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1.
GIS技术支持下的洪水模型建模 总被引：11，自引：4，他引：11
在复杂区域建立洪水模型时,计算网格的手工生成方法容易出错甚至不可行,自动生成算法则可大大节省计算网格生成的工作量。洪水模型中的计算网格与GIS栅格数据及不规则三角网空间数据结构非常相似,因此,GIS中成熟的网格自动生成算法可用于生成洪水模型计算网格。文章详细讨论了GIS支持下的洪水模型自动建立步骤,并以黄河下游花园口～夹河滩河段为例,利用地形图、土地利用图、水利工程设施分布、水文站点图等资料,通过自动生成网格及其空间拓扑关系,建立了洪水过程数值模拟模型,并详细解释了计算网格数据格式。 相似文献
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基于GIS的二维非结构化剖分网格优化 总被引：2，自引：1，他引：1
非结构化网格剖分是数值模拟的关键技术之一,网格质量直接影响到计算的收敛性和精确度。在GIS辅助建立非结构化网格空间拓扑关系的基础上,针对GIS和实际研究问题给出Spring-Laplace方法——一种新的单元尺度函数定义,在GIS空间算法下利用该方法优化节点位置,并基于推进阵面算法的思想,结合空间邻近拓扑关系实现了三角剖分节点和网格的重新编号算法,方便了开边界条件的赋值,提高了计算效率。实例表明,该方法大大提高了网格生成质量,能适应FVCOM数值模型对非结构化网格剖分的要求,其收敛速度快,具有较高的运算效率。 相似文献
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在分析现有非结构化网格剖分算法的基础上,提出了一种GIS支持下的改进分治算法实现约束Delaunay三角网格剖分.该方法利用了GIS的空间拓扑关系对算法输入数据进行预处理,基于三角形的统一数据结构实现了网格细化,对输出剖分网格进行准确的拓扑和约束条件的检查,并基于推进阵面算法思想,结合空间邻近拓扑关系实现了三角剖分节点和网格的重新编号,方便了实际问题中开边界条件的赋值,提高了计算效率.实例应用表明,该方法大大简化了数值模型非结构化网格剖分的前处理过程,集成了几种综合算法的优点,在保证原分治算法时间复杂度的基础上,提高了约束条件下Delaunay三角网格生成的质量. 相似文献
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《山地学报》2017,(2)
新疆果子沟区域是我国与中亚地区社会、经济、文化交流的重要通道以及我国石油、天然气等能源资源安全大通道,沿途滑坡灾害频发,威胁人类安全、影响社会、经济发展,但该区域针对滑坡灾害的研究程度较低,需借助滑坡灾害易发性分析与风险等级评估结果指导防灾减灾。本文基于GF-1号卫星影像数据进行滑坡解译,选取地层岩性、断层密度、坡度、坡向、地表高程、植被指数等6个评估因子,探讨运用GIS、RS技术及统计分析模型进行滑坡灾害易发性分析与建模。基于频率比法分析各因子敏感性,利用二元Logistic回归模型进行灾害易发性分析,将研究区滑坡灾害风险分为极低、低、中、高、极高五个等级。将模型计算结果与历史滑坡信息进行比较,并借助ROC Curve检验模型准确性,AUC为0.844,表明模型预测结果具有较高准确性,因此建立的分析模型可以满足新疆果子沟区域滑坡灾害分析与评估应用,研究成果可为研究区重大线型工程保护、边坡加固提供辅助决策支持。 相似文献
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滑坡是怒江流域主要的地质灾害,对流域内人民生命财产和生态系统安全带来了极大的危害,因此本研究针对研究区内滑坡灾害主要诱发因子进行判识。利用1991～2006年云南省减灾年鉴、长系列流域内相关站点的年平均降雨量、2006年云南省1：5万的TM影像数据等,以GIS技术为平台对其相关因子关联性进行统计与分析。研究发现：沿怒江干流发生的滑坡灾害主要受到坡度、植被盖度、降雨强度及公路建设等因子的影响,分析灾害点的分布与相关因子间的相关性,发现相关性比较密切的是坡度〉25。的地带;植被盖度为30％～70％的地带;年降水量达到1250—1500mm的地带,以及公路沿线的地带,并以相关性作为灾害发生风险度评价的权重,建立了基于GIS的滑坡灾害危险性评价模型,实现了对怒江干流区域滑坡灾害危险性区划。 相似文献
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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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在面向服务的分布计算架构中,企业服务总线(ESB)提供了服务间智能化集成、管理、中介和交互功能。在利用网格架构的面向服务体系结构中,总结如何利用ESB灵活、开放的集成异构多源的GIS平台和数据源。整体架构基于OGSA,服务集成采用ESB,网格门户和实际GIS平台通过ESB连接,形成基于总线消息驱动的智能化服务集成网格系统。该系统将在Internet平台上广泛互联现有的GIS资源,实现GIS"单系统映射"。通过细粒度服务搭建和配置,生成GIS实例,直接而简单地满足具体的业务需求。 相似文献
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河流对岸坡的侵蚀作用是滑坡失稳的重要因素之一,特别是在中国黄土地区。因此,探讨河流水位的季节性变化对黄土边坡稳定性的影响规律,对早期黄土滑坡灾害预警具有重要作用。论文以甘肃省天水市清泉村滑坡为例,分析5年内沿岸边坡形变速率与季节性水位变化之间的关系。基于SBAS-InSAR技术获取滑坡时序形变信息,借助MNDWI与DEM获取边坡底部时序水位信息,并结合GPM降雨数据进行相关性分析,研究发现随着降雨增多、河流水位的上涨,清泉村滑坡的形变速率明显增大,在夏季时滑坡形变量增长较快,并且边坡形变相较于水位季节变化具有一定的滞后性;经相关性分析,得出水位与滑坡形变的相关性系数为0.46,降雨与滑坡形变的相关性系数为0.39,表明清泉村滑坡的形变速率与水位变化更相关。因此,河流的季节性变化对滑坡形变速率具有一定影响,进而造成河流对沿岸滑坡的侵蚀作用呈现出季节性变化。研究揭示的黄土滑坡与河流水位的季节性变化关系,对揭示河岸边坡的演化过程、滑坡识别与灾害防治具有重要意义。 相似文献
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基于GIS的区域群发性降雨型滑坡时空预报研究 总被引：2，自引：0，他引：2
以滑坡灾害突出的雅安市雨城区为例,综合考虑降雨强度、前期降雨量及下垫面(地形、岩性、植被覆盖等)构建了基于GIS分析获取的易发指数+BP型神经网络时空预报模型。首先通过试验确定了模型的网络参数和网络结构,然后通过危险性区划图获取降雨型滑坡易发指数,并利用GIS的空间插值功能和雨量站数据获取相应降雨型滑坡的雨量数据,将量化后下垫面的易发指数和降雨数据作为神经元输入层数据。将模型应用于研究区,其中46个降雨型滑坡数据作为训练样本,10个降雨型滑坡数据作为检验样本,预测精度达到90%,显示该模型对于降雨型滑坡的时空预报精度较高。 相似文献
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Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN) 总被引：7，自引：0，他引：7
An efficient and accurate method of generating landslide susceptibility maps is very important to mitigate the loss of properties and lives caused by this type of geological hazard. This study focuses on the development of an accurate and efficient method of data integration, processing and generation of a landslide susceptibility map using an ANN and data from ASTER images. The method contains two major phases. The first phase is the data integration and analysis, and the second is the Artificial Neural Network training and mapping. The data integration and analysis phase involve GIS based statistical analysis relating landslide occurrence to geological and DEM (digital elevation model) derived geomorphological parameters. The parameters include slope, aspect, elevation, geology, density of geological boundaries and distance to the boundaries. This phase determines the geological and geomorphological factors that are significantly correlated with landslide occurrence. The second phase further relates the landslide susceptibility index to the important geological and geomorphological parameters identified in the first phase through ANN training. The trained ANN is then used to generate a landslide susceptibility map. Landslide data from the 2004 Niigata earthquake and a DEM derived from ASTER images were used. The area provided enough landslide data to check the efficiency and accuracy of the developed method. Based on the initial results of the experiment, the developed method is more than 90% accurate in determining the probability of landslide occurrence in a particular area. 相似文献
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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
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A dynamic model for rainfall-induced landslides on natural slopes 总被引：18，自引：0，他引：18
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基于SINMAP模型的区域滑坡危险性定量评估及模型验证 总被引：1，自引：0，他引：1
武利 《地理与地理信息科学》2012,28(2):35-39,113
利用稳定态水文学理论与无限斜坡稳定性模型,构建分布式斜坡稳定性定量评估模型SINMAP,以坡体滑塌十分发育的陕西省略阳县为试验区,利用Grid DEM提取坡度、流向、地形湿度指数和有效汇水面积等流域地形水文数据,将GIS专题图、遥感数据等作为模型输入数据,获得地表斜坡稳定性分级专题图,实现滑坡危险性定量评估;将模型模拟结果与目前国内最具有权威性的中国县(市)地质灾害调查结果进行对比分析,发现两者在稳定性分级标准划分、滑坡点定性评价、滑坡危险性分区等方面都具有很好的相似性和可比性,说明模型的模拟结果能够客观反映研究区地表滑坡危险性,对可能出现的滑坡具有一定的预测精度。因此,该模型的研究有望为定量分析区域滑坡与环境因子的关系、区域滑坡预测等工作奠定基础。 相似文献
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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
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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
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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
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GIS支持下基于支持向量机的滑坡危险性评价 总被引：1，自引：0，他引：1
以仙游县为例,探讨了将地理信息系统技术(GIS)和支持向量机(SVM)算法应用于滑坡灾害危险性评价的基本思路和技术路线。主要内容包括SVM的基本原理和方法、滑坡灾害危险性评价指标的选取和量化、SVM模型的建立以及具体的实现过程。实践证明该方法是一种较好的滑坡灾害危险性评价方法。 相似文献