Probabilistic landslide hazard assessment at the basin scale

We propose a probabilistic model to determine landslide hazard at the basin scale. The model predicts where landslides will occur, how frequently they will occur, and how large they will be. We test the model in the Staffora River basin, in the northern Apennines, Italy. For the study area, we prepare a multi-temporal inventory map through the interpretation of multiple sets of aerial photographs taken between 1955 and 1999. We partition the basin into 2243 geo-morpho-hydrological units, and obtain the probability of spatial occurrence of landslides by discriminant analysis of thematic variables, including morphological, lithological, structural and land use. For each mapping unit, we obtain the landslide recurrence by dividing the total number of landslide events inventoried in the unit by the time span of the investigated period. Assuming that landslide recurrence will remain the same in the future, and adopting a Poisson probability model, we determine the exceedance probability of having one or more landslides in each mapping unit, for different periods. We obtain the probability of landslide size by analysing the frequency–area statistics of landslides, obtained from the multi-temporal inventory map. Assuming independence, we obtain a quantitative estimate of landslide hazard for each mapping unit as the joint probability of landslide size, of landslide temporal occurrence and of landslide spatial occurrence.     

Terrain Pattern Recognition and Spatial Decision Making for Regional Slope Stability Studies

A terrain partition scheme is presented that allows the identification of regions with high landslide risk in natural terrain zones on the basis of geomorphometric criteria from moderate resolution DEMs. The key factor being the terrain segmentation to aspect regions (regions formed by points preserving the same aspect direction) instead of using an artificial regular-grid terrain partition scheme. The study area is in western Greece (NW Peloponnesus) whereas a moderate resolution digital elevation model with spacing 75 m is used. Landslide inventory analysis and knowledge conceptualization identified that the landslide susceptibility of a particular aspect region is high, if the mean elevation is low and the mean gradient is high. Each aspect region was parametrically represented on the basis of its mean gradient and elevation. The domain of each parameter was divided to seven slices (classes) on the basis of the observed density. Subsequent knowledge based mapping identified aspect regions with high landslide susceptibility for the following spatial rule: (a) “mean slope in class 6 or 7” and (b) “mean elevation in class 1 to 5”. Alternatively the rule is expressed as mean slope to be equal or greater than 15^∘ whereas mean elevation to be in the range 0 to 750 m. These identified zones correspond to regions where historical landslides occurred (populated coastal areas in the North) as well as to south regions (natural terrain zone) where no landslide record is available, because of the limitations posed by the natural terrain landslide mapping program in Greece. The presented terrain segmentation technique combined to the spatial decision-making process, provided both an object framework for integrating geomorphometric parameters and a method for landslide risk analysis in natural terrain zones.     

Automated landslide mapping using spectral analysis and high-resolution topographic data: Puget Sound lowlands, Washington, and Portland Hills, Oregon

Landslide inventory maps are necessary for assessing landslide hazards and addressing the role slope stability plays in landscape evolution over geologic timescales. However, landslide inventory maps produced with traditional methods — aerial photograph interpretation, topographic map analysis, and field inspection — are often subjective and incomplete. The increasing availability of high-resolution topographic data acquired via airborne Light Detection and Ranging (LiDAR) over broad swaths of terrain invites new, automated landslide mapping procedures. We present two methods of spectral analysis that utilize LiDAR-derived digital elevation models of the Puget Sound lowlands, Washington, and the Tualatin Mountains, Oregon, to quantify and automatically map the topographic signatures of deep-seated landslides. Power spectra produced using the two-dimensional discrete Fourier transform and the two-dimensional continuous wavelet transform identify the characteristic spatial frequencies of deep-seated landslide morphologic features such as hummocky topography, scarps, and displaced blocks of material. Spatial patterns in the amount of spectral power concentrated in these characteristic frequency bands highlight past slope instabilities and allow the delineation of landslide terrain. When calibrated by comparison with detailed, independently compiled landslide inventory maps, our algorithms correctly classify an average of 82% of the terrain in our five study areas. Spectral analysis also allows the creation of dominant wavelength maps, which prove useful in analyzing meter-scale topographic expressions of landslide mechanics, past landslide activity, and landslide-modifying geomorphic processes. These results suggest that our automated landslide mapping methods can create accurate landslide maps and serve as effective, objective, and efficient tools for digital terrain analysis.     

Comparing landslide inventory maps

Landslide inventory maps are effective and easily understandable products for both experts, such as geomorphologists, and for non experts, including decision-makers, planners, and civil defense managers. Landslide inventories are essential to understand the evolution of landscapes, and to ascertain landslide susceptibility and hazard. Despite landslide maps being compiled every year in the word at different scales, limited efforts are made to critically compare landslide maps prepared using different techniques or by different investigators. Based on the experience gained in 20 years of landslide mapping in Italy, and on the limited literature on landslide inventory assessment, we propose a general framework for the quantitative comparison of landslide inventory maps. To test the proposed framework we exploit three inventory maps. The first map is a reconnaissance landslide inventory prepared for the Umbria region, in central Italy. The second map is a detailed geomorphological landslide map, also prepared for the Umbria region. The third map is a multi-temporal landslide inventory compiled for the Collazzone area, in central Umbria. Results of the experiment allow for establishing how well the individual inventories describe the location, type and abundance of landslides, to what extent the landslide maps can be used to determine the frequency-area statistics of the slope failures, and the significance of the inventory maps as predictors of landslide susceptibility. We further use the results obtained in the Collazzone area to estimate the quality and completeness of the two regional landslide inventory maps, and to outline general advantages and limitations of the techniques used to complete the inventories.     

Pre-processing algorithms and landslide modelling on remotely sensed DEMs

Terrain analysis applications using remotely sensed Digital Elevation Models (DEMs), nowadays easily available, permit to quantify several river basin morphologic and hydrologic properties (e.g. slope, aspect, curvature, flow path lengths) and indirect hydrogeomorphic indices (e.g. specific upslope area, topographic wetness index) able to characterize the physical processes governing the landscape evolution (e.g. surface saturation, runoff, erosion, deposition). Such DEMs often contain artifacts and the automated hydrogeomorphic characterization of the watershed is influenced by terrain analysis procedures consisting in artificial depression (pit) and flat area treatment approaches combined with flow direction methods.In shallow landslide deterministic models, when applied using topographic dataset at medium scale (e.g. 30 m of resolution), the choice of the most suitable DEM-processing procedure is not trivial and can influence model results. This also affects the selection of most critical areas for further finer resolution studies or for the implementation of countermeasures aiming to landslide risk mitigation.In this paper such issue is investigated using as topographic input the ASTER DEMs and comparing two different combinations of DEM correction and flow routing schemes. The study areas comprise ten catchments in Italy for which hydrogeomorphic processes are significant. Aims of this paper are: 1) to introduce a parameter estimation procedure for the physically-based DEM correction method PEM4PIT (Physical Erosion Model for PIT removal); 2) to investigate the influence of different terrain analysis procedures on results of the slope stability model SHALSTAB (SHAllow Landsliding STABility) using remotely-sensed ASTER DEMs; 3) trying to assess which of terrain analysis methods is more appropriate for describing terrain instability.     

Analysis of LiDAR-derived topographic information for characterizing and differentiating landslide morphology and activity

This study used airborne laser altimetry (LiDAR) to examine the surface morphology of two canyon-rim landslides in southern Idaho. The high resolution topographic data were used to calculate surface roughness, slope, semivariance, and fractal dimension. These data were combined with historical movement data (Global Positioning Systems (GPS) and laser theodolite) and field observations for the currently active landslide, and the results suggest that topographic elements are related to the material types and the type of local motion of the landslide. Weak, unconsolidated materials comprising the toe of the slide, which were heavily fractured and locally thrust upward, had relatively high surface roughness, high fractal dimension, and high vertical and lateral movement. The body of the slide, which predominantly moved laterally and consists mainly of undisturbed, older canyon floor materials, had relatively lower surface roughness than the toe. The upper block, consisting of a down-dropped section of the canyon rim that has remained largely intact, had a low surface roughness on its upper surface and high surface roughness along fractures and on its west face (unrelated to landslide motion). The upper block also had a higher semivariance than the toe and body. The topographic data for a neighboring, older and larger landslide complex, which failed in 1937, are similarly used to understand surface morphology, as well as to compare to the morphology of the active landslide and to understand scale-dependent processes. The morphometric analyses demonstrate that the active landslide has a similar failure mechanism and is topographically more variable than the 1937 landslide, especially at scales > 20 m. Weathering and the larger scale processes of the 1937 slide are hypothesized to cause the lower semivariance values of the 1937 slide. At smaller scales (< 10 m) the topographic components of the two landslides have similar roughness and semivariance. Results demonstrate that high resolution topographic data have the potential to differentiate morphological components within a landslide and provide insight into the material type and activity of the slide. The analyses and results in this study would not have been possible with coarser scale digital elevation models (10-m DEM). This methodology is directly applicable to analyzing other geomorphic surfaces at appropriate scales, including glacial deposits and stream beds.     

Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression

This work has evaluated the probability of earthquake-triggered landslide occurrence in the whole of El Salvador, with a Geographic Information System (GIS) and a logistic regression model. Slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness are the predictor variables used to determine the dependent variable of occurrence or non-occurrence of landslides within an individual grid cell. The results illustrate the importance of terrain roughness and soil type as key factors within the model — using only these two variables the analysis returned a significance level of 89.4%. The results obtained from the model within the GIS were then used to produce a map of relative landslide susceptibility.     

数字地形分析在滑坡研究中的应用综述

高效的数字地形分析（Digital Terrain Analysis,DTA）是滑坡预测与评估研究的重要手段。文章综述了DTA在滑坡研究中的应用现状,基本内容包括地形因子分析、地形形态分析、地形单元划分以及DEM与滑坡模型的结合分析。地形因子分析的应用多而广,主要思路是在地形因子与滑坡发育的关系研究基础上分析其滑坡敏感性,进而构建滑坡预测和评估模型;地形形态分析是滑坡识别的重要手段,加强地貌形态和滑坡发育的关系研究有助于对潜在滑坡地形的识别;地形单元划分能为滑坡研究提供统计和分析单元;DEM与滑坡专业模型的结合方式多样,程度各异。同时,从尺度选择与转换的角度探讨了DTA滑坡研究的尺度问题,分析了DTA的局限性,指出DEM不能提供完备无误的地形信息,DTA不能完全取代常规的地形分析。最后,基于以上论述对未来的研究趋势提出了展望。     

The landslide response of alpine basins to post-Little Ice Age glacial thinning and retreat in southwestern British Columbia

The role of post-Little Ice Age (LIA) Neoglacial retreat on landslide activity is investigated in 19 alpine basins along the upper Lillooet River Valley, British Columbia. We examine how Neoglacial scouring and glacial recession have modified hillslope form and slope stability, and construct a decision-making flowchart to identify landslide hazards associated with glacial retreat. This work is based on field mapping, GIS analysis, statistical associations between landslides and terrain attributes, and a comparison between Neoglaciated and non-Neoglaciated terrain within each basin.The bedrock landslide response to glacial retreat varies appreciably according to lithology and the extent of glacial scour below the LIA trimline. Valleys carved in weak Quaternary volcanics show significant erosional oversteepening and contain deep-seated slope movement features, active rock fall, rock slides, and rock avalanches near glacial trimlines. Basins in stronger granitic rock rarely show increased bedrock instability resulting from post-LIA retreat, except for shallow-seated rock slides along some trimlines and failures on previously unstable slopes. In surficial materials, landslides associated with post-LIA retreat originate in till or colluvium, as debris slides or debris avalanches, and are concentrated along lateral moraines or glacial trimlines.Significant spatial association was also observed between recent catastrophic failures, gravitational slope deformation, and slopes that were oversteepened then debuttressed by glacial erosion. Eight out of nine catastrophic rock slope failures occurred just above glacial trimlines and all occurred in areas with a previous history of deep-seated gravitational slope movement, implying that this type of deformation is a precursor to catastrophic detachment.     

Qualitative landslide susceptibility assessment by multicriteria analysis: A case study from San Antonio del Sur, Guantánamo, Cuba

Geomorphological information can be combined with decision-support tools to assess landslide hazard and risk. A heuristic model was applied to a rural municipality in eastern Cuba. The study is based on a terrain mapping units (TMU) map, generated at 1:50,000 scale by interpretation of aerial photos, satellite images and field data. Information describing 603 terrain units was collected in a database. Landslide areas were mapped in detail to classify the different failure types and parts. Three major landslide regions are recognized in the study area: coastal hills with rockfalls, shallow debris flows and old rotational rockslides denudational slopes in limestone, with very large deep-seated rockslides related to tectonic activity and the Sierra de Caujerí scarp, with large rockslides. The Caujerí scarp presents the highest hazard, with recent landslides and various signs of active processes. The different landforms and the causative factors for landslides were analyzed and used to develop the heuristic model. The model is based on weights assigned by expert judgment and organized in a number of components such as slope angle, internal relief, slope shape, geological formation, active faults, distance to drainage, distance to springs, geomorphological subunits and existing landslide zones. From these variables a hierarchical heuristic model was applied in which three levels of weights were designed for classes, variables, and criteria. The model combines all weights into a single hazard value for each pixel of the landslide hazard map. The hazard map was then divided by two scales, one with three classes for disaster managers and one with 10 detailed hazard classes for technical staff. The range of weight values and the number of existing landslides is registered for each class. The resulting increasing landslide density with higher hazard classes indicates that the output map is reliable. The landslide hazard map was used in combination with existing information on buildings and infrastructure to prepare a qualitative risk map. The complete lack of historical landslide information and geotechnical data precludes the development of quantitative deterministic or probabilistic models.     

Landslide susceptibility analysis with a heuristic approach in the Eastern Alps (Vorarlberg, Austria)

The aim of the study is landslide hazard assessment carried out on a working scale of 1:25 000. The study area within the Northern Calcareous Alps was geologically and geotechnically mapped in order to identify causes and mechanisms of active mass movements. The field surveys were digitised by a Geographical Information System and divided into data layers. The geological units were classified according to their geotechnical properties. All layers were converted into grids and spatially analysed together with a Digital Elevation Model. Comparing the layers with the inventory of active landslides, the prevailing factors leading to sliding movements were identified. Because of the complex tectonic setting and the small number of active landslides, a statistical method of hazard assessment was not applicable. Using the heuristic approach of an index method, the data layers of geotechnical class, bedding conditions, tectonic layouts, slope angles, slope orientations, vegetation and erosion were analysed. The susceptibility of each layer has been evaluated with help of bivariate statistics. The layers have been weighted with indices due to their importance iteratively and were combined into a landslide susceptibility map.     

基于DEM的月球雨海地区粗糙度研究

月球表面粗糙度是揭示月表地貌形态空间分异特征的重要指标,并在一定程度上映射月表地貌的形成与演化机理。运用基于中国“嫦娥一号”卫星获取的DEM数据,提取月球雨海地区的月表粗糙度,并在月球正面地质图数据辅助下,分析月表粗糙度分布特征及其与地质单元岩性以及地质年龄的关系。结果显示:月球雨海地区的粗糙度与地质单元岩性存在较强相关关系,且随着地质年龄的增长,玄武岩单元的粗糙度呈现增大的趋势。此外,在小于7 km的尺度范围内,雨海地区受持续撞击作用的影响,Hurst指数分布在0.7~0.9之间,地形较为粗糙;在更大尺度上,由于受到火山熔岩流充填机制的控制,Hurst指数不断减小,地形不断趋于平缓。     

Susceptibility assessments of shallow earthflows triggered by heavy rainfall at three catchments by logistic regression analyses

Sometimes regional meteorological anomalies trigger different types of mass movements. In May 1998, the western Black Sea region of Turkey experienced such a meteorological anomaly. Numerous residential and agricultural areas and engineering lifelines were buried under the flood waters. Besides the reactivation of many previously delineated landslides, thousands of small-scale landslides (mostly the earthflow type) occurred all over the region. The earthflows were mainly developed in flysch-type units, which have already presented high landslide concentrations. In this study, three different catchments — namely Agustu, Egerci, and Kelemen — were selected because they have the most landslide-prone geological units of the region. The purposes of the present study are to put forward the spatial distributions of the shallow earthflows triggered, to describe the possible factors conditioning the earthflows, and to produce the shallow earthflow susceptibility maps of the three catchments. The unique condition units (UCU) were employed during the production of susceptibility maps and during statistical analyses. The unique condition units numbered 4052 for the Agustu catchment, 13,241 for the Egerci catchment and 12,314 for the Kelemen catchment. The earthflow intensity is the highest in the Agustu catchment (0.038 flow/UCU) and lowest in the Egerci catchment (0.0035 flow/UCU). Logistic regression analyses were also employed. However, during the analyses, some difficulties were encountered. To overcome the difficulties, a series of sensitivity analyses were performed based on some decision rules introduced in the present study. Considering the decision rules, the proper ratios of UCU free from earthflow (0) / UCU including the earthflow (1) for the Agustu, Egerci and Kelemen catchments were obtained as 3, 6, and 5, respectively. Also, a chart for the proper ratio selection was developed. The regression equations from the selected ratios were then applied to the entire catchment and the earthflow susceptibility maps were produced. The landslide susceptibility maps revealed that 15% of the Agustu catchment, 8% of the Egerci catchment, and 7% of the Kelemen catchment have very high earthflow susceptibility; and most of the earthflows triggered by the May 1998 meteorological event were found in the very high susceptibility zones.     

黄土丘陵沟壑区地形定量因子的关联性分析

不同地形因子虽然在语义概念、计算方法等方面均有明显的差异,但各地形因子之间并不是绝对孤立的,它们之间相互关联、相互影响。这种关联的强弱与趋势,都从不同角度揭示着地形起伏变化与地貌发育的本质及内在规律,同时,还在一定程度上映射着地表形态的发育过程。文章以黄土高原丘陵沟壑区的15个样本地区为实验样区,以高分辨率、高精度的1:1万比例尺DEM为基础数据,应用BP神经网络模型,探讨地形定量因子与地面坡度之间的关联性特征,并将神经网络的方法与传统的多元回归方法进行比较。结果表明,相对于传统的多元回归方法,带隐含层的BP神经网络分析方法能更为有效地反映地形因子间隐含的关联特征。该研究方法为进行地貌多定量指标的的选择和多因子之间关联性的量化提供了一种新的方法。     

地形对黄土高原滑坡的影响

高分辨率地形与影像数据的缺乏已成为研究地表现象、特征与过程的重要瓶颈。低成本无人机设备和摄影测量技术的发展,打开了地学领域获取高分辨率数据的大门,大大提高了地质灾害野外调查与灾害编目的精度与效率。本文通过无人机野外调查和遥感室内目视解译,构建了一个包含307个黄土滑坡属性的数据库。在此基础上,通过数字地形分析和数理统计等方法,总结归纳了黄土滑坡样本数据的分布规律,探讨了地形对黄土滑坡分布的影响,阐述了地形相对高差对最长滑动距离、滑坡周长、滑坡面积的影响,提出了基于传统经验公式拟合的滑坡规模快速预测公式。结果表明：① 滑坡规模—频率分布具有明显的规律性,不同最大长度、最大宽度和周长的黄土滑坡数量分布均呈现正偏态分布,而不同面积的滑坡数量分布则服从幂函数分布;② 地形对黄土滑坡发育控制作用明显,不同地形高差、平均坡度、坡形的斜坡单元滑坡发育数量差异较大;③ 地形相对高差与滑坡的最长滑距、周长和面积的拟合曲线很好地符合幂律分布规律,但不同地形区的拟合效果有所差异,黄土丘陵区拟合效果最好,黄土高原全区次之,黄土台塬区最差;④ 本文建立的黄土滑坡规模快速预测模型,为黄土滑坡灾害调查提供了经验公式支撑。     

Widespread syn-sedimentary deformation on a muddy deep-water basin-floor: the Vischkuil Formation (Permian), Karoo Basin, South Africa

The ∼380-m-thick mudstone–siltstone-dominated Vischkuil Formation represents the initiation phase of a 1.3-km-thick prograding basin floor to slope to shelf succession that marks a significant increase in the rate of siliciclastic sediment supply to the early Karoo Basin in the Permian. In the upper Vischkuil Formation three well exposed, widespread (∼3000 km²) 10–70-m-thick intervals of deformed strata are encased within undeformed sediments. Such chaotic mass movement deposits that are mappable over areas comparable with seismic-scale mass transport deposits are commonly associated with submarine slope settings. However, the surrounding lithofacies and the correlation of distinctive marker beds indicate that these deformation intervals developed in a distal low gradient basin floor setting. The deformed intervals comprise a lower division of tight down-flow verging folds dissected by thrust planes that sole out onto a highly sheared décollement surface that are interpreted as slides. The lower divisions are overlain by an upper division of chaotic lithofacies with large contorted clasts of sandstone supported by a fine-grained matrix interpreted as a debrite. The juxtaposition of these lithofacies, the distribution of thickness of the divisions, and their close kinematic relationships indicate that the emplacement of the debris-flows triggered and drove the underlying slide, in a low-gradient distal setting. Individual beds in the deformed intervals can be mapped laterally into undeformed strata indicating limited movement of the slide. Therefore, widespread zones of syn-sedimentary deformation in deep-water settings do not necessarily indicate a slope setting and should not be used as single criterion to determine depositional setting. When associated with major debrites they may be developed on a flat basin floor.     

Size and spatial distribution of loess slides on the Chinese Loess Plateau

ABSTRACT

The size and spatial distribution of loess slides are important for estimating the yield of eroded materials and determining the landslide risk. While previous studies have investigated landslide size distributions, the spatial distribution pattern of landslides at different spatial scales is poorly understood. The results indicate that the loess slide distribution exhibits a power-law scaling across a range of the size distribution. The mean landslide size and size distribution in the different geomorphic types are different. The double Pareto and inverse gamma functions can coincide well with the empirical probability distribution of the loess slide areas and can quantitatively reveal the rollover location, maximum probability, and scaling exponents. The frequency of loess slides increases with mean monthly precipitation. Moreover, point distance analysis showed that > 80% of landslides are located < 3 km from other loess slides. We found that the loess slides at the two study sites (Zhidan and Luochuan County) in northern Shaanxi Province, China show a significant clustered distribution. Furthermore, analysis results of the correlated fractal dimension show that the landslides exhibit a dispersed distribution at smaller spatial scales and a clustered distribution at larger spatial scales.     

Geomorphic studies of landslides in the Tully Valley, New York: implications for public policy and planning

On April 27, 1993, a large landslide in the Tully Valley, Onondaga County, NY, destroyed three houses and resulted in the evacuation of four others; it also triggered a loss of potable drinking water for about 15 homes north of the slide area and affected a total of 20 ha of land. In the 7 years following this slide, several studies have been conducted by federal and state environmental agencies and by local universities. The goal of these investigations has been to determine what caused this slide, document the history of past landslides in the region, and establish whether future slides are likely to occur. This paper reports on the results of these investigations and examines their effect on the Tully Valley community.     

位移监测在滑坡时空运动研究中的应用

滑坡时空运动特征是滑坡地质体在内因和外因共同作用下，自一种状态向另一种状态转化的地质过程。滑坡位移监测是研究滑坡变形影响因素、动态规律及预测预报的主要途径，特别是滑坡深部位移监测，又为研究滑坡体的时空运动过程提供了重要信息。本文结合几个滑坡的深部位移监测实践，综合分析位移监测信息，研究滑坡体的时空运动特征及发展趋势，为滑坡时空运动系统研究及稳定性预测提供依据。     

Validation of landslide hazard models using a semantic engine on online news

The objective of this work is twofold: (i) automatically setting up a landslide inventory using a state-of-the art semantic engine based on data mining on online news and (ii) evaluating if the automatically generated inventory can be used to validate a regional scale landslide warning system based on rainfall-thresholds.The semantic engine scanned internet news in real time in a 50 months test period. At the end of the process, an inventory of approximately 900 landslides was automatically set up for the Tuscany region (23,000 km², Italy). Using a completely automated procedure, the inventory was compared with the outputs of the regional landslide early warning system and a good correspondence was found, e.g. 84% of the events reported in the news is correctly identified by the warning system.On the basis of the obtained results, we conclude that automatic validation of landslide models using geolocalized landslide events feedback is possible. The source of data for validation can be obtained directly from the Internet channel using an appropriate semantic engine dedicated to perform a monitoring of the Google News aggregator.Moreover, validation statistics can be used to evaluate the effectiveness of the predictive model and, if deemed necessary, an update of the rainfall thresholds could be performed to obtain an improvement of the forecasting effectiveness of the warning system.In the near future, the proposed procedure could operate in continuous time and could allow for a periodic update of landslide hazard models and landslide early warning systems with minimum or none human intervention.