GIS based landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal, India using binary logistic regression analysis

Landslide susceptibility mapping is the first step in regional hazard management as it helps to understand the spatial distribution of the probability of slope failure in an area.An attempt is made to map the landslide susceptibility in Tevankarai Ar subwatershed,Kodaikkanal,India using binary logistic regression analysis.Geographic Information System is used to prepare the database of the predictor variables and landslide inventory map,which is used to build the spatial model of landslide susceptibility.The model describes the relationship between the dependent variable(presence and absence of landslide) and the independent variables selected for study(predictor variables) by the best fitting function.A forward stepwise logistic regression model using maximum likelihood estimation is used in the regression analysis.An inventory of 84 landslides and cells within a buffer distance of 10m around the landslide is used as the dependent variable.Relief,slope,aspect,plan curvature,profile curvature,land use,soil,topographic wetness index,proximity to roads and proximity to lineaments are taken as independent variables.The constant and the coefficient of the predictor variable retained by the regression model are used to calculate the probability of slope failure and analyze the effect of each predictor variable on landslide occurrence in thestudy area.The model shows that the most significant parameter contributing to landslides is slope.The other significant parameters are profile curvature,soil,road,wetness index and relief.The predictive logistic regression model is validated using temporal validation data-set of known landslide locations and shows an accuracy of 85.29 %.     

Landslides in the Central Coalfield (Cantabrian Mountains, NW Spain): Geomorphological features, conditioning factors and methodological implications in susceptibility assessment

A geomorphological study focussing on slope instability and landslide susceptibility modelling was performed on a 278 km² area in the Nalón River Basin (Central Coalfield, NW Spain). The methodology of the study includes: 1) geomorphological mapping at both 1:5000 and 1:25,000 scales based on air-photo interpretation and field work; 2) Digital Terrain Model (DTM) creation and overlay of geomorphological and DTM layers in a Geographical Information System (GIS); and 3) statistical treatment of variables using SPSS and development of a logistic regression model. A total of 603 mass movements including earth flow and debris flow were inventoried and were classified into two groups according to their size. This study focuses on the first group with small mass movements (10⁰ to 10¹ m in size), which often cause damage to infrastructures and even victims. The detected conditioning factors of these landslides are lithology (soils and colluviums), vegetation (pasture) and topography. DTM analyses show that high instabilities are linked to slopes with NE and SW orientations, curvature values between − 6 and − 0.7, and slope values from 16° to 30°. Bedrock lithology (Carboniferous sandstone and siltstone), presence of Quaternary soils and sediments, vegetation, and the topographical factors were used to develop a landslide susceptibility model using the logistic regression method. Application of “zoom method” allows us to accurately detect small mass movements using a 5-m grid cell data even if geomorphological mapping is done at a 1:25,000 scale.     

强磁性体ΔT异常计算的误差分析研究

本文主要针对当前磁法勘探中高精度处理解释的需求,对强磁性体ΔT异常计算存在的误差进行分析研究.我们首先通过理论模型计算试验,证明常规计算采用的投影关系的ΔT与实际测量的模量差ΔT之间的误差E在磁异常幅值大时是明显存在的,其影响不容忽视.其次,当磁性强且剩磁存在时,投影ΔT曲线及其误差曲线在磁化方向与地磁场方向改变时具有一定的对称性;地磁场T0、磁性体形态(如二度水平圆柱体模型的半径r、柱体埋深R)和磁性参数(如磁化率κ)等参数确定的情况下,最大误差值出现在磁性体正上方,且其大小与磁性参数(κ)和模型体规模(如r/R)之间皆是指数关系;另外,研究还发现ΔT的计算误差曲线的一些其他规律特点,如在各纬度带上,ΔT计算误差的最大值Emax曲线的极值主要分布在中纬度地区;磁异常矢量 T a与地磁场 T 0的夹角θ逐渐变化时,随θ变化Emax曲线的极值分布在θ=90°~120°范围内;当磁异常幅值小于10000 nT时,最大误差近似为磁异常矢量垂直于地磁场方向的测点附近的误差值;另外,磁性体(圆柱体为例)的半径(即尺度)与埋深的比值r/R超过0.5,且磁化率超过0.1SI时误差已达到3.9 nT,磁化率增大与对应的Emax的值呈指数增长特点.因此,我们的研究表明,在强磁性体、磁异常幅值大的数据处理、反演及解释时,现有方法会产生较大的误差,应该基于严格的模量差ΔT,完善相应的处理以及反演方法.     

联合DBSCAN聚类采样和SVM分类的滑坡易发性评价

针对基于机器学习的滑坡易发性评价中非滑坡样本选取不规范导致的分类精度较低问题,本文提出联合基于密度的噪声应用空间聚类（Density-Based Spatial Clustering of Applications with Noise,DBSCAN）采样策略和支持向量机（Support Vector Machine,SVM）分类方法的DBSCAN-SVM滑坡易发性评价模型。首先,基于DBSCAN聚类和空间分析选取非滑坡样本;然后,将样本数据代入SVM分类模型进行训练与验证,预测并提取SVM分类中属于滑坡的概率,获得滑坡易发性;最后,以四川省绵阳市为试验区,预测滑坡易发性概率,基于滑坡易发性精度与分级结果等要素,与传统非滑坡样本采集策略的SVM滑坡易发性评价模型进行对比,并结合实际情况对DBSCAN-SVM模型评价结果进行分析。研究结果表明,相比传统SVM滑坡易发性评价模型,本文提出的DBSCAN-SVM滑坡易发性评价模型在高易发区和极高易发区中包含的滑坡样本数量较多,准确率、召回率、AUC、F1分数均得到提高,精度较高。     

GIS-based detachment susceptibility analyses of a cut slope in limestone, Ankara—Turkey

Due to the rapidly growing population of the city of Ankara (Turkey) and increased traffic congestion, it has become necessary to widen the Ankara-Eskişehir (E-90) highway connecting the newly built areas west of the city to the city center. During widening, several cut slopes were formed along the highway route. As a result, some instability problems (small-sized rock falls/sliding, sloughing, raveling) produced detachment zones along a cut slope in highly jointed, folded and sheared limestone, causing local degradation of the cut slope. Identification of the areas that are likely to detach from the cut slope in the future is considered to be very important for the application of remedial measures. For this purpose, the relationships between the existing detachment zones and various parameters (e.g., point load strength index, weathering, block size, daylighting, shear zone) were investigated using GIS-based statistical detachment susceptibility analyses in order to predict the further aerial extension of the detachment zones with time. During the overlay analyses, statistical index and weighting factor methods were used. The outcomes of the analyses were compared and evaluated with the field observations to check the reliability of the methods and to assess the detachment zones that may develop in the future. The detachment susceptibility map without the block-size layer gives the best result and indicates some risky zones where detachments are likely to occur in the future. Recommendations on remedial measures of the cut slope should consider these risky zones.     

Managing expert-information uncertainties for assessing collapse susceptibility of abandoned underground structures

Assessing the collapse susceptibility of abandoned cavities at a regional scale is associated with large uncertainties that are mainly related to the very nature of the phenomena, but also to the difficulty in collecting exhaustive information at such a scale on often “forgotten” structures. In this context, the expert's role is essential, because he is able to synthesize the information resulting from the inventory and from the commonly imprecise, if not vague, criteria on the basis of his experience and his knowledge of the geological, historical, economic regional context.In this article, we propose mathematical tools for representing and processing this information in order to give flexibility to this step and manage the uncertainty inherent in the expert's information. The first tool, based on the weight of evidence theory, is for managing the uncertainty due to the heterogeneous spatial distribution of the data, whereas the second tool, based on the fuzzy set theory, is for managing the imprecision and incompleteness of available data, which hinder the definition of the class boundaries of the quantitative decision criteria. Based on an appropriate representation of the uncertainty sources (related to the input data and to the expert diagnostic), we then propose a methodology that integrates the uncertainty in the final output of the collapse susceptibility assessment and provides a confidence indicator useful within the decision-making process. The proposed methodology is applied to the Arras territory in the North of France, where abandoned chalk pits (dating back to the Roman ages) and war saps located in the vicinity of the First World War front lines (i.e. covered trenches), raise both difficulties for urban planning.     

变形岩石磁性各向异性及其应变相关性的模拟

本文介绍处于弱磁场中的磁性砂岩人工样品,在三种应变作用下磁化率各向异性特征的研究结果.结果表明,磁化率椭球与应变椭球之间,显示了密切的相关性.文中并对上述情况下,磁化率各向异性特征及剩磁特征,从机理上进行了分析.     

曹岘黄土和小良山红土剖面磁化率解释机制的差异

磁化率因其磁测方法快捷、简便和没有破坏性的优点,作为一种研究手段以利用环境物质的磁性来恢复古环境,分析磁性矿物在环境系统中的迁移、转化和组合规律等方面,得到了快速而广泛的应用,取得了一系列研究成果。事实上影响沉积物磁化率的因素是多种多样的,因此在具体应用磁化率分析古环境上要持慎重态度,并结合其他实验结果进行解释,尤其要注意沉积类型的差别对解释磁化率结果的影响。为进一步分析磁化率对古环境的指示意义,本文选取黄土和红土两种沉积类型进行磁化率测试,了解不同类型沉积物的磁化率指示意义,为正确解析磁化率提供依据。