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1.
Spatial patterns of old, deep-seated landslides: A case-study in the northern Ethiopian highlands 总被引：1，自引：0，他引：1
M. Van Den Eeckhaut J. Moeyersons J. Nyssen Amanuel Abraha J. Poesen Mitiku Haile J. Deckers 《Geomorphology》2009,105(3-4):239-252
During the last decade, slope failures were reported in a 500 km2 study area in the Geba–Werei catchment, northern Ethiopia, a region where landslides were not considered an important hazard before. Field observations, however, revealed that many of the failures were actually reactivations of old deep-seated landslides after land use changes. Therefore, this study was conducted (1) to explore the importance of environmental factors controlling landslide occurrence and (2) to estimate future landslide susceptibility. A landslide inventory map of the study area derived from aerial photograph interpretation and field checks shows the location of 57 landslides and six zones with multiple landslides, mainly complex slides and debris flows. In total 14.8% of the area is affected by an old landslide. For the landslide susceptibility modelling, weights of evidence (WofE), was applied and five different models were produced. After comparison of the models and spatial validation using Receiver Operating Characteristic curves and Kappa values, a model combining data on elevation, hillslope gradient, aspect, geology and distance to faults was selected. This model confirmed our hypothesis that deep-seated landslides are located on hillslopes with a moderate slope gradient (i.e. 5°–13°). The depletion areas are expected on and along the border of plateaus where weathered basalts rich in smectite clays are found, and the landslide debris is expected to accumulate on the Amba Aradam sandstone and upper Antalo limestone. As future landslides are believed to occur on inherently unstable hillslopes similar to those where deep-seated landslides occurred, the classified landslide susceptibility map allows delineating zones where human interventions decreasing slope stability might cause slope failures. The results obtained demonstrate that the applied methodology could be used in similar areas where information on the location of landslides is essential for present-day hazard analysis. 相似文献
2.
Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong 总被引：29，自引：0，他引：29
Steep terrain and high a frequency of tropical rainstorms make landslide occurrence on natural terrain a common phenomenon in Hong Kong. This paper reports on the use of a Geographical Information Systems (GIS) database, compiled primarily from existing digital maps and aerial photographs, to describe the physical characteristics of landslides and the statistical relations of landslide frequency with the physical parameters contributing to the initiation of landslides on Lantau Island in Hong Kong. The horizontal travel length and the angle of reach, defined as the angle of the line connecting the head of the landslide source to the distal margin of the displaced mass, are used to describe runout behavior of landslide mass. For all landslides studied, the horizontal travel length of landslide mass ranges from 5 to 785 m, with a mean value of 43 m, and the average angle of reach is 27.7°. This GIS database is then used to obtain a logistic multiple regression model for predicting slope instability. It is indicated that slope gradient, lithology, elevation, slope aspect, and land-use are statistically significant in predicting slope instability, while slope morphology and proximity to drainage lines are not important and thus excluded from the model. This model is then imported back into the GIS to produce a map of predicted slope instability. The results of this study demonstrate that slope instability can be effectively modeled by using GIS technology and logistic multiple regression analysis. 相似文献
3.
GIS and ANN model for landslide susceptibility mapping 总被引：1，自引：0，他引：1
XU Zeng-wang 《地理学报》2001,11(3):374-381
Landslide hazard is as the probability of occurrence of a potentially damaging landslide phenomenon within specified period of time and within a given area. The susceptibility map provides the relative spatial probability of landslides occurrence. A study is presented of the application of GIS and artificial neural network model to landslide susceptibility mapping, with particular reference to landslides on natural terrain in this paper. The method has been applied to Lantau Island, the largest outlying island within the territory of Hong Kong. A three-level neural network model was constructed and trained by the back-propagate algorithm in the geographical database of the study area. The data in the database includes digital elevation modal and its derivatives, landslides distribution and their attributes, superficial geological maps, vegetation cover, the raingauges distribution and their 14 years 5-minute observation. Based on field inspection and analysis of correlation between terrain variables and landslides frequency, lithology, vegetation cover, slope gradient, slope aspect, slope curvature, elevation, the characteristic value, the rainstorms corresponding to the landslide, and distance to drainage line are considered to be related to landslide susceptibility in this study. The artificial neural network is then coupled with the ArcView3.2 GIS software to produce the landslide susceptibility map, which classifies the susceptibility into three levels: low, moderate, and high. The results from this study indicate that GIS coupled with artificial neural network model is a flexible and powerful approach to identify the spatial probability of hazards. 相似文献
4.
GIS and ANN model for landslide susceptibility mapping 总被引：4，自引：0，他引：4
XU Zeng-wang 《地理学报(英文版)》2001,11(3):374-381
1 IntroductionThe population growth and the expansion of settlements and life-lines over hazardous areas exert increasingly great impact of natural disasters both in the developed and developing countries. In many countries, the economic losses and casualties due to landslides are greater than commonly recognized and generate a yearly loss of property larger than that from any other natural disasters, including earthquakes, floods and windstorms. Landslides in mountainous terrain often occur a… 相似文献
5.
Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence 总被引：12，自引：0，他引：12
Ranjan Kumar Dahal Shuichi Hasegawa Atsuko Nonomura Minoru Yamanaka Santosh Dhakal Pradeep Paudyal 《Geomorphology》2008,102(3-4):496-510
Landslide hazard mapping is a fundamental tool for disaster management activities in mountainous terrains. The main purpose of this study is to evaluate the predictive power of weights-of-evidence modelling in landslide hazard assessment in the Lesser Himalaya of Nepal. The modelling was performed within a geographical information system (GIS), to derive a landslide hazard map of the south-western marginal hills of the Kathmandu Valley. Thematic maps representing various factors (e.g., slope, aspect, relief, flow accumulation, distance to drainage, soil depth, engineering soil type, landuse, geology, distance to road and extreme one-day rainfall) that are related to landslide activity were generated, using field data and GIS techniques, at a scale of 1:10,000. Landslide events of the 1970s, 1980s, and 1990s were used to assess the Bayesian probability of landslides in each cell unit with respect to the causative factors. To assess the accuracy of the resulting landslide hazard map, it was correlated with a map of landslides triggered by the 2002 extreme rainfall events. The accuracy of the map was evaluated by various techniques, including the area under the curve, success rate and prediction rate. The resulting landslide hazard value calculated from the old landslide data showed a prediction accuracy of > 80%. The analysis suggests that geomorphological and human-related factors play significant roles in determining the probability value, while geological factors play only minor roles. Finally, after the rectification of the landslide hazard values of the new landslides using those of the old landslides, a landslide hazard map with > 88% prediction accuracy was prepared. The methodology appears to have extensive applicability to the Lesser Himalaya of Nepal, with the limitation that the model's performance is contingent on the availability of data from past landslides. 相似文献
6.
Predicting landslides for risk analysis — Spatial models tested by a cross-validation technique 总被引：3，自引：3，他引：0
A landslide-hazard map is intended to show the location of future slope instability. Most spatial models of the hazard lack reliability tests of the procedures and predictions for estimating the probabilities of future landslides, thus precluding use of the maps for probabilistic risk analysis. To correct this deficiency we propose a systematic procedure comprising two analytical steps: “relative-hazard mapping” and “empirical probability estimation”. A mathematical model first generates a prediction map by dividing an area into “prediction” classes according to the relative likelihood of occurrence of future landslides, conditional by local geomorphic and topographic characteristics. The second stage estimates empirically the probability of landslide occurrence in each prediction class, by applying a cross-validation technique. Cross-validation, a “blind test” here using non-overlapping spatial or temporal subsets of mapped landslides, evaluates accuracy of the prediction and from the resulting statistics estimates occurrence probabilities of future landslides. This quantitative approach, exemplified by several experiments in an area near Lisbon, Portugal, can accommodate any subsequent analysis of landslide risk. 相似文献
7.
Landslide Representation Strategies in Susceptibility Studies using Weights-of-Evidence Modeling Technique 总被引：4，自引：0，他引：4
This paper is focused primarily on how to represent landslide scarp areas, how to analyze results achieved by the application
of specific strategies of representation and how to compare the outcomes derived by different tests, within a general framework
related to landslide susceptibility assessment. These topics are analyzed taking into account the scale of data survey (1:10,000)
and the role of a landslide susceptibility map into projects targeted toward the definition of prediction, prevention, and
mitigation measures, in a wider context of civil protection planning. These aims are achieved by using ArcSDM (Arc Spatial
Data Modeler), a software extension to ArcView GIS useful for developing spatial prediction models using regional datasets.
This extension requires a representation by points of the investigated problems (landslide susceptibility, aquifer vulnerability,
detection of mineral deposits, identification of natural habitats of animals, and plants, etc.). Maps of spatial evidence
from regional geological and geomorphological datasets were used to generate maps showing susceptibility to slope failures
in two different study areas, located in the northern Apennines and in the central Alps (Italy), respectively. The final susceptibility
maps for both study areas were derived by the application of the weights-of-evidence (WofE) modeling technique. By this method
a series of subjective decisions were required, strongly dependent on an understanding of the natural processes under study,
supported by statistical analysis of the spatial associations between known landslides and evidential themes. Except for maps
of attitude, permeability, and structure, that were not available for both study areas, the other data were the same and comprised
geological, land use, slope, and internal relief maps.
The paper illustrates how different representations of scarp areas by points (in terms of different number of points) did
not greatly influence the final response map, considering the scale of this work. On the contrary, some differences were observed
in the capability of the model to describe the relations between predictor variables and landslides. In effect, a representation
of the scarp areas using one point every 50 m led to a more efficient model able to better define relationships of this type.
It avoided both problems of redundancy of information, deriving by the use of too many points, and problems related to a random
positioning of the centroid. Moreover, it permitted to minimize the uncertainty related with identification and mapping of
landslides. 相似文献
8.
Probabilistic landslide hazard assessment at the basin scale 总被引：32，自引：9，他引：32
Fausto Guzzetti Paola Reichenbach Mauro Cardinali Mirco Galli Francesca Ardizzone 《Geomorphology》2005,72(1-4):272-299
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. 相似文献
9.
A dynamic model for rainfall-induced landslides on natural slopes 总被引：18，自引：0，他引：18
10.
Landslide hazard mapping along the coastline of the Cilento region (Italy) by means of a GIS-based parameter rating approach 总被引：2，自引：1，他引：1
This paper deals with the heuristic approach used for landslide hazard zonation along the coastal slopes and cliffs of the Cilento region between Agropoli and Sapri (Italy). This sector of coastline (about 118 km in length) is formed mainly of Mesozoic carbonates and Miocene flysch; Quaternary marine sandstones together with beach sands also crop out. Due to the destructive force of the waves, the coastline is affected by several landslides (mainly rock-falls and slides). The major geomorphological, geological and structural features of about 154 slopes and cliffs have been analysed and several parameters affecting the rock-masses were detected and measured. These parameters deal with topographical, geological, geomechanical, environmental and wave hydraulic characteristics of the studied area. In order to perform the heuristic approach, the Rock Engineering Systems (RES) proposed by Hudson was adopted with several modifications. The main steps of this work were: (1) the choice of parameters relevant to landslide hazard zonation, (2) the analysis of binary interaction between parameters, (3) the weighting of interaction importance, (4) the rating assignment to different classes of parameter values and (5) the final computation of an “Instability Index” (I.I.). A database containing the measured parameters was prepared, and using an interaction matrix, the outputs were linked into a Geographic Information System. It contains the following elements: geological and geomorphological features, historical data regarding landslides, images and values of I.I. for the studied slopes and cliffs. If new landslides occur or near-shore engineered structures are built, then the I.I. values will be automatically upgraded.Values of the I.I. were grouped into 3 classes marking low, medium and high landslide hazard. Both carbonatic rock-masses and flysch were distinguished with respect to I.I. values to show the differences in landslide susceptibility. In fact, rapid but small rock-falls can cause more casualties than moderate speed but large slides. High landslide hazard affects about 41% of carbonate cliffs and about 53% of slopes in arenaceous-marly flysch. 相似文献
11.
Landslide susceptibility analysis with a heuristic approach in the Eastern Alps (Vorarlberg, Austria) 总被引：5，自引：0，他引：5
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. 相似文献
12.
13.
数字地形分析在滑坡研究中的应用综述 总被引：2，自引：0，他引：2
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。 相似文献
14.
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. 相似文献
15.
DEM地形分析在山区地质灾害研究中的应用——以云南省漾濞县为例 总被引：1，自引：0，他引：1
云南省漾濞县具有典型的山地特点,每年其境内发生的地质灾害都给人民生命和财产造成了极大的损失。在漾濞县的地质灾害调查中,通过"3S"技术的应用,建立了漾濞县的数字高程模型,进行了基于ArcGIS的地形分析,提取出了坡度和坡向等重要的地形因子。通过研究发现:坡度是漾濞县地质灾害频发的最主要控制因素,漾濞江及其支流上游的滑坡和崩塌为泥石流的发生提供了物源基础;同时阳坡是地质灾害发生的主要坡向,滑坡和崩塌等灾害发生频繁。最后,制作了漾濞县坡度、坡向分析图,指出了漾濞县较易发生地质灾害的地区,为其他山地地区地质灾害研究提供了一种借鉴模式。 相似文献
16.
Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression 总被引：13，自引：0，他引：13
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. 相似文献
17.
A landslide susceptibility model using the Analytical Hierarchy Process method and multivariate statistics in perialpine Slovenia 总被引：27，自引：3，他引：27
Landslides cause damage to property and unfortunately pose a threat even to human lives. Good landslide susceptibility, hazard, and risk models could help mitigate or even avoid the unwanted consequences resulted from such hillslope mass movements. For the purpose of landslide susceptibility assessment the study area in the central Slovenia was divided to 78 365 slope units, for which 24 statistical variables were calculated. For the land-use and vegetation data, multi-spectral high-resolution images were merged using Principal Component Analysis method and classified with an unsupervised classification. Using multivariate statistical analysis (factor analysis), the interactions between factors and landslide distribution were tested, and the importance of individual factors for landslide occurrence was defined. The results show that the slope, the lithology, the terrain roughness, and the cover type play important roles in landslide susceptibility. The importance of other spatial factors varies depending on the landslide type. Based on the statistical results several landslide susceptibility models were developed using the Analytical Hierarchy Process method. These models gave very different results, with a prediction error ranging from 4.3% to 73%. As a final result of the research, the weights of important spatial factors from the best models were derived with the AHP method. Using probability measures, potentially hazardous areas were located in relation to population and road distribution, and hazard classes were assessed. 相似文献
18.
A model for the prediction of topographic and climatic control on shallow landsliding in mountainous terrain is enhanced to analyse the impact of upslope rocky outcrops on downslope shallow landsliding. The model uses a ‘generalised quasi-dynamic wetness index’ to describe runoff propagation on bare rock surfaces connected to downslope soil-mantled topographic elements. This approach yields a simple enhanced model capable of describing the influence of upslope bedrock outcrops on the pattern of downslope soil saturation. The model is applied in both diagnostic and predictive modes to a small catchment in the eastern Italian Alps for which a detailed inventory of shallow landslides in areas dominated by rocky outcrops is available. In the diagnostic mode, the model is used with satisfactory results to reproduce the pattern of instability generated by an intense short-duration storm occurred on 14 September 1994, which triggered a large percentage of the surveyed landslides. In the predictive mode, the model is used for hazard assessment, and the return time of the critical rainfall needed to cause instability for each topographic element is determined. Modelling results obtained in the predictive mode are evaluated against all the surveyed landslides. It is revealed that the generalised quasi-dynamic model offers considerable improvement over the non-generalised quasi-dynamic model and the steady-state model in predicting existing landslides as represented in the considered landslide inventory. 相似文献
19.
Landsat series multispectral remote sensing imagery has gained increasing attention in providing solutions to environmental problems such as land degradation which exacerbate soil erosion and landslide disasters in the case of rainfall events. Multispectral data has facilitated the mapping of soils, land-cover and structural geology, all of which are factors affecting landslide occurrence. The main aim of this research was to develop a methodology to visualize and map past landslides as well as identify land degradation effects through soil erosion and land-use using remote sensing techniques in the central region of Kenya. The study area has rugged terrain and rainfall has been the main source of landslide trigger. The methodology comprised visualizing landslide scars using a False Colour Composite (FCC) and mapping soil erodibility using FCC components applying expert based classification. The components of the FCC were: the first independent component (IC1), Principal Component (PC) with most geological information, and a Normalised Difference Index (NDI) involving Landsat TM/ETM+ band 7 and 3.The FCC components formed the inputs for knowledge-based classification with the following 13 classes: runoff, extreme erosions, other erosions, landslide areas, highly erodible, stable, exposed volcanic rocks, agriculture, green forest, new forest regrowth areas, clear, turbid and salty water. Validation of the mapped landslide areas with field GPS locations of landslide affected areas showed that 66% of the points coincided well with landslide areas mapped in the year 2000. The classification maps showed landslide areas on the steep ridge faces, other erosions in agricultural areas, highly erodible zones being already weathered rocks, while runoff were mainly fluvial deposits. Thus, landuse and rainfall processes play a major role in inducing landslides in the study area. 相似文献
20.
Huge volcanic landslides are one of the most hazardous geomorphological processes that can occur during the evolution of volcanic ocean islands. The causes of these phenomena, however, are very complex and combine non-volcanic and volcanic factors. In the Canary Islands, more than 20 events have been detected during the last decades. A detailed analysis was carried out for La Orotava amphitheatre on Tenerife in order to understand the relationship between geomorphological and geological aspects and huge volcanic landslides. The results indicated four major features that play a significant role in such mass movements: deep erosive canyons, high coastal cliffs, widespread residual soils and structural axes. High coastal cliffs and deep erosive canyons locally reduce the stability conditions and control both the seaward and the lateral boundary of the landslide. Weak residual soils formed above phonolitic pyroclastic deposits occur repeatedly in the stratigraphic column of La Orotava and are characterised by their large extent. Thus, one of these soils may have evolved into the slip surface of the failure. Part of the head scarp of the amphitheatre is defined by a volcanic rift zone, as indicated by the measurement of dike orientation and a density map of eruptive vents. The four features are not able to trigger a failure, but to destabilise the volcano flank and determine the boundary of the slide. Therefore, information on depth and orientation of canyons; location and height of coastal cliffs; stratigraphic repetition, extension and thickness of residual soils and orientation and density of dikes and eruptive vents along structural axes should be incorporated into a hazard assessment on large landslides on volcanic islands. 相似文献