote sensing images. Therefore, the risk assessment of geological disasters along the road is of great significance for the prevention and control of geological disasters and the protection of life and property safety. Based on GF-6 data and other geographic data, this study used the comprehensive evaluation method to realize the geological disasters risk assessment of the Maoxian-Wenchuan section along the G213 line, and analysed and discussed the causes and spatial distribution of geological disasters along the G213 line. Our study presents several key findings, (1) The order of impact degree of each impact factor is road network density, soil erosion, slope, human activities, vegetation coverage, rainfall, and slope aspect, among them, the road network density factor plays a leading role, and the aspect factor is the least impact factor; (2) The geological disasters risk in the study area is divided into five categories: extremely low risk, low risk, medium risk, high risk, and extremely high risk. In general, the geological disasters risk of the research road section is relatively high, and the risk area division is consistent with the historical disaster point data. The research results can provide reference for the smooth development and implementation of road geological disasters risk assessment in the mountainous areas in southwestern China.

Mining Subsidence Prediction Model and Parameters Inversion in Mountainous Areas

Coal mining in mountainous areas is general in China, especially in Shanxi Province. Under the influence of topography in mountainous areas, surface collapses and landslides caused by underground mining happen at a certain frequency and threaten human lives and assets. Accurate prediction of the movement and deformation of mining subsidence in mountainous areas facilitates the prevention and control of geological disasters. The probability integral method is an official prediction method for mining subsidence prediction in China, while it is lacking in the prediction accuracy in mountainous areas due to the inherent topography. Therefore, a practical prediction model based on slopes slip combined parameters optimization was proposed in this study. The slip subsidence and slip horizontal movement were deduced based on the probability integral method considering the topography (slope angle α < 30°) and geological conditions (loess covered) to build the prediction model. The dynamic step fruit fly optimization algorithm (DSFOA) was applied for parameters inversion about the probability integral method in the proposed prediction model, while the other parameters in the proposed model were determined by mechanics analysis based on the nature of losses. The determination of parameters is more efficient, objective and reasonable, so that the prediction accuracy can be improved. The measured data of the working panel 22,101 located in Taiyuan, Shanxi Province was verified by this practical model, and the result shows that the mean square error of subsidence and the horizontal movement was decreased to 71 mm and 276 mm, respectively, hence, the applicability of the proposed mining subsidence prediction model in mountainous areas is verified. This work will contribute to a comprehensive understanding on the law of surface movement and provide theoretical guidance for surface damage prevention and control in mountainous mining areas.

Application of Hydrogeology, Engineering Geology and Environmental Geology Technology in Prevention and Control of Geological Disasters

Application of Hydrogeology, Engineering Geology and Environmental Geology Technology in Prevention and Control of Geological Disasters

Analysis on the Practice of Grouting Technology in Geological Disaster Control

Analysis on the Practice of Grouting Technology in Geological Disaster Control

Landslide Susceptibility Assessment Considering Landslide Volume: A Case Study of Yangou Watershed on the Loess Plateau (China)

Because of the special geological conditions on the Loess Plateau, Landslide erosion is not only the main goal of prevention and control of geological disasters, but also an important erosion mode of soil and water loss in the basin. Thus, landslide susceptibility assessment before only considering landslide frequency is not far enough for a decision-maker. The study aims to consider both frequency and scale of landslides for a better landslide susceptibility evaluation. Taking the Yangou small watershed as an example, this study used a VR model, RIRA method, and the GIS method to comprehensively consider frequency and scale to analyze landslide susceptibility of the small watershed. Based on the detailed analysis of the existing literature, slope, elevation, NDVI, land-use, lithology, amount distant to road, amount distant to river, profile curvature, and rainfall as landslide are selected as the conditioning factors (CFs) of the landslide, to draw the sensitivity map. The map of landslide susceptibility was classified into five zones: very low, low, medium, high, and very high, and the cover areas occupy 6.90, 12.81, 12.83, 9.42, and 5.87 km2, respectively. A total of 60% of the landslide occurred in the zones of high and very high susceptibility, accounting for 87% of the total volume in the study area. The very high susceptibility is the area with a larger relief and along the river and road. The findings will help decision makers to formulate scientific comprehensive policies that take into account disaster prevention and soil conservation measures in specific regions.

Study on the Law of Subsidence of Overburden Strata above the Longwall Gob

In recent years, with the increase of depth and intensity of coal mining, geological disasters in deep engineering occur frequently. It is essential to study the law of subsidence of overburden after mining for analyzing the mechanism and control of geological disasters in deep engineering. However, the value of the subsurface subsidence factor and other overburden subsidence parameters could not be obtained easily. In this paper, the strata bulking of the caving zone, the bed separation of the fractured zone, and the dilatation of bending zone were considered a kind of expansion in the vertical direction uniformly. An assumption on vertical expansion value distribution of overburden strata above the longwall gob was proposed. Based on the assumption, a formula of the subsurface subsidence factor was deduced according to such parameters as the bulking factor, mining depth, mining height, and surface subsidence factor. Moreover, many field data were used to verify the correctness of the assumption by the data fitting method. The results show that the exponential function could well describe the expansion distribution characteristic of overburden strata and subsurface subsidence in the vertical direction. The parameter a in the deduced formula influences the shape of the subsurface subsidence curve; it is called the subsurface subsidence influence factor (SSIF). The SSIF, maximal vertical expansion value, and the mining depth-to-mining height ( MD / MH ) ratio influence the subsurface subsidence factor. The expansion distribution (E-D) factor is defined to describe the subsidence characteristic of overburden strata above the longwall gob by the surface subsidence factor and bulking factor of the caving zone. The E-D factor presents the logarithm relation with the MD / MH ratio, and the range of its maximum is 2.84~3.40. The case study demonstrates that the subsurface subsidence factor calculated by the proposed method has higher precision, and the mean errors between the calculated value and the measured value are less than 2%.

Geological Disaster Control Engineering Quality, Safety Management Countermeasures

Geological Disaster Control Engineering Quality, Safety Management Countermeasures

Early identification and monitoring of hidden debris flow in low mountain red bed area based on InSAR and optical remote sensing technology——A case study of Wenjiagou debris flow in the Eastern New District of Chengdu

Because of the typical geological environment and climate conditions, the number of debris flow geological disasters in low mountain red bed area is small, and most of them have high concealment. Identifying and monitoring debris flow under this kind of special disaster pregnant background has a certain significance for the prevention and control of geological disasters. Taking Wenjiagou debris flow in Danjing street, Eastern New District of Chengdu as an example, this paper uses InSAR technology and optical remote sensing technology to identify and monitor Wenjiagou debris flow by multi-period, multi-source and multi-means method. Combined with the geological environment conditions of red bed area, this paper comprehensively analyzes the causes and development characteristics of Wenjiagou debris flow. Research shows:1) The debris flow in Wenjiagou is very hidden. The source of landslide in the early stage can be detected by using InSAR technology, which has certain deformation characteristics. 2) Using multi- period optical remote sensing images, the partial slope deformation can be identified in the study area, and the debris flow can be effectively identified in the early stage. 3) The provenance of Wenjiagou debris flow is mainly controlled by geological structure and stratum lithology. Finally, combined with the results of remote sensing interpretation and ground survey, the paper puts forward the targeted prevention and control suggestions of “Stable material source + Combination of blocking and drainage + Ecological restoration” for Wenjiagou debris flow, which has a certain guiding role for the development and planning of the Eastern New District of Chengdu.

The Formation Mechanism of Surface Landslide Disasters in the Mining Area under Different Slope Angles

Slope stability analysis is important for the safe mining of mineral resources. The collapse of goafs in loess gullies can lead to natural disasters such as surface landslides. In this context, this study analyzes monitoring data obtained from surface observation in the Shendong mining area of the Hanjiawan coal mine based on the geological conditions therein. The monitoring results show that the working face experiences a starting period, an active period, and a declining period, from the start of mining to the end of the working face. At the initial mining stage, there is no evident surface movement or deformation in the mining area. When the advance distance of the 12106 working face is between 13 m and 109 m, the surface movement and deformation vary significantly, and the maximum subsidence reaches 1963 mm, which is enough to cause landslides. We select the physical and mechanical parameters of the rock and soil in the mine and then simulate the formation mechanism of surface landslides under different slope angles of the mining area using FLAC3D software. Because of the collapse of the mined-out area, the overlying strata structure is destroyed, the subsidence basin is shifted to the center as a whole, and the slope mass is subjected to tensile and compression deformation, resulting in plastic damage, which develops downward along the crack and leads to a collapse because of the discontinuous movement and deformation of the surface; moreover, step-type ground fissures are produced. The results also show that when the slope angle is greater than 60°, the displacement of the slope mass is not uniform, and the rock stratum in a position with large displacement loses its support, leading to landslides; when the slope angle is less than 30°, the bedrock surface forms a sliding surface and develops to the surface, thus decreasing the possibility of landslides. Based on the stability analysis of the collapsed slope in the goaf of the loess gully, a scientific basis is provided for the effective prevention and control of geological disasters in the Shendong mining area.