球面退化四叉树格网的剖分及变形分析

为有效解决经纬度格网与四元三角网(QTM)在全球空间数据管理与操作中存在的不足,提出一种新的全球离散格网剖分方法——球面退化四叉树格网(DQG),给出该格网的剖分原理与编码规则,并对其进行几何变形计算与分析。结果表明:DQG既具有经纬度格网结构简单的特征,又具有QTM几何变形稳定等优点。     

球面DQG地址码与经纬度坐标的快速转换算法

为了解决传统球面格网与经纬度坐标在转换效率或精度上存在的问题,提出一种新的转换算法.在分析球面退化四叉树格网(DQG)的剖分原理及其编码规则的基础上,给出DQG单元的行列定义规则,并设计了一套地址码与经纬度之间快速坐标转换的详细算法;将该算法与QTM行列逼近法、ZOT投影法及ETP投影法进行效率对比实验,结果表明:对于100万个DQG格网单元,其转换算法的平均耗时量为上述传统算法的53%、39%和7%,且避免了QTM行列逼近法出现的半格网误差现象,精度较高.     

基于球面DQG的矢量与地形数据无缝集成

现有的全球大规模空间数据可视化系统主要侧重于影像和地形数据的综合表达,针对矢量与地形的集成可视化能力相对较弱。该文以球面退化四叉树格网(Degenerate Quad-tree Grids,DQG)为基础,通过DQG格网的三角化过程构建了地表DEM模型,并提出了从矢量线对象到地形格网表面的映射方法。采用GTOPO30数据集和国界矢量数据进行了相关实验,结果表明:该方法能实现矢量数据与多分辨率DEM的无缝集成,并能有效地避免矢量对象"悬浮"和"入地"等现象。     

基于QTM的海平面上升分析与模拟

针对海平面上升影响范围分析与模拟这一国际前沿问题,通过研究基于球面四元三角网(QTM)的关键技术问题,包括复杂拓扑关系计算、LOD剖分、球面水淹分析、基于QTM的多分辨率的DEM数据组织方法和分析精度的相关性评定等,以.Net和Direct3D为开发工具,设计开发了基于QTM的海平面上升影响范围评估模型。该研究结果可为全球海平面上升影响的防灾减灾决策提供有效支撑,并推动了球面数据模型和球面格网拓扑分析的理论成果在全球变化预测相关领域的应用进展。     

一种改进的DQG格网编码与经纬度高效转换算法

格网编码与经纬度间的转换效率是影响格网应用的关键因素。现有转换算法难以满足海量空间大数据的实时计算与分析需求,效率有待提升。为此,该文提出一种改进的DQG格网编码与经纬度高效转换算法:首先,引入二进制DQG格网编码代替四进制编码;然后,根据DQG格元的分布特征推导出格元行号和经度差的关系,以此改进格元列号的计算过程;最后,使用查找表进行Morton码的编码和解码,以提高转换效率。实验结果表明,该文提出的DQG格网编码与经纬度转换算法的平均效率分别是四进制DQG、单层二维SDZ算法的20.15倍和4.58倍,基本满足海量格网数据的实时转换与计算需求,为海量空间大数据的高效计算与分析奠定了基础。     

一种基于球面QTM格网的面要素边界跟踪填充算法

为实现四元三角网(Quaternary Triangular Mesh,QTM)对球面面状要素矢量数据的离散化及可视化,该文将基于栅格单元的"边界代数法"扩展到球面三角格网单元,提出了一种基于QTM格网的边界跟踪填充算法,主要内容包括:通过ETP投影实现球面QTM格网与平面三角格网的相互转换,建立矢量线角度与三角格元邻近搜索的对应关系;"边界跟踪"并记录边界格元进行分类处理;最终给出"边界跟踪"下两种不同的填充模式。实验表明,该算法实现了球面矢量多边形在QTM格网中的填充。     

全球离散格网的建模方法及基本问题

全球离散格网(Discrete Global Grid,DGG)模型是数字地球及空间信息格网的基础,不同的建模方法不但影响空间数据的存储和管理效率,而且影响全球GIS的操作功能。该文介绍了DGG的评价标准,将DGG的建模方法归纳为3种类型:经纬度格网模型、自适应格网模型和正多面体格网模型,重点分析了不同类型球面离散格网模型的几何结构、单元特征和应用模式。最后,提出了DGG在Global GIS中亟待解决的基本问题,包括编码、精度、应用、误差、整合和定位问题。     

DEM结构特征对坡度坡向的影响分析

数字高程模型已严格定义为按规则格网阵列记录的地形高程数据,其固有的结构特征(如格网分辨率、格网方向、高程数据准确度等)直接影响DEM对地形表达和坡度、坡向的计算精度。该文通过理论和数据独立的DEM实验分析方法,研究了DEM结构特征对坡度、坡向的影响,得出如下结论:1)高分辨率的DEM并不一定能给出高精度的坡度、坡向计算结果;2)可通过g=bm/ms×180/π×cos2S来选择合适的DEM分辨率;3)三阶不带权差分算法的坡度、坡向计算结果对DEM方向有较强的依赖性。     

顾及地形特征语义约束的高保真地形建模方法探索

地形建模过程中常缺乏对地形整体特征的表达,这导致了当前地形模型中地形局部特征并不符合地形对象属性这一失真现象的出现。该文提出了"地形语义"概念来实现对地形局部特征的描述,通过语义的形式化表达实现了对其区域内高程的约束,同时设计了语义DEM(S-DEM)概念模型,基于与现有格网DEM兼容的数据结构,实现了顾及语义的内插方法,并通过建立三维原型系统实现了S-DEM的三维表达。与传统方法相比,S-DEM模型保证了地形区域特征与地形属性的一致性,确保了地形局部特征与垂直面的表达。研究结果表明,地形语义在本质上是地形对象特征的体现,同时在数据结构上依赖于地形的面向对象表达。     

平面影像到QTM像元的转换算法及精度分析

平面影像数据到四元三角网(Quaternary Triangular Mesh,QTM)像元的转换是实现全球QTM格网影像无缝建模的首要任务。提出基于面积权的数据转换方法,给出不同类型的权重及格网值的计算,并利用ArcGIS中256级灰度的Wsiearth.tif图像数据分析了转换精度。结果表明:将4 km分辨率的影像数据转换到12层的QTM像元时,转换误差在0~2灰度内占96.27%,对一般应用的影响可以忽略不计。     

Equal arc ratio projection and a new spherical triangle quadtree model

A projection family, named Equal Arc Ratio Projection (EARP), is proposed in this paper, which has two kinds of geometric cases. Coordinates in the projections are determined by the ratios between four special arcs. The projection for spherical octahedron is derived, which is available for Dutton's Quaternary Triangular Mesh (QTM), and both projections of Goodchild's and Otoo's for QTM are found to be two special implementations of EARP. The icosahedral projection and thus the corresponding spherical triangle quadtree partition model are also developed. The partition model is compared with several other global grid models.     

Reducing the grid orientation dependence of flow routing on square-grid digital elevation models

Topographical parameters derived from digital elevation models by employing flow routing algorithms may depend on the orientation of the square grid. Grid orientation dependence results from the insufficient isotropy of square grid and affects the flow directions and subsequent calculations based on flow routing. In this article, a systematic approach for analysing the rotational invariance of flow accumulation calculations is presented and applied. Computed flow accumulation maps are found to depend strongly on the grid orientation, especially if flow routing methods with low dispersion are used. It is also shown that isotropy of flow routing algorithms can be significantly improved by introducing a numerical parameter resulting in adjustable weighting for cardinal and diagonal directions in flow routing. The actual value of this parameter depends on the used flow routing method.     

山体效应对北半球林线分布的影响(英文)

Alpine timberline, as the "ecological transition zone," has long attracted the attention of scientists in many fields, especially in recent years. Many unitary and dibasic fitting models have been developed to explore the relationship between timberline elevation and latitude or temperature. However, these models are usually on regional scale and could not be applied to other regions; on the other hand, hemispherical-scale and continental-scale models are usually based on about 100 timberline data and are necessarily low in precision. The present article collects 516 data sites of timberline, and takes latitude, continentality and mass elevation effect(MEE) as independent variables and timberline elevation as dependent variable to develop a ternary linear regression model. Continentality is calculated using the meteorological data released by WorldClim and mountain base elevation(as a proxy of mass elevation effect) is extracted on the basis of SRTM 90-meter resolution elevation data. The results show that the coefficient of determination(R2) of the linear model is as high as 0.904, and that the contribution rate of latitude, continentality and MEE to timberline elevation is 45.02%(p=0.000), 6.04%(p=0.000) and 48.94%(p=0.000), respectively. This means that MEE is simply the primary factor contributing to the elevation distribution of timberline on the continental and hemispherical scales. The contribution rate of MEE to timberline altitude differs in different regions, e.g., 50.49%(p=0.000) in North America, 48.73%(p=0.000) in the eastern Eurasia, and 43.6%(p=0.000) in the western Eurasia, but it is usually very high.     

A study of the contribution of mass elevation effect to the altitudinal distribution of timberline in the Northern Hemisphere简

Alpine timberline, as the ＂ecologica tion of scientists in many fields, especially in transition zone,＂ has long attracted the atten- recent years. Many unitary and dibasic fitting models have been developed to explore the relationship between timberline elevation and latitude or temperature. However, these models are usually on regional scale and could not be applied to other regions; on the other hand, hemispherical-scale and continental-scale models are usually based on about 100 timberline data and are necessarily low in precision. The present article collects 516 data sites of timberline, and takes latitude, continentality and mass elevation effect （MEE） as independent variables and timberline elevation as dependent variable to develop a ternary linear regression meteorological data released by WorldClim and model. Continentality is calculated using the mountain base elevation （as a proxy of mass elevation effect） is extracted on the basis of SRTM 90-meter resolution elevation data. The results show that the coefficient of determination （R2） of the linear model is as high as 0.904, and that the contribution rate of latitude, continentality and MEE to timberline elevation is 45.02% （p=0.000）, 6.04% （p=0.000） and 48.94% （p=0.000）, respectively. This means that MEE is simply the primary factor contributing to the elevation distribution of timberline on the continental and hemispherical scales. The contribution rate of MEE to timberline altitude dif- fers in different regions, e.g., 50.49% （p=0.000） in North America, 48.73% （p=0.000） in the eastern Eurasia, and 43.6% （p=0.000） in the western Eurasia, but it is usually very high.     

基于DEM的任意方向坡度计算方法

坡度是数字地形分析中重要的地形因子,在水文分析、土壤侵蚀模拟、地貌类型划分等地学分析及工程上均有广泛的应用。由于地形的各向异性,坡度在各个方向上并不相同。目前,基于DEM所提取的坡度,均是位于最陡方向上的坡度,而任意给定方向坡度计算是地学分析和工程应用中较为常见的问题。在对目前DEM坡度提取算法研究的基础上,通过数学分析,给出了格网DEM上任意方向格网点的坡度计算模型和计算流程,并给出了相应的计算实例,从而将坡度计算模型从特定方向推向任意方向,使DEM坡度计算更具普适性。     

山体效应对北半球林线分布的影响分析

通过搜集整理了北半球516 个林线数据, 结合WorldClim 气象数据计算了林线数据点上的大陆度, 并依据SRTM高程数据提取了林线处的山体基面高度(作为山体效应的代用因子), 然后以纬度、大陆度和山体基面高度为解释变量, 建立三元回归模型。结果表明:线性回归模型的判定系数R²为0.904, 二次回归模型的R²高达0.912。相比先前不考虑基面高度的林线分布模型(R² = 0.79), 纳入了山体基面高度的林线分布模型能够更加有效的拟合半球尺度的林线分布; 结果还表明, 山体基面高度对北半球林线高度分布的贡献率达到了48.94% (p =0.000), 而纬度和大陆度分别为45.02% (p = 0.000) 和6.04% (p = 0.000)。这揭示了山体效应对半球尺度林线分布具有重要的影响。基面高度在北美洲地区对林线高度的贡献率最大(50.49%, p=0.000), 在欧亚大陆东部地区为48.73% (p = 0.000), 在欧亚大陆西部地区为43.6% (p=0.000)。这一结果说明山体效应对林线分布高度的影响虽有区域差异, 但都有较高的贡献率。     

山体效应及其对林线分布的影响(英文)

The concept of mass elevation effect(massenerhebungseffect,MEE) was intro-duced by A.de Quervain about 100 years ago to account for the observed tendency for temperature-related parameters such as tree line and snowline to occur at higher elevations in the central Alps than on their outer margins.It also has been widely observed in other ar-eas of the world,but there have not been significant,let alone quantitative,researches on this phenomenon.Especially,it has been usually completely neglected in developing fitting mod-els of timberline elevation,with only longitude or latitude considered as impacting factors.This paper tries to quantify the contribution of MEE to timberline elevation.Considering that the more extensive the land mass and especially the higher the mountain base in the interior of land mass,the greater the mass elevation effect,this paper takes mountain base elevation(MBE) as the magnitude of MEE.We collect 157 data points of timberline elevation,and use their latitude,longitude and MBE as independent variables to build a multiple linear regres-sion equation for timberline elevation in the southeastern Eurasian continent.The results turn out that the contribution of latitude,longitude and MBE to timberline altitude reach 25.11%,29.43%,and 45.46%,respectively.North of northern latitude 32°,the three factors’ contribu-tion amount to 48.50%,24.04%,and 27.46%,respectively;to the south,their contribution is 13.01%,48.33%,and 38.66%,respectively.This means that MBE,serving as a proxy indi-cator of MEE,is a significant factor determining the elevation of alpine timberline.Compared with other factors,it is more stable and independent in affecting timberline elevation.Of course,the magnitude of the actual MEE is certainly determined by other factors,including mountain area and height,the distance to the edge of a land mass,the structures of the mountains nearby.These factors need to be included in the study of MEE quantification in the future.This paper could help build up a high-accuracy and multi-scale elevation model for alpine timberline and even other altitudinal belts.     

Association of elevation error with surface type,vegetation class and data origin in discrete-returns airborne LiDAR

Airborne LiDAR (light detection and ranging) data are now commonly regarded as the most accurate source of elevation data for medium-scale topographical modelling applications. However, quoted LiDAR elevation error may not necessarily represent the actual errors occurring across all surfaces, potentially impacting the reliability of derived predictions in Geographical Information Systems (GIS). The extent to which LiDAR elevation error varies in association with land cover, vegetation class and LiDAR data source is quantified relative to dual-frequency global positioning system survey data captured in a 400-ha area in Ireland, where four separate classes of LiDAR point data overlap. Quoted elevation errors are found to correspond closely with the minimum requirement recommended by the American Society of Photogrammetry and Remote Sensing for the definition of 95% error in urban areas only. Global elevation errors are found to be up to 5 times the quoted error, and errors within vegetation areas are found to be even larger, with errors in individual vegetation classes reaching up to 15 times the quoted error. Furthermore, a strong skew is noted in vegetated areas within all the LiDAR data sets tested, pushing errors in some cases to more than 25 times the quoted error. The skew observed suggests that an assumption of a normal error distribution is inappropriate in vegetated areas. The physical parameters that were found to affect elevation error most fundamentally were canopy depth, canopy density and granularity. Other factors observed to affect the degree to which actual errors deviate from quoted error included the primary use for which the data were acquired and the processing applied by data suppliers to meet these requirements.