Relationships between landslide types and topographic attributes in a loess catchment, China

Topographic attributes have been identified as the most important factor in controlling the initiation and distribution of shallow landslides triggered by rainfall.As a result,these landslides influence the evolution of local surface topography.In this research,an area of 2.6 km 2 loess catchment in the Huachi County was selected as the study area locating in the Chinese Loess Plateau.The landslides inventory and landslide types were mapped using global position system(GPS) and field mapping.The landslide inventory shows that these shallow landslides involve different movement types including slide,creep and fall.Meanwhile,main topographic attributes were generated based on a high resolution digital terrain model(5 m × 5 m),including aspect,slope shape,elevation,slope angle and contributing area.These maps were overlaid with the spatial distributions of total landslides and each type of landslides in a geographic information system(GIS),respectively,to assess their spatial frequency distributions and relative failure potentials related to these selected topographic attributes.The spatial analysis results revealed that there is a close relation between the topographic attributes of the postlandsliding local surface and the types of landslide movement.Meanwhile,the types of landslide movement have some obvious differences in local topographic attributes,which can influence the relative failure potential of different types of landslides.These results have practical significance to mitigate natural hazard and understandgeomorphologic process in thick loess area.     

Regional landslide hazard assessment based on Distance Evaluation Model

There are many factors influencing landslide occurrence. The key for landslide control is to confirm the regional landslide hazard factors. The Cameron Highlands of Malaysia was selected as the study area. By bivariate statistical analysis method with GIS software the authors analyzed the relationships among landslides and environmental factors such as lithology, geomorphy, elevation, road and land use. Distance Evaluation Model was developed with Landslide Density(LD). And the assessment of landslide hazard of Cameron Highlands was performed. The result shows that the model has higher prediction precision.     

Using LIDAR and ground truth for landslide recognition and characterization of geotechnical and morphological parameters in sedimentary rocks,a case study in Northern Bavaria (Germany)

The use of LIDAR-derived shaded relief maps led to the identification of all potential landslide areas in a hilly region in Northern Bavaria (1590 km²), Germany. Every possible structure was investigated by field investigation which resulted in a detailed database of 1002 landslides within the study area. The analysis of geological, lithological, topographical and morphological properties (spatial ratio, lithological and geological setting, length/width distribution, material properties and slope angle) revealed characteristic appearances of the landslides and possible relationships between different aspects. Strong relations between the lithological setting, spatial ratio of the mapped landslides and distribution of slope angle could be observed. This study shows the value of high-resolution shaded relief maps for detecting and mapping landslides in a large area with comparatively little work and time in comparison to the traditional approach to mapping. It reveals that many landslides were not known before. Landslides are much more common in Northern Bavaria and have a higher influence on the denudation rate of the Franconian Alb than expected before.     

Landslide susceptibility analysis of Karakoram highway using analytical hierarchy process and scoops 3D

Landslides are prevalent, regular, and expensive hazards in the Karakoram Highway(KKH) region. The KKH connects Pakistan with China in the present China-Pakistan Economic Corridor(CPEC) context. This region has not only immense economic importance but also ecological significance. The purpose of the study was to map the landslide-prone areas along KKH using two different techniquesAnalytical Hierarchy Process(AHP) and Scoops 3 D model. The causative parameters for running AHP include the lithology, presence of thrust, land use land cover, precipitation, and Digital Elevation Model(DEM) derived variables(slope, curvature, aspect, and elevation). The AHP derived final landslide susceptibility map was classified into four zones, i.e., low, moderate, high, and extremely high. Over 80% of the study area falls under the moderate(43%) and high(40%) landslide susceptible zones. To assess the slope stability of the study area, the Scoops 3 D model was used by integrating with the earthquake loading data. The results of the limit equilibrium analysis categorized the area into four groups(low, moderate, high, and extremely high mass) of slope failure. The areas around Main Mantle Thrust(MMT) including Dubair, Jijal, and Kohistan regions, had high volumes of potential slope failures. The results from AHP and Scoops 3 D techniques were validated with the landslides inventory record of the Geological Survey of Pakistan and Google Earth. The results from both the techniques showed similar output that coincides with the known landslides areas. However, Scoops 3 D provides not only susceptible zones but also the range of volume of the potential slope failures. Further, these techniques could be used in other mountainous areas, which could help in the landslide mitigation measures.     

桂林-阳朔地区DEM地形特征与岩性相关性分析及分类研究

地形地貌是岩性解译的重要信息,地形因子作为描述DEM数字曲面几何特征的定量指标参数,可用来定量化表达不同岩性所在地区地形地貌特征。本文以桂林-阳朔地区为研究区,研究地形因子数学、地质意义,建立岩性与地形因子组合间的定量关联,进而实现岩石类型划分。本文基于ASTERGDEM提取坡度、起伏度等12个地形因子,在分析各个地形因子地质意义基础上,通过聚类分析及方差分析的多元统计分析方法,研究各岩性地形因子特性及其关联性,建立研究区岩性之间的定量差异;此外,利用因子分析方法研究岩性分类过程中的主导因素,确定适宜岩性分类方法以实现定量化岩性分类。实验结果表明：不同岩性、不同地形地貌的地形因子（组合）之间具有显著差异,基于因子分析得到的宏观地形复杂度指数（MTI）以及微观曲率指数（MCI）对岩石类型的分类精度达77.36%。研究表明,地形复杂度等地形因子可用于岩性分类,采用因子分析方法可获取反映地形地貌宏观、微观特征的定量指标,且岩性分类效果良好。     

Regional landslide hazard assessment based on Distance Evaluation Model

There are many factors influencing landslide occurrence. The key for landslide control is to confirm the regional landslide hazard factors. The Cameron Highlands of Malaysia was selected as the study area. By bivariate statistical analysis method with GIS software the authors analyzed the relationships among landslides and environmental factors such as lithology, geomorphy, elevation, road and land use. Distance Evaluation Model was developed with Landslide Density （LD）. And the assessment of landslide hazard of Cameron Highlands was performed. The result shows that the model has higher prediction precision.     

Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed,Gansu Province,China

Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups, (i) training dataset and (ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages, distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation.     

基于栅格最大值法的县域综合地质灾害建模

四川省地形高低悬殊, 岩性构造发育, 各类地质灾害频发, 开展地质灾害易发性评价具有重要意义。崩塌、泥石流属于广义上的滑坡, 以四川省丹巴县为例, 从考虑不同滑坡类别的区域性地质灾害易发性出发综合考虑崩塌、滑坡、泥石流的空间概率分布。基于ArcGIS通过高精度数字高程模型共选取高程、坡度等10个地质灾害关键控制因素, 采用信息量模型对综合地质灾害进行了易发性评价。最终通过ArcGIS的单元统计(Cell Statistics)功能实现多个栅格图层最大值法合成综合易发性, 进一步利用受试者工作特征曲线(ROC)验证单种滑坡类别易发性模型的精度。按照自然断点法将研究区划分为极低、低、中、高、极高易发区, 高易发区和极高易发区主要集中分布在章谷镇、太平桥乡以及甲居镇等地。研究结果证明信息量模型能对单类地质灾害进行评价, 栅格最大值法是获取综合易发性的一种有效评价方法。      

Landslide susceptibility assessment of the region affected by the 25 April 2015 Gorkha earthquake of Nepal

Nepal was hit by a 7.8 magnitude earthquake on 25^th April, 2015. The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal. We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork, using bivariate statistical model with different landslide causative factors. From the investigation, it is observed that most of the coseismic landslides are independent of previous landslides. Out of 3,716 mapped landslides, we used 80% of them to develop a susceptibility map and the remaining 20% were taken for validating the model. A total of 11 different landslide-influencing parameters were considered. These include slope gradient, slope aspect, plan curvature, elevation, relative relief, Peak Ground Acceleration (PGA), distance from epicenters of the mainshock and major aftershocks, lithology, distance of the landslide from the fault, fold, and drainage line. The success rate of 87.66% and the prediction rate of 86.87% indicate that the model is in good agreement between the developed susceptibility map and the existing landslides data. PGA, lithology, slope angle and elevation have played a major role in triggering the coseismic mass movements. This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.     

GIS-based evaluation on the fault motion-induced coseismic landslides

Earthquake-induced potential landslides are commonly estimated using landslide susceptibility maps. Nevertheless, the fault location is not identified and the ground motion caused by it is unavailable in the map. Thus, potential coseismic landslides for a specific fault motion-induced earthquake could not be predicted using the map. It is meaningful to incorporate the fault location and ground motion characteristics into the landslide predication model. A new method for a specific fault motion-induced coseismic landslide prediction model using GIS (Geographic Information System) is proposed herein. Location of mountain ridges, slope gradients over 45 o , PVGA (Peak Vertical Ground Accelerations) exceeded 0.15 g, and PHGA (Peak Horizontal Ground Accelerations) exceeded 0.25 g of slope units were representing locations that initiated landslides during the 1999 Chi-Chi earthquake in Taiwan. These coseismic landslide characteristics were used to identify areas where landslides occurred during Meishan fault motion-induced strong ground motions in Chiayi County in Taiwan. The strong ground motion (over 8 Gal in the database, 1 Gal = 0.01 m/s 2 , and 1 g = 981 Gal) characteristics were evaluated by the fault length, site distance to the fault, and topography, and their attenuation relations are presented in GIS. The results of the analysis show that coseismic landslide areas could be identified promptly using GIS. The earthquake intensity and focus depth have visible effects on ground motion. The shallower the focus depth, the larger the magnitude increase of the landslides. The GIS-based landslide predication method is valuable combining the geomorphic characteristics and ground motion attenuation relationships for a potential region landslide hazard assessment and in disaster mitigation planning.     

Rapid susceptibility mapping of co-seismic landslides triggered by the 2013 Lushan Earthquake using the regression model developed for the 2008 Wenchuan Earthquake

The primary objective of landslide susceptibility mapping is the prediction of potential landslides in landslide-prone areas.The predictive power of a landslide susceptibility mapping model could be tested in an adjacent area of similar geoenvironmental conditions to find out the reliability.Both the 2008 Wenchuan Earthquake and the 2013 Lushan Earthquake occurred in the Longmen Mountain seismic zone,with similar topographical and geological conditions.The two earthquakes are both featured by thrust fault and similar seismic mechanism.This paper adopted the susceptibility mapping model of co-seismic landslides triggered by Wenchuan earthquake to predict the spatial distribution of landslides induced by Lushan earthquake.Six influencing parameters were taken into consideration: distance from the seismic fault,slope gradient,lithology,distance from drainage,elevation and Peak Ground Acceleration(PGA).The preliminary results suggested that the zones with high susceptibility of coseismic landslides were mainly distributed in the mountainous areas of Lushan,Baoxing and Tianquan counties.The co-seismic landslide susceptibility map was completed in two days after the quake and sent to the field investigators to provide guidance for rescue and relief work.The predictive power of the susceptibility map was validated by ROC curve analysis method using 2037 co-seismic landslides in the epicenter area.The AUC value of 0.710 indicated that the susceptibility model derived from Wenchuan Earthquake landslides showed good accuracy in predicting the landslides triggered by Lushan earthquake.     

霍西煤矿区地表滑坡灾害敏感性数值建模与等级划分

本文以山西省霍西煤矿区为研究区,利用遥感和GIS方法对滑坡灾害的敏感性进行了数值建模与定量评价。利用交叉检验方法构建了径向基核函数支持向量机滑坡敏感性评价模型,并基于拟合精度对模型进行了定量评价;对各评价因子在模型中的重要性进行对比分析;基于空间分辨率为30m的评价因子,通过径向基核函数支持向量机模型获得了霍西煤矿区滑坡敏感性指数值,并利用分位数法将霍西煤矿区的滑坡敏感性分为极高、高、中和低4个等级。结果表明：拟合精度建模阶段和验证阶段分别为87.22%和70.12%;与滑坡敏感性关系最密切的5个评价因子依次是岩性、距道路距离、坡向、高程和土地利用类型;极高和高敏感区域分布了93.49%的滑坡点,面积占总面积的50.99%,是比较合理的分级方案。本研究不仅可以为研究区人工边坡调查和煤矿资源合理开采提供借鉴,对相似矿区的相关工作也具有参考价值。     

Analysing post-earthquake landslide susceptibility using multi-temporal landslide inventories——a case study in Miansi Town of China

The earthquake that occurred on May 12, 2008, in Wenchuan County aroused a great deal of research on co-seismic landslide susceptibility assessment, but there is still a lack of an evaluation method that considers the activity state of the landslide itself. Therefore, this paper establishes a new susceptibility evaluation model that superimposes the active landslide state based on previous susceptibility evaluation models. Based on a multi-phase landslide database, the probabilistic approach was used to evaluate landslide susceptibility in the Miansi town over many years. We chose the elevation, slope, aspect, and distance from the channel as trigger factors and then used the probability comprehensive discrimination method to calculate the probability of landslide occurrence. Then, the susceptibility results of each period were calculated by superposition with the activity rate. The results show that between 2008 and 2014, the proportion of areas with low landslide susceptibility in the study area was the largest, and the proportionof areas with the highest susceptibility was minimal. The landslide area with highest susceptibility gradually decreased from 2014 to 2017. However, in 2017, 15.06% of the area was still with high susceptibility, and relevant disaster prevention and reduction measures should be taken in these areas. The larger area under the receiver operating characteristic curve(AUC) indicates that the results of the landslide susceptibility assessment in this study are more objective and reliable than those of previous models. The difference in the AUC values over many years shows that the accuracy of the evaluation results of this model is not constant, and a greater number of landslides or higher landslide activity corresponds to a higher accuracy of the evaluation results.     

基于SBAS-InSAR的矿区采空区潜在滑坡综合识别方法

针对位于山区且受大量采空区影响的边坡,利用传统测量方法监测耗费人力、物力且光学遥感难以定量识别其是否为潜在滑坡的问题,本文提出一种融合研究区小基线集（SBAS-InSAR）地表监测数据、坡度及坡向的识别方法。通过SBAS-InSAR技术获得研究区地表雷达视线（LOS）方向形变速率,将其转化为垂直方向形变速率,并根据研究区DEM建立坡度及坡向分析图,根据不同山体的坡度、坡向找到易发生滑坡的区域,融入该区域垂直方向的时序形变速率,对其进行滑坡识别。实验表明：卡房镇周边受采空区的影响较大,多数区域垂直方向年形变速率大于10 mm/a;通过本文方法对研究区潜在滑坡进行识别,发现在研究区的21处历史滑坡点中,有16处被识别为潜在滑坡,5处未被识别但也位于发生形变的区域内,表明本文方法对潜在滑坡的识别精度高,具有可行性。该研究为识别采空附近的潜在滑坡提供了一种新的思路,可以有效识别采空区附近山体边坡是否处于潜在的、不明显的滑动状态,对滑坡灾害具有预警作用。     

Failure analysis on a heavy rainfall-induced landslide in Huay Khab Mountain in Northern Thailand

On 28 th July 2018, a massive landslide occurred in a mountainous area in Northern Thailand. The landslide after ten days of heavy rainfall generated the movement of uphill mountain soil into the populated village. This study presents a comprehensive failure analysis of local rainfallinduced landslides based on topographical and geological information. Rainfall measurement data were gathered from two rainfall stations close to the study area. The rainfall records show that the total monthly rainfalls in 2018 were significantly higher than the average monthly rainfalls over the past decade. Site investigation started with an unmanned aerial photogrammetric survey to generate a digital elevation model. Then, dynamic probing test, microtremor survey, and electrical resistivity survey were carried out along undisturbed soils beside the failed slope to evaluate the thickness of the soft soil cover on top of the rock basement. During the site survey, residual soil samples were collected to determine engineering properties in the laboratory. Finally, a slope stability analysis was performed to assess the landslide hazard based on the results of aerial photogrammetric survey, field exploration, and laboratory tests. The slope stability analysis and rainfall records revealed that the Huay Khab landslide was mainly caused by an increase in the water content of residual soils due to the prolonged rainfall which led to a sharp decrease in the shear strength. This leads to the conclusion that the proposed landslide investigation program could be used to assess the potential of landslide failure due to prolonged rainfall on a local scale.     

基于逻辑回归模型和3S技术的思南县滑坡易发性评价

区域滑坡易发性评价对滑坡灾害防治具有重要意义，贵州省思南县由于其特殊的自然地理和地质条件，受滑坡地质灾害的影响非常严重，因此，非常有必要对思南县的滑坡易发性进行评价。在滑坡编录的基础上，采用由RS、GIS和GPS组成的3S技术，获取了思南县的数字高程模型、坡度、坡向、剖面曲率、坡长、岩土类型、地表湿度指数、距离水系的距离、植被覆盖度和地表建筑物指数10个滑坡影响因子；再在频率比和相关性分析的基础上，利用逻辑回归模型对思南县的滑坡易发性进行了评价并绘制了易发性分布图。结果表明:利用逻辑回归模型预测思南县滑坡易发性的准确率(AUC值)达到0.797，较为准确地预测出了思南县滑坡分布规律；极高和高滑坡易发区主要分布在高程低于600 m、地表坡度较大且以软质岩类为主的区域；而极低和低滑坡易发区主要分布在高程较高、地表坡度较小且以硬质岩类为主的区域。      

Hazard and population vulnerability analysis: a step towards landslide risk assessment

In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlán, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility,magnitude(area-velocity ratio) and landslide frequency of the area of interest were produced based on information derived from a geomorphological landslide inventory; the latter was generated by using very high resolution satellite stereo pairs along with information derived from other sources(Google Earth,aerial photographs and historical information).Estimations of landslide susceptibility were determined by combining four statistical techniques:(i) logistic regression,(ii) quadratic discriminant analysis,(iii) linear discriminant analysis, and(iv)neuronal networks. A Digital Elevation Model(DEM)of 10 m spatial resolution was used to extract the slope angle, aspect, curvature, elevation and relief.These factors, in addition to land cover, lithology anddistance to faults, were used as explanatory variables for the susceptibility models. Additionally, a Poisson model was used to estimate landslide temporal frequency, at the same time as landslide magnitude was obtained by using the relationship between landslide area and the velocity of movements. Then,due to the complexity of evaluating it, vulnerability of population was analysed by applying the Spatial Approach to Vulnerability Assessment(SAVE) model which considered levels of exposure, sensitivity and lack of resilience. Results were expressed on maps on which different spatial patterns of levels of landslide hazard and vulnerability were found for the inhabited areas. It is noteworthy that the lack of optimal methodologies to estimate and quantify vulnerability is more notorious than that of hazard assessments.Consequently, levels of uncertainty linked to landslide risk assessment remain a challenge to be addressed.     

基于修正Green-Ampt模型的降雨诱发区域浅层斜坡失稳灾害分析

由于具有类似的工程地质和水文地质条件, 在高度相关的降雨作用下, 同一个区域中的降雨诱发浅层斜坡失稳灾害常成群出现。在区域尺度预测浅层斜坡失稳灾害对滑坡灾害的防灾减灾工作具有重要的意义。为此, 提出了一种基于力学原理的降雨诱发浅层斜坡失稳灾害预测新模型RARIL。该模型采用修正Green-Ampt模型进行降雨入渗分析, 采用无限体边坡模型进行安全系数计算, 利用可靠度原理考虑区域斜坡稳定性分析中的参数不确定性。该模型具有可考虑降雨诱发浅层斜坡的失稳力学机理、可考虑区域内斜坡土体参数不确定性, 以及计算效率高、易于在GIS平台上实现等优点。案例分析表明, RARIL模型较为准确地预测了2010年8月12日11∶00至2010年8月14日9∶00期间强降雨在四川省汶川县映秀镇附近的303省道K0-K20段沿线区域引发的滑坡灾害, 研究结果证明RARIL模型在预测降雨诱发区域斜坡失稳灾害方面有很好的应用前景。      

Evaluating effectiveness of frequency ratio,fuzzy logic and logistic regression models in assessing landslide susceptibility: a case from Rudraprayag district,India

Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics (ROC) curve, spatially agreed area approach and seed cell area index (SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning.     

GIS based spatial data analysis for landslide susceptibility mapping

Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps,satellite image,field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e.,very high,high,moderate,low and very low. This map was validated using the existing landslide distribution in the area.