Application of oblique photogrammetry technique in geological hazard identification and decision management

With the continuous development of the oblique photography technique, it has been used more and more widely in the field of geological disasters. It can quickly obtain the three-dimensional(3D) real scene model of dangerous mountainous areas under the premise of ensuring the safety of personnel while restoring the real geographic information as much as possible. However, geological disaster areas are often accompanied by many adverse factors such as cliffs and dense vegetation. Based on this, the paper introduced the flight line design of oblique photogrammetry, analyzed the multi-platform data fusion processing, studied the multi-period data dynamic evaluation technology and proposed the application methods of data acquisition, early warning, disaster assessment and decision management suitable for geological disaster identification through the analysis of actual cases, which will help geologists to plan and control geological work more scientifically and rationally, improve work efficiency and reduce the potential personnel safety hazards in the process of geological survey, to offer technical support to the application of oblique photogrammetry in geological disaster identification and decision making and provide the scientific basis for personal and property safety protection and later-stage geological disaster management in disaster areas.

Regional Integrated Meteorological Forecasting and Warning Model for Geological Hazards Based on Logistic Regression

Information model is adopted to integrate factors of various geosciences to estimate the susceptibility of geological hazards. Further combining the dynamic rainfall observations, Logistic regression is used for modeling the probabilities of geological hazard occurrences, upon which hierarchical warnings for rainfall-induced geological hazards are produced. The forecasting and warning model takes numerical precipitation forecasts on grid points as its dynamic input, forecasts the probabilities of geological hazard occurrences on the same grid, and translates the results into likelihoods in the form of a 5-level hierarchy. Validation of the model with observational data for the year 2004 shows that 80% of the geological hazards of the year have been identified as ＂likely enough to release warning messages＂. The model can satisfy the requirements of an operational warning system, thus is an effective way to improve the meteorological warnings for geological hazards.

Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

Assessing model of highway slope stability based on optimized SVM

Considering the geological hazards attributed to the highway slope,using a common simple model cannot accurately assess the stability of the slope.First,principal component analysis(PCA)was conducted to extract the principal components of six factors(namely,bulk density,cohesion,internal friction angle,slope angle,slope height,and pore water pressure ratio)affecting the slope stability.Second,four principal components were adopted as input variables of the support vector machine(SVM)model optimized by genetic algorithm(GA).The output variable was slope stability.Lastly,the assessing model of highway slope stability based on PCA-GA-SVM is established.The maximal absolute error of the model is 0.0921 and the maximal relative error is 9.21%by comparing the assessment value and the practical value of the test sample.The above studies are conducive to enrich the assessing model of highway slope stability and provide some reference for highway slope engineering treatment.

Deformation and failure of a high-steep slope induced by multi-layer coal mining

During underground mining,accurate revelation on the deformation and failure mechanisms of a high-steep slope under multi-layer mining conditions facilitates the prevention and control of geological disasters in mines.Numerical simulation based on discrete element theory can be used to explore the characteristics and mechanism of action of deformation and failure of a slope under complex geological and multi-layer mining conditions.By utilising PFC2 D(particle flow code) software,the deformation and failure characteristics of a high-steep slope in Faer Coal Mine in Guizhou Province,China were investigated.Additionally,the mechanism of influence of different numbers of mining layers on the deformation and failure of the high and steep slope was elucidated.The result showed that after the goaf passed by the slope toe,multi-layer mining aggravated the subsidence and deformation of the slope toe:the slope toppled forward as it sank.The toppling of the slope changed the slope structures:the strata in the front of the slope were transformed from anti-dip to down-dip features.Extruded by collapsedtoppled rock mass,the slope toe and the rock mass located in the lower part of the slope toe generally exhibited a locking effect on the slope.Multi-layer mining degraded the overall stability of the slope,in that the total displacement of the slope was much greater than the total mining thickness of the coal seams.Based on the aforementioned research,ideas for preventing and controlling geological disasters during mining operations under a high-steep slope were proposed.

Experimental study on slope sliding and debris flow evolution with and without barrier

A constitutive model on the evolution of debris flow with and without a barrier was established based on the theory of the Bingham model. A certain area of the Laoshan Mountain in Nanjing, Jiangsu Province, in China was chosen for experimental study, and the slope sliding and debris flow detection system was utilized. The change curve of the soil moisture content was attained, demonstrating that the moisture content of the shallow soil layer increases faster than that of the deep soil layer, and that the growth rate of the soil moisture content of the steep slope is large under the first weak rainfall, and that of the gentle slope is significantly affected by the second heavy rainfall. For the steep slope, slope sliding first occurs on the upper slope surface under heavy rainfall and further develops along the top platform and lower slope surface, while under weak rainfall the soil moisture content at the lower part of the slope first increases because of the high runoff velocity, meaning that failure occurring there is more serious. When a barrier was placed at a high position on a slope, debris flow was separated and distributed early and had less ability to carry solids, and the variation of the greatest depth of erosion pits on soil slopes was not significant.

The Studies of Slope Stability Around Gilgel Gibe-ⅡHydroelectric Project,Southwest of Ethiopia

The hillside and road cuttings of most parts of the north,south and western regions of the Ethiopian Plateau have a record of instability.Landslide-generated problems claimed many lives and property damages in the country.On the road from town Fofa to Gilgel GibeⅡproject instability problem is common.Since the area is extremely rugged,the variation in the elevation is very large and

Engineering geological conditions and features of geologic hazards in Wudongde reservoir of Jinshajiang River valley

There is a great difference between the distribution and evolvement characteristics of slope geological hazard in the same geographical location and climatic conditions,taking the similar structural-genetic connection in Wudongde reservoir area of Jinshajiang River valley for example. In all engineering geological conditions,the chronologic age and attitude of strata,and the lithologic association factors control the distributions and evolvement characteristics of slope geological hazard in the studied area. The study shows that the slopes in geological evolution are in different stages. The conclusion helps to understand the types and the intensity of geological disasters.

Exploring mechanism of hidden,steep obliquely inclined bedding landslides using a 3DEC model:A case study of the Shanyang landslide in Shaanxi Province,China

Catastrophic geological disasters frequently occur on slopes with obliquely inclined bedding structures(also referred to as obliquely inclined bedding slopes),where the apparent dip sliding is not readily visible.This phenomenon has become a focal point in landslide research.Yet,there is a lack of studies on the failure modes and mechanisms of hidden,steep obliquely inclined bedding slopes.This study investigated the Shanyang landslide in Shaanxi Province,China.Using field investigations,laboratory tests of geotechnical parameters,and the 3DEC software,this study developed a numerical model of the landslide to analyze the failure process of such slopes.The findings indicate that the Shanyang landslide primarily crept along a weak interlayer under the action of gravity.The landslide,initially following a dip angle with the support of a stable inclined rock mass,shifted direction under the influence of argillization in the weak interlayer,moving towards the apparent dip angle.The slide resistance effect of the karstic dissolution zone was increasingly significant during this process,with lateral friction being the primary resistance force.A reduction in the lateral friction due to karstic dissolution made the apparent dip sliding characteristics of the Shanyang landslide more pronounced.Notably,deformations such as bending and uplift at the slope’s foot suggest that the main slide resistance shifts from lateral friction within the karstic dissolution zone to the slope foot’s resistance force,leading to the eventual buckling failure of the landslide.This study unveils a novel failure mode of apparent dip creep-buckling in the Shanyang landslide,highlighting the critical role of lateral friction from the karstic dissolution zone in its failure mechanism.These insights offer a valuable reference for mitigating risks and preventing disasters related to obliquely inclined bedding landslides.

Deformation,structure and potential hazard of a landslide based on InSAR in Banbar county,Xizang(Tibet)

The Tibetan Plateau is characterized by complex geological conditions and a relatively fragile ecological environment.In recent years,there has been continuous development and increased human activity in the Tibetan Plateau region,leading to a rising risk of landslides.The landslide in Banbar County,Xizang(Tibet),have been perturbed by ongoing disturbances from human engineering activities,making it susceptible to instability and displaying distinct features.In this study,small baseline subset synthetic aperture radar interferometry(SBAS-InSAR)technology is used to obtain the Line of Sight(LOS)deformation velocity field in the study area,and then the slope-orientation deformation field of the landslide is obtained according to the spatial geometric relationship between the satellite’s LOS direction and the landslide.Subsequently,the landslide thickness is inverted by applying the mass conservation criterion.The results show that the movement area of the landslide is about 6.57×10^(4)m^(2),and the landslide volume is about 1.45×10^(6)m^(3).The maximum estimated thickness and average thickness of the landslide are 39 m and 22 m,respectively.The thickness estimation results align with the findings from on-site investigation,indicating the applicability of this method to large-scale earth slides.The deformation rate of the landslide exhibits a notable correlation with temperature variations,with rainfall playing a supportive role in the deformation process and displaying a certain lag.Human activities exert the most substantial influence on the spatial heterogeneity of landslide deformation,leading to the direct impact of several prominent deformation areas due to human interventions.Simultaneously,utilizing the long short-term memory(LSTM)model to predict landslide displacement,and the forecast results demonstrate the effectiveness of the LSTM model in predicting landslides that are in a continuous development and movement phase.The landslide is still active,and based on the spatial heterogeneity of landslide deformation,new recommendations have been proposed for the future management of the landslide in order to mitigate potential hazards associated with landslide instability.

Geometry and Maximum Width of a Stable Slope Considering the Arching Effect

The stability of an arching slope in deformable materials above strong rocks strongly depends on the shape and width of the span.Equations for a free surface problem that incorporate these two parameters were derived using a simplified two-dimensional arching slope model,and were validated using physical model tests under 1 g and centrifugal conditions.The results are used to estimate the maximum excavation width for a weak claystone slope in a lignite mine,for which we calculate a safety factor of 1.31.

基于无人机倾斜摄影测量三维建模的区域黄土滑坡识别及特征分析

【研究目的】黄土滑坡是黄土地区人居与城镇建设安全的重大隐患。滑坡识别是滑坡灾害及其他研究工作的基础,因此基于无人机倾斜摄影测量三维建模从不同维度、不同视角直观快速地识别黄土滑坡并进行特征参数提取,能够为黄土滑坡风险识别及风险管理精细化研究提供技术支撑。【研究方法】以宁夏回族自治区固原市彭阳县红河镇西南部的黑牛沟村为研究区,采用无人机倾斜摄影测量数据获取、三维建模、现场验证结合地统计学分析,开展了区域黄土滑坡识别及其特征参数提取和分析。【研究结果】基于三维实景模型确定并分析研究区沟谷沿线地貌凹陷区是否存在陡壁及其周界形态,结合色调、纹理和微地貌等标志实现了黄土滑坡识别,共圈定了23个滑坡,结合现场验证移除2个非滑坡点,最终确定了21个滑坡;滑坡密集分布在主沟和支沟沟口,多呈对滑的形式出现在沟谷两侧且具有群发性;大型及特大型滑坡占比达到57.14%,滑坡的滑动方向主要以西南(阳坡)、东南(半阳坡)为主,相对高差集中在80~120 m,滑坡体坡形多呈凹形坡,滑坡体坡度主要集中在20°~30°;滑坡体土地利用类型主要为植被,其次为裸地,也有一部分为农田,道路和河流占比极少。【结论】基于无人机倾斜摄影测量构建的三维实景模型可从多维度、多视角精确快速地识别区域黄土滑坡,并分析其相关特征参数,能够弥补当前二维平面遥感影像存在的不足;还能够为滑坡易发性、危险性、易损性及风险评估等相关研究提供数据支撑。

云南省地质灾害气象风险预警技术改进及应用检验

利用2014—2022年云南省地质灾害数据和气象降水资料,开展有效降水量致灾概率研究,并结合地质灾害易发因子,分区建立了新一代精细化地质灾害气象风险预警模型,并对模型性能开展了应用检验。结果表明:新建的地质灾害气象风险预警模型提高了预警产品的时空分辨率和准确率,应用效果良好。模型能提前较好地反映出区域性强降水过程背景下的气象风险预警等级;对较难预报的局地强降水,也可以通过实时更新的监测预警产品给出风险加强的趋势,提前发出地质灾害气象风险预警信息;能直接客观反映出极端强降水背景下的气象风险高级别预警,起到较好的预警提示作用。

地质灾害易发性评价方法综述

我国地形地质条件复杂,地质灾害多发,人类各类工程地质活动加剧了地质灾害的发生与发展.地质灾害预防与管理工作是保障人民生命与财产安全的前提与基础.地质灾害易发性评价是地质灾害危险性评价和风险评价的前提,也是地质灾害区划和防治工作的基础.本文基于国内外地质灾害易发性的相关研究,对地质灾害易发性概念、评价指标体系、权重计算方法和易发性评价模型进行分析总结,并指出了地质灾害易发性评价中亟待解决的主要问题.

Extensive identification of landslide boundaries using remote sensing images and deep learning method

The frequent occurrence of extreme weather events has rendered numerous landslides to a global natural disaster issue.It is crucial to rapidly and accurately determine the boundaries of landslides for geohazards evaluation and emergency response.Therefore,the Skip Connection DeepLab neural network(SCDnn),a deep learning model based on 770 optical remote sensing images of landslide,is proposed to improve the accuracy of landslide boundary detection.The SCDnn model is optimized for the over-segmentation issue which occurs in conventional deep learning models when there is a significant degree of similarity between topographical geomorphic features.SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block(ASPC)with a coding structure that reduces model complexity.The experimental results demonstrate that SCDnn can identify landslide boundaries in 119 images with MIoU values between 0.8and 0.9;while 52 images with MIoU values exceeding 0.9,which exceeds the identification accuracy of existing techniques.This work can offer a novel technique for the automatic extensive identification of landslide boundaries in remote sensing images in addition to establishing the groundwork for future inve stigations and applications in related domains.

信息量确定系数耦合模型的地质灾害易发性评价——以铜陵义安区为例

目的为研究地质灾害所带来的人员伤亡和财产损失等问题。方法以铜陵义安区为例,选取坡度、地形起伏度、工程地质岩组、距断层距离、斜坡结构、归一化植被指数(NDVI)6个评价因子,采用信息量模型(I)、确定系数模型(CF)及I-CF耦合模型建立义安区地质灾害易发性评价体系,利用受试者工作特征(ROC)曲线对模型进行对比和分析。结果坡度、地形起伏度对义安区地质灾害易发性评价影响程度较大的主要因子;信息量模型、确定系数模型、I-CF耦合模型的AUC值分别为0.890、0.884、0.913,说明,I-CF耦合模型预测精度优于另外两种单一模型。结论研究表明,采用I-CF耦合模型在义安区地质灾害易发性评价结果中效果更好,中、高易发区主要分布于南部、东南部及西部丘陵山区,主要涉及天门镇、顺安镇、新桥办事处、钟鸣镇及五松镇,该区域主要以矿业开发和城镇建设为主,同时地形起伏相对较大,植被覆盖较高,采矿现象普遍,灾害点比较集中,其中,采空塌陷地质灾害主要分布于天门镇、钟鸣镇和顺安镇一带,多为矿山早期开采遗留的老采空区导致,可对当地政府进行地质灾害防范工作具有重要指导意义。

基于BIM的公路边坡可视化管理方法研究

山地、丘陵地区的公路建设和运营中常伴有大量边坡,边坡的灾害问题已成为制约我国公路、铁路建设与运营发展的主要因素。目前,主流边坡信息化管理系统在信息集成领域存在缺陷,难以满足对各类复杂边坡科学监测与精细化管理的需求。为此,将BIM可视化技术引入到边坡监测与管理中,利用可视化模型“所见即所得”的优势与强大的数据集成能力改善沟通环境、提高管理效率。首先,通过地质钻孔数据解译结合地层层序优化逻辑确定地层层序、地层边界与分布范围,利用Dynamo节点开发基于钻孔数据的自动化建模程序,提出基于Revit+Dynamo的边坡地质BIM精细化建模方法。然后,提出联合OBJ-JSON格式储存模型关键属性信息的边坡模型轻量化导出方案,实现模型与地质信息的集成以及大体量边坡地质模型与Web的端互通,基于Three.js框架扩展WebGL原生代码优化BIM模型并开发了边坡BIM模型的Web端交互应用。最后,全方位分析涵盖项目全生命周期管理的内需并借助MySQL数据库技术将上述成果进行整合,开发了基于BIM的高速公路边坡的可视化监测管理平台并运用于实际工程。实例结果表明,基于平台建立的边坡可视化管理方案能够大幅提升案例公路边坡项目在运用阶段的管理水平与管理效率。研究为边坡信息化、可视化管理流程的制定和实施提供了参考。

基于路段单元的公路地质灾害风险气象预警系统

面向山区交通风险管控需求,以公路为承灾体对象的地质灾害风险气象预警研究具有重要意义。以浙江省磐安县方前镇为研究区,考虑道路等级、斜坡单元、边坡类型和边坡稳定性现状4个方面,研究确定公路地质灾害预警单元的划分方法;考虑历史地质灾害的发育规律,将公路边坡分为土质、岩质和土岩混合质边坡3种类型,分别建立不同类型边坡地质灾害易发性评价体系,并通过层次分析法计算各指标权重及分值;在确定各预警单元所辖边坡地质灾害易发性等级的基础上,结合研究区四级气象预警判据建立基于路段单元的公路地质灾害风险气象预警模型,采用Java语言开发预警系统。经与2021年“烟花”台风期新生公路地质灾害点验证发现,预警成功率为100%。研究结果提供了公路地质灾害风险气象预警单元的划分方法和系统研发思路,能够为山区公路地质灾害风险气象预警提供借鉴与参考。

不同降雨工况条件下的崩滑地质灾害危险性评价

为针对性地采取预防、避让、治理等地质灾害防治与管控提供依据,完善在地质灾害危险性评价中将降雨作为单一诱发因子参与评价体系的弊端,在大雨、暴雨、大暴雨和特大暴雨4种不同降雨工况条件下进行了研究区崩滑地质灾害危险性评价。以云南省元阳县作为研究区域,以栅格单元作为评价单元,选取地貌类型、高程、坡度、坡向、曲率、工程地质岩组、土地利用类型、断层距离和河流距离9个评价因子,采用主观的层次分析法与客观的信息量模型相结合的加权信息量模型对元阳县崩塌、滑坡进行了地质灾害易发性评价。研究结果表明:基于自然间断点法元阳县域可分为低、中、高、极高4类易发区,4类易发区面积分别占元阳县面积的21.55%,35.46%,25.53%和17.16%。利用ROC曲线得出区划结果精度AUC值为0.812,表明区划结果很好。在易发性评价基础上,以年平均最大日降雨量为诱发因素,分别对大雨、暴雨、大暴雨和特大暴雨4种工况条件下的研究区进行了崩塌、滑坡地质灾害危险性评价,得到了大雨([25,50) mm)工况、暴雨([50,100) mm)工况、大暴雨([100,250]mm)工况和特大暴雨(>250 mm)工况4种条件下基于极值假设的研究区崩滑地质灾害危险性评价结果,并对不同降雨工况条件下的地质灾害危险性评价结果进行了对比分析,确定了地质灾害危险性评价结果在不同降雨条件下的空间合理性。通过与实际调查结果的对比表明,4种不同降雨工况条件下的崩滑地质灾害危险性评价结果与实际高度吻合,说明评价结果具有较高的可靠性与合理性。

基于实景三维模型的地质灾害隐患识别——以广东省上坪镇为例

为了打破地质灾害中高位隐蔽性隐患发现难的局限,查清复杂地形下突发地质灾害的特点,实现地质灾害隐患点的精准识别。本研究以广东省连平县上坪镇为研究区域,基于无人机倾斜摄影测量技术构建高精度实景三维模型,生成点云、数字高程模型等衍生数据,在真三维环境中结合山体阴影进行隐患点识别,并结合实地调查对典型灾点的特征信息进行分析。结果表明:本研究识别的隐患点与现地验证情况一致,正确率达100%;共识别出隐患点23处(滑坡14处、崩塌9处),灾害密度约4处/km~2。本研究通过集成“空地联动”“点面体协同”“二三维一体”的方法,将立体灾害点搬进数字空间,实现了隐蔽性点位和调查盲区的全覆盖,对灾害预警和风险防控具有重要意义。