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1.
Qualitative landslide susceptibility assessment by multicriteria analysis: A case study from San Antonio del Sur, Guantánamo, Cuba 总被引:1,自引:0,他引:1
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. 相似文献
2.
Determining landslide susceptibility in Central Taiwan from rainfall and six site factors using the analytical hierarchy process method 总被引:6,自引:0,他引:6
This work provides a landslide susceptibility assessment model for rainfall-induced landslides in Central Taiwan based on the analytical hierarchy process method. The model considers rainfall and six site factors, including slope, geology, vegetation, soil moisture, road development and historical landslides. The rainfall factor consists of 10-day antecedent rainfall and total rainfall during a rainfall event. Landslide susceptibility values are calculated for both before and after the beginning of a rainfall event. The 175 landslide cases with detailed field surveys are used to determine a landslide-susceptibility threshold value of 9.0. When a landslide susceptibility assessment value exceeds the threshold value, slope failure is likely to occur. Three zones with different landslide susceptibility levels (below, slightly above, and far above the threshold) are identified. The 9149 landslides caused by Typhoon Toraji in Central Taiwan are utilized to validate the study's result. Approximately, 0.2%, 0.4% and 15.3% of the typhoon-caused landslides are located in the three landslide susceptibility zones, respectively. Three villages with 6.6%, 0.4% and 4.9% of the landslides respectively are used to validate the accuracy of the landslide susceptibility map and analyze the main causes of landslides. The landslide susceptibility assessment model can be used to evaluate susceptibility relative to accumulated rainfall, and is useful as an early warning and landslide monitoring tool. 相似文献
3.
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
4.
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
5.
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
6.
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
7.
滑坡危险度评价的地形判别法 总被引:10,自引:1,他引:10
选取影响滑坡发育的坡度、坡形、坡向、坡体的相对高度和地形与地层产状的组合关系5个主要地形因素,结合三峡库区重点滑坡段(云阳-巫山)205个滑坡统计资料,利用地形判别法,对典型滑坡危险度进行评价。将各地形判别因子在区域滑坡发育上的贡献率作为评价典型滑坡危险度的评价值,利用层次分析法,建立典型滑坡危险度判别矩阵。将判别矩阵的归一化特征向量作为判别因子的权重,得到典型滑坡的危险度。通过建立典型滑坡危险度评价表,对滑坡进行有效的管理。此研究方法有效地避免了对评价因子赋值的主观性,并提出了对不同危险度等级的滑坡管理措施。 相似文献
8.
斜坡类型描述岩层产状与斜坡的角度关系,很大程度上决定了斜坡岩土体变形的方式和强度,对地质灾害分布具有重要作用。斜坡的顺向坡、反向坡与地形的阳坡、阴坡概念相似,可以利用改进的太阳辐射地形因子计算模型(TOBIA指数)对斜坡类型进行定量化表达。计算TOBIA指数需要斜坡坡度、坡向、岩层倾角、倾向4个参数。以三峡库区顺向坡基岩滑坡多发地段青干河流域为例,通过区域地质图上产状点获取离散岩层倾角和倾向数值,经空间插值得到空间连续分布的倾角和倾向参数;通过数字高程模型获取坡度和坡向参数,得到区内TOBIA指数分布。在此基础上进一步研究指数和滑坡发育关系。结果表明,TOBIA指数值与区内斜坡类型密切相关,根据TOBIA指数值能很好地区分斜坡类型。以二分类变量逻辑回归模型对坡度和指数两个变量进行分析,发现引入TOBIA指数后,回归模型对已知滑坡拟合度由55%提高到71.5%,能有效提高区域滑坡灾害危险性区划结果精度。 相似文献
9.
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
10.
Comparison of landslide susceptibility based on a decision-tree model and actual landslide occurrence: The Akaishi Mountains, Japan 总被引:7,自引:0,他引:7
This paper proposes a statistical decision-tree model to analyze landslide susceptibility in a wide area of the Akaishi Mountains, Japan. The objectives of this study were to validate the decision-tree model by comparing landslide susceptibility and actual landslide occurrence, and to reveal the relationships among landslide occurrence, topography, and geology. Landslide susceptibility was examined through ensemble learning with a decision tree. Decision trees are advantageous in that estimation processes and order of important explanatory variables are explicitly represented by the tree structures. Topographic characteristics (elevation, slope angle, profile curvature, plan curvature, and dissection and undissection height) and geological data were used as the explanatory variables. These topographic characteristics were calculated from digital elevation models (DEMs). The objective variables were landslide occurrence and reactivation data between 1992 and 2002 that were depicted by satellite image analysis. Landslide susceptibility was validated by comparing actual data on landslides that occurred and reactivated after the model was constructed (between 2002 and 2004).This study revealed that, from 2002 to 2004, landslides tended to occur and reactivate in catchments with high landslide susceptibility. The landslide susceptibility map thus depicts the actual landslide occurrence and reactivation in the Akaishi Mountains. This result indicates that the decision-tree model has appropriate accuracy for estimating the probabilities of future landslides. The tree structure indicates that landslides occurred and reactivated frequently in the catchments that had an average slope angle exceeding ca. 29° and a mode of slope angle exceeding 33°, which agree well with previous studies. A decision tree also quantitatively expresses important explanatory variables at the higher order of the tree structure. 相似文献
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基于专家知识的滑坡危险性模糊评估方法 总被引:6,自引:0,他引:6
滑坡发生的影响因素众多, 其危险性与各因素之间的关系多呈非线性关系, 同时各因素之 间也存在或强或弱的相关性, 而目前的危险性评价方法难以体现这些要求。本文提出了一种借助 滑坡专家知识并利用模糊推理理论进行滑坡危险性评价的方法。该方法通过建立了①坡度与岩 层倾角之差和坡向与岩层倾向之差、②坡度和岩性、③临空面和岩性、④坡形和岩性等四种环境 因子组合, 以此将不同环境因子之间的相关性融入各组合模型中, 并将四种组合所得的模糊危险 度进行叠加用于滑坡危险度的模糊评价。环境组合模型中的参数利用专家经验给出。将该方法应 用于三峡库区云阳- 巫山段, 得到了滑坡危险性的分级分布图。从滑坡危险性分布图上可清楚发 现, 本方法所计算出的危险性值在滑坡发生的地区明显高于未发生滑坡的地区, 该结果可以用于 城镇建设和重要基础规划设施的参考。 相似文献
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DOMENICO GUIDA MANUELA PELFINI MAURIZIO SANTILLI 《Geografiska Annaler: Series A, Physical Geography》2008,90(3):211-226
Complex landslides, capable of reactivation, are typical slope movements in high relief areas. Due to their distribution, size and kinematics, these landforms represent a major hazard, posing a high risk to populations, settlements and infrastructures. This paper integrates geomorphological analyses, instrumental measurements and dendrochronological approaches in assessing a large, reactivated landslide system on the southern piedmont of Monte Sirino (southern Italy). The landslide system is associated with weak geological structures, earthquake activity, and rapid recent incision of the mid-Pleistocene Noce lake deposits. Potential reactivation triggers include a higher regional annual rainfall, one of the highest in southern Italy, and more frequent heavy snowfalls in recent decades. Reactivation of the Sirino landslide system has important implications for the motorway connecting Salerno and Reggio Calabria, which crosses it. The results of our study show that the slide is reactivated with an almost decadal frequency and that major reactivations are correlated to prolonged snowfall, which occurs with increasing frequency in the southern Apennines. The last observation suggests the need for similar studies on the behaviour of other landslide systems in the southern Apennines, performing integrated approaches such as geotechnical and dendrogeomorphological analysis. 相似文献
16.
Arif Mert Eker Mehmet Dikmen Selim Cambazoğlu Şebnem H.B. Düzgün 《International journal of geographical information science》2013,27(1):132-158
The purpose of this study was to investigate the capabilities of different landslide susceptibility methods by comparing their results statistically and spatially to select the best method that portrays the susceptibility zones for the Ulus district of the Bart?n province (northern Turkey). Susceptibility maps based on spatial regression (SR), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression (LR) method, and artificial neural network method (ANN) were generated, and the effect of each geomorphological parameter was determined. The landslide inventory map digitized from previous studies was used as a base map for landslide occurrence. All of the analyses were implemented with respect to landslides classified as rotational, active, and deeper than 5 m. Three different sets of data were used to produce nine explanatory variables (layers). The study area was divided into grids of 90 m × 90 m, and the ‘seed cell’ technique was applied to obtain statistically balanced population distribution over landslide inventory area. The constructed dataset was divided into two datasets as training and test. The initial assessment consisted of multicollinearity of explanatory variables. Empirical information entropy analysis was implemented to quantify the spatial distribution of the outcomes of these methods. Results of the analyses were validated by using success rate curve (SRC) and prediction rate curve (PRC) methods. Additionally, statistical and spatial comparisons of the results were performed to determine the most suitable susceptibility zonation method in this large-scale study area. In accordance with all these comparisons, it is concluded that ANN was the best method to represent landslide susceptibility throughout the study area with an acceptable processing time. 相似文献
17.
Field monitoring of the Corvara landslide (Dolomites, Italy) and its relevance for hazard assessment 总被引:4,自引:1,他引:4
The Corvara landslide is an active slow moving rotational earth slide - earth flow, located uphill of the village of Corvara in Badia, one of the main tourist centres in the Alta Badia valley in the Dolomites (Province of Bolzano, Italy). Present-day movements of the Corvara landslide cause National Road 244 and other infrastructures to be damaged on a yearly basis. The movements also give rise to more serious risk scenarios for some buildings located in front the toe of the landslide. For these reasons, the landslide has been under observation since 1997 with various field devices that enable slope movements to be monitored for hazard assessment purposes. Differential GPS measurements on a network of 47 benchmarks has shown that horizontal movements at the surface of the landslide have ranged from a few centimetres to more than 1 m between September 2001 and September 2002. Over the same period, vertical movements ranged from a few centimetres to about 10 cm, with the maximum displacement rate being recorded in the track zone and in the uppermost part of the accumulation lobe of the landslide. Borehole systems, such as inclinometers and TDR cables, have recorded similar rates of movement, with the depths of the major active shear surfaces ranging from 48 m to about 10 m. From these data, it is estimated that the active component of the landslide has a volume of about 50 million m3. In this paper the monitoring data collected so far are presented and discussed in detail to prove that the hazard for the Corvara landslide, considered as the product of yearly probability of occurrence and magnitude of the phenomenon, can be regarded has as medium or high if the velocity or alternatively the volume involved is considered. Finally, it is also concluded that the monitoring results obtained provide a sound basis on which to develop and validate numerical models, manage hazard and support the identification of viable passive and active mitigation measures. 相似文献
18.
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
19.
基于信息量与逻辑回归模型的次生滑坡灾害敏感性评价——以汶川县北部为例 总被引:4,自引:2,他引:2
次生滑坡灾害的影响是震后较长时间里人们持续关注的焦点,对其开展敏感性评价具有重要意义。选取5.12地震的重灾区汶川县北部作为研究区,利用遥感与地理信息技术提取地震滑坡信息,在全面分析滑坡与高程、坡度、坡向、岩性、断裂带、地震烈度以及水系等7个影响因子相关特性的基础上,采用信息量法与逻辑回归模型进行灾害敏感性评价,将研究区划分为极轻度、轻度、中度、高度和极高危险5个级别,并对不同模型的适用性开展分析和对比。结果表明,逻辑回归模型在描述区域滑坡灾害危险度总体特征方面稍具优势。 相似文献
20.
María Jos Domínguez-Cuesta Montserrat Jimnez-Snchez Edgar Berrezueta 《Geomorphology》2007,89(3-4):358-369
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. 相似文献