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1.
This paper explains the procedure for the generation of a landslide risk index map at national level in Cuba, using a semi-quantitative model with ten indicator maps and a cell size of 90 × 90 m. The model was designed and implemented using spatial multi-criteria evaluation techniques in a GIS system. Each indicator was processed, analysed and standardised according to its contribution to hazard and vulnerability. The indicators were weighted using direct, pairwise comparison and rank-ordering weighting methods, and weights were combined to obtain the final landslide risk index map. The results were analysed per physiographic region and administrative units at provincial and municipal levels. The Sierra Maestra mountain system was found to have the largest concentration of high landslide risk index values while the Nipe–Cristal–Baracoa system has the highest absolute values, although they are more dispersed. The results obtained allow designing an appropriated landslide risk mitigation plan at national level and to link the information to the national hurricane early warning system, allowing also warning and evacuation for landslide-prone areas.  相似文献   

2.
Avalanche hazard mapping over large undocumented areas   总被引：3，自引：1，他引：2  
An innovative methodology to perform avalanche hazard mapping over large undocumented areas is herewith presented and discussed. The method combines GIS tools, computational routines, and statistical analysis in order to provide a “semi-automatic” definition of areas potentially affected by avalanche release and motion. The method includes two main modules. The first module is used to define zones of potential avalanche release, based on the consolidated relations on slope, morphology, and vegetation. For each of the identified zones of potential release, a second module, named Avalanche Flow and Run-out Algorithm (AFRA), provides an automatic definition of the areas potentially affected by avalanche motion and run-out. The definition is generated by a specifically implemented “flow-routing algorithm” which allows for the determination of flow behaviour in the track and in the run-out zone. In order to estimate the avalanche outline in the run-out zone, AFRA uses a “run-out cone”, which is a 3D projection of the angle of reach α. The α-value is evaluated by statistical analysis of historical data regarding extreme avalanches. Pre- and post-processing of the AFRA input/output data is done in an open source GIS environment (GRASS GIS). The method requires only a digital terrain model and an indication of the areas covered by forest as input parameters. The procedure, which allows rapid mapping of large areas, does not in principle require any site-specific historical information. Furthermore, it has proven to be effective in all cases where a preliminary cost-efficient analysis of the territories potentially affected by snow avalanche was needed.  相似文献   

3.
The increasing availability of remotely sensed data offers a new opportunity to address landslide hazard assessment at larger spatial scales. A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that may experience landslide activity. This system combines a calculation of static landslide susceptibility with satellite-derived rainfall estimates and uses a threshold approach to generate a set of ‘nowcasts’ that classify potentially hazardous areas. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale near real-time landslide hazard assessment efforts, it requires several modifications before it can be fully realized as an operational tool. This study draws upon a prior work’s recommendations to develop a new approach for considering landslide susceptibility and hazard at the regional scale. This case study calculates a regional susceptibility map using remotely sensed and in situ information and a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America. The susceptibility map is evaluated with a regional rainfall intensity–duration triggering threshold and results are compared with the global algorithm framework for the same event. Evaluation of this regional system suggests that this empirically based approach provides one plausible way to approach some of the data and resolution issues identified in the global assessment. The presented methodology is straightforward to implement, improves upon the global approach, and allows for results to be transferable between regions. The results also highlight several remaining challenges, including the empirical nature of the algorithm framework and adequate information for algorithm validation. Conclusions suggest that integrating additional triggering factors such as soil moisture may help to improve algorithm performance accuracy. The regional algorithm scenario represents an important step forward in advancing regional and global-scale landslide hazard assessment.  相似文献   

4.
In general, landslides in Malaysia mostly occurred during northeast and southwest periods, two monsoonal systems that bring heavy rain. As the consequence, most landslide occurrences were induced by rainfall. This paper reports the effect of monsoonal-related geospatial data in landslide hazard modeling in Cameron Highlands, Malaysia, using Geographic Information System (GIS). Land surface temperature (LST) data was selected as the monsoonal rainfall footprints on the land surface. Four LST maps were derived from Landsat 7 thermal band acquired at peaks of dry and rainy seasons in 2001. The landslide factors chosen from topography map were slope, slope aspect, curvature, elevation, land use, proximity to road, and river/lake; while from geology map were lithology and proximity to lineament. Landslide characteristics were extracted by crossing between the landslide sites of Cameron Highlands and landslide factors. Using which, the weighting system was derived. Each landslide factors were divided into five subcategories. The highest weight values were assigned to those having the highest number of landslide occurrences. Weighted overlay was used as GIS operator to generate landslide hazard maps. GIS analysis was performed in two modes: (1) static mode, using all factors except LST data; (2) dynamic mode, using all factors including multi-temporal LST data. The effect of addition of LST maps was evaluated. The final landslide hazard maps were divided into five categories: very high risk, high risk, moderate, low risk, and very low risk. From verification process using landslide map, the landslide model can predict back about 13–16% very high risk sites and 70–93% of very high risk and high risk combined together. It was observed however that inclusion of LST maps does not necessarily increase the accuracy of the landslide model to predict landslide sites.  相似文献   

5.
The Faroe Islands in the North Atlantic Ocean are susceptible to flow-type landslides in coarse-grained highly organic colluvium. Following several hazardous debris avalanche events, research work has been initiated to quantify landslide risk. A central task in this work is to predict landslide runout behavior. From numerical simulation of four debris avalanches, this study provides a first screening of which rheology and appertaining input parameters best predict runout behavior of debris avalanches in the Faroe Islands. Three rheologies (frictional, Voellmy, and Bingham) are selected and used for individual back analysis of the events in the numerical models BING and DAN3D. A best fit rheology is selected from comparing predicted and observed landslide runout behavior. General back analysis to identify the optimal input parameters for the chosen rheology is performed by cross validation, where each debris avalanche is modeled with input parameters from the three other events. Optimal input parameters are found from the model run producing the most accurate runout length and velocity. The Bingham is selected as the best fit rheology, a result differing from similar studies of coarse-grained landslides. A reason for why particularly the frictional rheology proves unsuitable is its tendency to produce too long runout lengths of the low-weight runout material, a result showing important limitations for using the frictional rheology in DAN3D. Optimal Bingham input parameters are τ y ?=?980 Pa and μ b ?=?117 Pa/s. However, future studies performed in 2D models are needed for precise parameterization before results can be used for landslide risk assessment.  相似文献   

6.
A procedure for landslide risk assessment is presented. The underlying hypothesis is that statistical relationships between past landslide occurrences and conditioning variables can be used to develop landslide susceptibility, hazard and risk models. The latter require also data on past damages. Landslides occurred during the last 50 years and subsequent damages were analysed. Landslide susceptibility models were obtained by means of Spatial Data Analysis techniques and independently validated. Scenarios defined on the basis of past landslide frequency and magnitude were used to transform susceptibility into quantitative hazard models. To assess vulnerability, a detailed inventory of exposed elements (infrastructures, buildings, land resources) was carried out. Vulnerability values (0–1) were obtained by comparing damages experienced in the past by each type of element with its actual value. Quantitative risk models, with a monetary meaning, were obtained for each element by integrating landslide hazard and vulnerability models. Landslide risk models showing the expected losses for the next 50 years were thus obtained for the different scenarios. Risk values obtained are not precise predictions of future losses but rather a means to identify areas where damages are likely to be greater and require priority for mitigation actions.  相似文献   

7.
Avalanche hazard and risk mapping is of utmost importance in mountain areas in Europe and elsewhere. Advanced methods have been developed to describe several aspects of avalanche hazard assessment, such as the dynamics of snow avalanches or the intensity of snowfall to assume as a reference meteorological forcing. However, relatively little research has been conducted on the identification of potential avalanche release areas. In this paper, we present a probabilistic assessment of potential avalanche release areas in the Italian Autonomous Province of Bolzano, eastern Alps, using the Weights of Evidence and Logistic Regression methods with commonly available GIS datasets. We show that a data-driven statistical model performs better than simple, although widely adopted, screening criteria that were proposed in the past, although the complexity of observed release areas is only partly captured by the model. In the best case, the model enables predicting about 70 % of avalanches in the 20 % of area classified at highest hazard. Based on our results, we suggest that probabilistic identification of potential release areas could provide a useful aid in the screening of sites for subsequent, more detailed hazard assessment.  相似文献   

8.
滑坡灾害持续影响着人民生命财产安全和地区社会经济可持续发展,滑坡危险性评价能够为防灾减灾和区域规划提供有效的理论依据。以福建省南平市为研究区,区内1711个历史滑坡灾害点,选择高程、坡度、坡向、曲率、地质岩性、土壤类型、降雨、水系、土地利用类型、公路和铁路共11个影响因子构成基本评价体系。使用Spearman相关系数对各因子进行共线性分析。基于1711个滑坡样本和1711个随机选取的非滑坡样本数据,利用人工神经网络模型对研究区进行了滑坡危险性评价,并利用混淆矩阵和接收者操作特征曲线（ROC）对模型进行验证。结果表明:混淆矩阵精度84.91%,ROC曲线下面积AUC值0.93,说明模型具有较高精度和预测率。使用自然间断法将滑坡危险性分为5个等级,结果表明研究区内危险性最高地区位于延平区和浦城县,顺昌县和松溪县次之,其余地区多为低危险区和较低危险区。研究结果可为当地区域规划和防灾减灾工程提供一定的理论依据和科学指导。  相似文献   

9.
Snow avalanche hazards in mountainous areas of developing countries have received scant attention in the scientific literature. The purpose of this paper is to describe this hazard and mitigative measures in Kaghan Valley, Pakistan Himalaya, and to review alternatives for future reduction of this hazard. Snow avalanches have long posed a hazard and risk to indigenous populations of the Himalaya and Trans-Himalaya mountains. Land use intensification due to population growth, new transportation routes, military activity and tourism is raising levels of risk. The history of land use in the study area is such that investigations of avalanche hazard must rely on different theoretical bases and data than in most industrialised countries. Despite the intensive use of valley-bottom land which is affected by avalanches, a number of simple measures are currently employed by the indigenous population to mitigate the hazard. Out-migration during the winter months is the most important one. During the intensive use period of summer avalanche-transported snow provides numerous resources for the population. In Kaghan the avalanche hazard is increasing primarily as a result of poorly located new buildings and other construction projects. The large scale of avalanche activity there rules out any significant improvement or protection of the currently difficult winter access. Instead, future mitigation of the hazard should focus on protecting the small number of winter inhabitants and minimising property damage.  相似文献   

10.
In this paper, a quantitative landslide hazard model is presented for transportation lines, with an example for a road and railroad alignment, in parts of Nilgiri hills in southern India. The data required for the hazard assessment were obtained from historical records available for a 21-year period from 1987 to 2007. A total of 901 landslides from cut slopes along the railroad and road alignment were included in the inventory. The landslides were grouped into three magnitude classes based on the landslide type, volume, scar depth, and run-out distance. To calculate landslide hazard, we estimated the total number of individual landslides per kilometer of the (rail) road for different return periods, based on the relationship between past landslides (recorded in our database) and triggering events. These were multiplied by the probability that the landslides belong to a given magnitude class. This gives the hazard for a given return period expressed as the number of landslides of a given magnitude class per kilometer of (rail) road. The relationship between the total number of landslides and the return period was established using a Gumbel distribution model, and the probability of landslide magnitude was obtained from frequency–volume statistics. The results of the analysis indicate that the total number of landslides, from 1- to 50-year return period, varies from 56 to 197 along the railroad and from 14 to 82 along the road. In total, 18 hazard scenarios were generated using the three magnitude classes and six return periods (1, 3, 5, 15, 25, and 50 years). The hazard scenarios derived from the model form the basis for future direct and indirect landslide risk analysis along the transportation lines. The model was validated with landslides that occurred in the year 2009.  相似文献   

11.
China is one of the countries where landslides caused the most fatalities in the last decades.The threat that landslide disasters pose to people might even be greater in the future,due to climate change and the increasing urbanization of mountainous areas.A reliable national-scale rainfall induced landslide suscep-tibility model is therefore of great relevance in order to identify regions more and less prone to landslid-ing as well as to develop suitable risk mitigating strategies.However,relying on imperfect landslide data is inevitable when modelling landslide susceptibility for such a large research area.The purpose of this study is to investigate the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China.In this context,it is aimed to explore the benefit of mixed effects mod-elling to counterbalance associated bias propagations.Six influencing factors including lithology,slope,soil moisture index,mean annual precipitation,land use and geological environment regions were selected based on an initial exploratory data analysis.Three sets of influencing variables were designed to represent different solutions to deal with spatially incomplete landslide information:Set 1(disregards the presence of incomplete landslide information),Set 2(excludes factors related to the incompleteness of landslide data),Set 3(accounts for factors related to the incompleteness via random effects).The vari-able sets were then introduced in a generalized additive model(GAM:Set 1 and Set 2)and a generalized additive mixed effect model(GAMM:Set 3)to establish three national-scale statistical landslide suscep-tibility models:models 1,2 and 3.The models were evaluated using the area under the receiver operating characteristics curve(AUROC)given by spatially explicit and non-spatial cross-validation.The spatial pre-diction pattern produced by the models were also investigated.The results show that the landslide inven-tory incompleteness had a substantial impact on the outcomes of the statistical landslide susceptibility models.The cross-validation results provided evidence that the three established models performed well to predict model-independent landslide information with median AUROCs ranging from 0.8 to 0.9.However,although Model 1 reached the highest AUROCs within non-spatial cross-validation(median of 0.9),it was not associated with the most plausible representation of landslide susceptibility.The Model 1 modelling results were inconsistent with geomorphological process knowledge and reflected a large extent the underlying data bias.The Model 2 susceptibility maps provided a less biased picture of landslide susceptibility.However,a lower predicted likelihood of landslide occurrence still existed in areas known to be underrepresented in terms of landslide data(e.g.,the Kuenlun Mountains in the northern Tibetan Plateau).The non-linear mixed-effects model(Model 3)reduced the impact of these biases best by introducing bias-describing variables as random effects.Among the three models,Model 3 was selected as the best national-scale susceptibility model for China as it produced the most plausible portray of rainfall induced landslide susceptibility and the highest spatially explicit predictive perfor-mance(median AUROC of spatial cross validation 0.84)compared to the other two models(median AUROCs of 0.81 and 0.79,respectively).We conclude that ignoring landslide inventory-based incomplete-ness can entail misleading modelling results and that the application of non-linear mixed-effect models can reduce the propagation of such biases into the final results for very large areas.  相似文献   

12.
The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.  相似文献   

13.
This paper is focussed on the hazard impact of landslides in the Three Gorges, and represents the progression of our ongoing study on regional land instability assessment in the Three Gorges area using imagery data from the Advanced Spaceborne Thermal Emission Radiometer (ASTER). The key development here is the establishment of a model that integrates land instability with several factors that can relate hazard to human life, such as slope failures occurring in proximity to built-up areas and roads, and areas of high landslide risk along the bank of Yangtze and its major tributaries. The method correctly identifies some of the known destructive landslides in the region, like Qianjiangping and Huangtupo, as belonging to areas of potentially high landslide impact. Our results suggest that several population centres, including the towns of Wushan and Badong, are rated at high landslide hazard levels. This study highlights the importance of differentiating between landslide types within susceptibility assessment, and identifies those locations in the Three Gorges where the probability of landslide occurrence with negative impact to life and property is greatest.  相似文献   

14.
用光学遥感数据和地理信息系统(GIS)分析了马来西亚Selangor地区的滑坡灾害。通过遥感图像解译和野外调查,在研究区内确定出滑坡发生区。通过GIS和图像处理,建立了一个集地形、地质和遥感图像等多种信息的空间数据库。滑坡发生的因素主要为:地形坡度、地形方位、地形曲率及与排水设备距离;岩性及与线性构造距离;TM图像解译得到的植被覆盖情况;Landsat图像解译得到的植被指数;降水量。通过建立人工神经网络模型对这些因素进行分析后得到滑坡灾害图:由反向传播训练方法确定每个因素的权重值,然后用该权重值计算出滑坡灾害指数,最后用GIS工具生成滑坡灾害图。用遥感解译和野外观测确定出的滑坡位置资料验证了滑坡灾害图,准确率为82.92%。结果表明推测的滑坡灾害图与滑坡实际发生区域足够吻合。  相似文献   

15.
Fatal landslides in Europe   总被引：4，自引：3，他引：1  
Landslides are a major hazard causing human and large economic losses worldwide. However, the quantification of fatalities and casualties is highly underestimated and incomplete, thus, the estimation of landslide risk is rather ambitious. Hence, a spatio-temporal distribution of deadly landslides is presented for 27 European countries over the last 20  years (1995–2014). Catastrophic landslides are widely distributed throughout Europe, however, with a great concentration in mountainous areas. In the studied period, a total of 1370 deaths and 784 injuries were reported resulting from 476 landslides. Turkey showed the highest fatalities with 335. An increasing trend of fatal landslides is observed, with a pronounced number of fatalities in the latest period from 2008 to 2014. The latter are mostly triggered by natural extreme events such as storms (i.e., heavy rainfall), earthquakes, and floods and only minor by human activities, such as mining and excavation works. Average economic loss per year in Europe is approximately 4.7 billion Euros. This study serves as baseline information for further risk mapping by integrating deadly landslide locations, local land use data, and will therefore help countries to protect human lives and property.  相似文献   

16.
Shallow landslides induced by heavy rainfall events represent one of the most disastrous hazards in mountainous regions because of their high frequency and rapid mobility. Recent advancements in the availability and accessibility of remote sensing data, including topography, land cover and precipitation products, allow landslide hazard assessment to be considered at larger spatial scales. A theoretical framework for a landslide forecasting system was prototyped in this study using several remotely sensed and surface parameters. The applied physical model SLope-Infiltration-Distributed Equilibrium (SLIDE) takes into account some simplified hypotheses on water infiltration and defines a direct relation between factor of safety and the rainfall depth on an infinite slope. This prototype model is applied to a case study in Honduras during Hurricane Mitch in 1998. Two study areas were selected where a high density of shallow landslides occurred, covering approximately 1,200 km2. The results were quantitatively evaluated using landslide inventory data compiled by the United States Geological Survey (USGS) following Hurricane Mitch’s landfall. The agreement between the SLIDE modeling results and landslide observations demonstrates good predictive skill and suggests that this framework could serve as a potential tool for the future early landslide warning systems. Results show that within the two study areas, the values of rates of successful estimation of slope failure locations reached as high as 78 and 75%, while the error indices were 35 and 49%. Despite positive model performance, the SLIDE model is limited by several assumptions including using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this physically based model are discussed with respect to future applications of landslide assessment and prediction over large scales.  相似文献   

17.
区域滑坡危险性评价方法还存在许多需要完善和改进的地方。以工程地质类比法为基础,用滑坡的面密度表示滑坡发生的危险性大小,基于线性代数中QR分解理论,提出了一种用高次多项式拟合致险因子与滑坡危险性间关系的算法,并把该算法与层次分析法模型、条件概率模型相融合,建立了一种改进的区域滑坡危险性评价模型。然后,通过在Visual Studio.Net C#环境下借助ArcEngine组件的二次开发实现了该模型。最后选取陕西省麟游县为实验区域,利用上述模型进行了滑坡危险性评价。经实际资料检验表明,该模型具有较高的可信度,可应用于今后的滑坡危险性区域评价工作中。  相似文献   

18.
多源遥感数据支持下区域滑坡灾害风险评价   总被引：1，自引：0，他引：1  
滑坡风险管理是防灾减灾的有效途径之一,而灾害风险评价是风险管理的基础和依据。以三峡库首区为研究区、多源遥感影像为主要数据源,利用立体像对技术及光谱分析等方法快速提取地形地貌、地表覆被、地质及水文条件等滑坡孕灾环境信息,应用随机森林模型分析区域滑坡危险性;采用面向对象方法建立典型承灾体识别规则,快速提取建筑物及交通道路等信息,综合分析滑坡危险性及承灾体信息,以实现区域滑坡灾害风险评价。结果显示:高风险区面积为41 km2,约占研究区面积的9%,主要集中于人口聚集的城镇和交通建设用地等经济价值大的地区。其评价结果与野外实地调查情况基本吻合。  相似文献   

19.
A practical application of a simple and economical solution to landslide hazard zonation based on slope stability analysis was carried out in the Veľká Čausa landslide, Horná Nitra region, central Slovakia. The region is prone to different types of slope deformation controlled by geological structure, physical and mechanical properties of materials, complicated hydrogeological setting, undulating morphology, and man-made influence. Taking into consideration the cause of the landslide, identified as groundwater change, two scenarios of landslide activity have been investigated. Scenario 1 considers the maximum groundwater level recorded from March 1995 to October 1998, corresponding to the period starting from the most recent landslide activity up to the end of remediation work. Scenario 2 considers the maximum groundwater level recorded from November 1998 to December 2004, after the remediation works, and corresponding to the actual situation of the landslide. It has been found from this study that slope angle has the highest influence on landslide instability in the Veľká Čausa landslide. Therefore, high resolution Digital Elevation Model (DEM) is essential for obtaining reasonable results. In addition, an appropriate selection of the model input parameters (e.g., shear strength) is very important. The validation between the calculated landslide hazard zonation map and results of monitoring survey were examined. The results show moderate to good agreement with the inclinometric and geodetic measurements. It was also verified that the most active part of the landslide is the north-western side.  相似文献   

20.
Landslide magnitude–frequency curves allow for the probabilistic characterization of regional landslide hazard. There is evidence that landslides exhibit self-organized criticality including the tendency to follow a power law over part of the magnitude–frequency distribution. Landslide distributions, however, also typically exhibit poor agreement with the power law at smaller sizes in a flattening of the slope known as rollover. Understanding the basis for this difference is critical if we are to accurately predict landslide hazard, risk or landscape denudation over large areas. One possible argument is that the magnitude–frequency distribution is dominated by physiographic controls whereby landslides tend to a larger size, and larger landslides are landscape limited according to a power law. We explore the physiographic argument using first a simple deterministic model and then a cellular automata model for watersheds in coastal British Columbia. The results compare favorably to actual landslide data: modeled landslides bifurcate at local elevation highs, deposit mass preferentially where the local slopes decrease, find routes in confined valley or channel networks, and, when sufficiently large, overwhelm the local topography. The magnitude–frequency distribution of both the actual landslides and the cellular automata model follow a power law for magnitudes higher than 10,000–20,000 m2 and show a flattening of the slope for smaller magnitudes. Based on the results of both models, we argue that magnitude–frequency distributions, including both the rollover and the power law components, are a result of actual physiographic limitations related to slope, slope distance, and the distribution of mass within landslides. The cellular automata model uses simple empirically based rules that can be gathered for regions worldwide.  相似文献   

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