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tobia指数
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  tobia index
     Based on the prepared landslides database,two landslide factors,slope and TOBIA index have been combined into the binary logistic regression model.
     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。
短句来源
     The regression function has classified successfully increased from 55% to 71.5% of the overall slope population after index is added. The results show that TOBIA index can be a quantitative causative factor data source for landslide hazard assessment.
     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。
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  “tobia指数”译为未确定词的双语例句
     Topographic/bedding-plane intersection angle(TOBIA) index produces spatially distributed fields of geometric alignment between topography and the orientation of geologic bedding planes.
     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。
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  相似匹配句对
     Index number for atmospheric pollution
     大气污染指数
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     Service Quality Index
     服务质量指数
     Topographic/bedding-plane intersection angle(TOBIA) index produces spatially distributed fields of geometric alignment between topography and the orientation of geologic bedding planes.
     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。
短句来源
     Based on the prepared landslides database,two landslide factors,slope and TOBIA index have been combined into the binary logistic regression model.
     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。
短句来源
     The regression function has classified successfully increased from 55% to 71.5% of the overall slope population after index is added. The results show that TOBIA index can be a quantitative causative factor data source for landslide hazard assessment.
     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。
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The geometric alignment or conformity between strikes of slope and geologic bedding planes such as soft or weak stratum surfaces is one of the causative factors of hillslope landslide.Topographic/bedding-plane intersection angle(TOBIA) index produces spatially distributed fields of geometric alignment between topography and the orientation of geologic bedding planes.Computation and digital mapping of TOBIA index requires the derivation of four spatially distributed variables:topographic slope,slope aspect,bedding...

The geometric alignment or conformity between strikes of slope and geologic bedding planes such as soft or weak stratum surfaces is one of the causative factors of hillslope landslide.Topographic/bedding-plane intersection angle(TOBIA) index produces spatially distributed fields of geometric alignment between topography and the orientation of geologic bedding planes.Computation and digital mapping of TOBIA index requires the derivation of four spatially distributed variables:topographic slope,slope aspect,bedding dip,and dip azimuth.TOBIA index is useful for prediction of potential slope failure and a study area of Three Gorges reservoir is chosen to verify the correlation between TOBIA index and dip slope landslides.The application demonstrates that the method here can provide an efficient means for estimating slope type.Based on the prepared landslides database,two landslide factors,slope and TOBIA index have been combined into the binary logistic regression model.The regression function has classified successfully increased from 55% to 71.5% of the overall slope population after index is added.The results show that TOBIA index can be a quantitative causative factor data source for landslide hazard assessment.

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。

Landslide hazard assessment is necessary for disaster management and planning in dam projects.This paper presents a geographical information systems/remote sensing-aided procedure for landslide hazard mapping at a regional scale around the Qinggan River of the Three Gorges,China,where most of landslides are active in dip slopes.A landslide inventory is carried out based on field investigations and aerial photo interpretation,while another data set of environmental factors is constructed,such as geological and...

Landslide hazard assessment is necessary for disaster management and planning in dam projects.This paper presents a geographical information systems/remote sensing-aided procedure for landslide hazard mapping at a regional scale around the Qinggan River of the Three Gorges,China,where most of landslides are active in dip slopes.A landslide inventory is carried out based on field investigations and aerial photo interpretation,while another data set of environmental factors is constructed,such as geological and topographic thematic maps,lithology and vegetation maps.The factors contributing to landslide occurrence such as altitude,slope and flow accumulation,are derived from Digital Elevation Models,and rock strata is also extracted from geological map,vegetation index from satellite images of Landsat TM bands 2/3/4.Quantitative geometric alignment relationships between strikes of slopes and strata are established by TOBIA index,and a method of generalized likelihood ratio is then utilized to analyze the relationships between landslide occurrence and environmental factors,such as lithology,slope angle,aspect,flow accumulation and vegetation,etc.Based on the database,the casual factors,which make possible contribution to landslide occurrence,are combined into a binary logistic regression model,and then the landslide probabilities are calculated by cell to cell.The results from the logistical regression model coincides well with the previous landslide occurrence.

以统计模型为基础、地理信息系统作为工具的滑坡灾害评价模式已经得到普遍认可和使用,数字高程模型(DEM)、遥感影像、区域地质调查资料已经成为区域滑坡评价研究的因子数据源。选择三峡库区青干河流域顺向坡滑坡多发地段为研究区,在滑坡编目数据库基础上,通过:(1)数字高程模型获取高程、坡度、地形聚水能力因子;(2)遥感影像获取植被指数;(3)区域地质调查资料、数字高程模型计算斜坡类型定量因子TOBIA指数及获取岩石地层单元因子。采用二分类变量逻辑回归评价方法对上述6种因子建立滑坡危险性评价模型,开展地理信息系统/遥感技术支持下顺向坡滑坡危险性评价研究。研究结果表明,根据模型概率值分布和已知滑坡发育关系,可以将研究区划分为高危险区、中等危险区、低危险区3个等级,高危险区包含70%已知滑坡,中等危险区包含14%已知滑坡,评价结果和实际滑坡发育情况吻合,合理地反映区内滑坡灾害发育的总体特征。

 
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