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1.
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
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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
3.
A dynamic model for rainfall-induced landslides on natural slopes 总被引：18，自引：0，他引：18
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Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China 总被引：23，自引：0，他引：23
The Support Vector Machine (SVM) is an increasingly popular learning procedure based on statistical learning theory, and involves a training phase in which the model is trained by a training dataset of associated input and target output values. The trained model is then used to evaluate a separate set of testing data. There are two main ideas underlying the SVM for discriminant-type problems. The first is an optimum linear separating hyperplane that separates the data patterns. The second is the use of kernel functions to convert the original non-linear data patterns into the format that is linearly separable in a high-dimensional feature space. In this paper, an overview of the SVM, both one-class and two-class SVM methods, is first presented followed by its use in landslide susceptibility mapping. A study area was selected from the natural terrain of Hong Kong, and slope angle, slope aspect, elevation, profile curvature of slope, lithology, vegetation cover and topographic wetness index (TWI) were used as environmental parameters which influence the occurrence of landslides. One-class and two-class SVM models were trained and then used to map landslide susceptibility respectively. The resulting susceptibility maps obtained by the methods were compared to that obtained by the logistic regression (LR) method. It is concluded that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, which only requires failed cases, has an advantage over the other two methods as only “failed” case information is usually available in landslide susceptibility mapping. 相似文献
5.
GIS支持下三峡库区秭归县滑坡灾害空间预测 总被引：3，自引：1，他引：2
基于GIS空间分析和统计模型相结合进行区域评价与空间预测是滑坡灾害研究的重要方向之一。以三峡库区秭归县为研究区,选择坡度、坡向、边坡结构、工程岩组、排水系统、土地利用和公路开挖作为评价因子。为提高模型的预测精度、可信度和推广能力,利用窗口采样规则降低训练样本之间的空间相关性。建立Logistic回归模型,对滑坡灾害与评价因子进行定量相关性分析。计算研究区滑坡灾害易发性指数,对其进行聚类分析,绘制滑坡易发性分区图,其中高、中易发区占整个研究区面积的38.9%,主要分布在人类工程活动频繁和靠近排水系统的区域。经过验证,该模型的预测精度达到77.57%。 相似文献
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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
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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
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A qualitative landslide susceptibility zonation map (scale 1:100,000) of a sector of the Río Mendoza Valley was prepared by overlapping thematic maps of conditioning factors. The main parameters affecting the distribution of landslides in the area were ranked according to slope instability. Geomorphological surveys and field observations enabled identification of 300 historical or prehistoric landslides. A landslide inventory was developed classifying the processes involved in slope instability, and analysing the degree of activity. The two most influential factors in decreasing slope stability were lithology and slope angle. 相似文献
10.
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
11.
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
12.
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. 相似文献
13.
GIS techniques for regional-scale landslide susceptibility assessment: the Sicily (Italy) case study
G. Manzo V. Tofani A. Battistini F. Catani 《International journal of geographical information science》2013,27(7):1433-1452
This study describes the assessment of landslide susceptibility in Sicily (Italy) at a 1:100,000 scale using a multivariate logistic regression model. The model was implemented in a GIS environment by using the ArcSDM (Arc Spatial Data Modeller) module, modified to develop spatial prediction through regional data sets. A newly developed algorithm was used to automatically extract the detachment area from mapped landslide polygons. The following factors were selected as independent variables of the logistic regression model: slope gradient, lithology, land cover, a curve number derived index and a pluviometric anomaly index. The above-described configuration has been verified to be the best one among others employing from three to eight factors. All the regression coefficients and parameters were calculated using selected landslide training data sets. The results of the analysis were validated using an independent landslide data set. On an average, 82% of the area affected by instability and 79% of the not affected area were correctly classified by the model, which proved to be a useful tool for planners and decision-makers. 相似文献
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地形对黄土高原滑坡的影响 总被引：4，自引：0，他引：4
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。 相似文献
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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
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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
17.
Cheng-Zhi Qin Li-Li Bao Rong-Xun Wang Xue-Mei Hu 《International journal of geographical information science》2013,27(7):1364-1380
Terrain attributes such as slope gradient and slope shape, computed from a gridded digital elevation model (DEM), are important input data for landslide susceptibility mapping. Errors in DEM can cause uncertainty in terrain attributes and thus influence landslide susceptibility mapping. Monte Carlo simulations have been used in this article to compare uncertainties due to DEM error in two representative landslide susceptibility mapping approaches: a recently developed expert knowledge and fuzzy logic-based approach to landslide susceptibility mapping (efLandslides), and a logistic regression approach that is representative of multivariate statistical approaches to landslide susceptibility mapping. The study area is located in the middle and upper reaches of the Yangtze River, China, and includes two adjacent areas with similar environmental conditions – one for efLandslides model development (approximately 250 km2) and the other for model extrapolation (approximately 4600 km2). Sequential Gaussian simulation was used to simulate DEM error fields at 25-m resolution with different magnitudes and spatial autocorrelation levels. Nine sets of simulations were generated. Each set included 100 realizations derived from a DEM error field specified by possible combinations of three standard deviation values (1, 7.5, and 15 m) for error magnitude and three range values (0, 60, and 120 m) for spatial autocorrelation. The overall uncertainties of both efLandslides and the logistic regression approach attributable to each model-simulated DEM error were evaluated based on a map of standard deviations of landslide susceptibility realizations. The uncertainty assessment showed that the overall uncertainty in efLandslides was less sensitive to DEM error than that in the logistic regression approach and that the overall uncertainties in both efLandslides and the logistic regression approach for the model-extrapolation area were generally lower than in the model-development area used in this study. Boxplots were produced by associating an independent validation set of 205 observed landslides in the model-extrapolation area with the resulting landslide susceptibility realizations. These boxplots showed that for all simulations, efLandslides produced more reasonable results than logistic regression. 相似文献
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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
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中部大城市居民港台旅游意象及其对旅游意愿的影响研究——以无港台旅游经历南昌市民为例 总被引：1，自引：1，他引：0
为了协助政府或企业对中部大城市港台游市场的预测、营销与管理,也为了验证人们对多个目的地旅游意象的差异是否导致他们对这些目的地旅游意愿的差异,文章以南昌市为例,分析、比较了中部大城市居民对港台两地的旅游意象和旅游意愿。对598位无港台旅游经历南昌市民的调查表明：香港的旅游意象优势多于台湾,就总体而言市民对香港的旅游意愿也显著强于台湾;市民对港台两地的旅游意愿和选择偏好均存在显著的群体分异。Logistic回归分析结果显示,香港的多数旅游意象优势、劣势因子显著影响市民在港台两地中偏好香港的概率。这就从潜在游客角度证实了目的地之间旅游意象差异与旅游意愿差异的因果联系。香港、台湾应重视对中部大城市旅游市场的开拓,但两地的具体策略应有所不同。 相似文献