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81.
Transect-based three-dimensional road modeling and visualization 总被引:3,自引:0,他引:3
LIQingquan TANGLuliang ZUOXiaoqing LIHanwu 《地球空间信息科学学报》2004,7(1):14-17
On the basis of the study on road elements and the existing three-dimensional road data models, this paper puts forward the transect-based road modeling, resolves the modeling of the simplest road with two road transects, and fulfils the visualization of the road. OpenGL is applied as the tool of visualization. The map texture technology, LOD algorithm and dynamic multi-differentiating texture technology are of benefit to the construction of 3D road GIS, and improve the speed of roaming and effective visualization. This paper also disusses the combination of 2D digitall road map and 3D road scene, and the dynamic response between them. Finally, on the basis of the research on the transect-based road model, this paper develops the three-dimen-sional road geographic information system called virtual road ( VRoad ), which not only supplies road designers with a set of tool which can turn the designed 2D road data into 3D road and the high road assistant function area in computer, but also supplies the road management with a set of tool which can realize the road real time and interactive roaming, high-efficiency management. 相似文献
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用国际地球自转服务提供的高精度日长序列ΔLOD(IERS(EOP99C04),和由美国国家环境预报中心(NCEP)对过去的气象资料进行重新分析和计算,提供的轴向大气角动量序列(AAM)来研究大气和带谐潮汐对地球自转变化(ΔLOD)中高频振荡激发的贡献。由Multitaper功率谱分析表明,ΔLOD序列在9.13d(天)、13.63d、13.66d、27.55d周期时呈现出比较强的谱峰,这些谱都在95%的显著性水平以上,有比较强的信噪比。从ΔLOD和AAM之差值序列谱分析结果及地球带谐响应系数k的估计,表明大气不是ΔLOD的高频变化的主要激发源。根据理论潮汐周期可知,有可能存在其它的激发源,如海洋对地球自转变化的激发。这还有待于进一步深入探讨。 相似文献
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多细节层次的三维植被符号设计 总被引:1,自引:0,他引:1
三维符号作为三维地图表达的重要组成部分,可以有效增强三维地图场景的可识读性。针对三维符号的基本概念、设计原则和共享机制等问题,该文从符号细节层次、视觉变量和排列方式3个方面展开研究,提出了一种三维植被符号构建模型,以典型植被对象为例进行了实现。由于植被对象种类繁多、形状不规则、结构复杂,因而建立简单、规则、通用的图形符号来表达植被对象,具有特殊性。在符号设计中特别地考虑了植被部分物候现象的表达,丰富了植被符号的语义内涵。 相似文献
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In the task of 3D building model reconstruction from point clouds we face the problem of recovering a roof topology graph in the presence of noise, small roof faces and low point densities. Errors in roof topology graphs will seriously affect the final modelling results. The aim of this research is to automatically correct these errors. We define the graph correction as a graph-to-graph problem, similar to the spelling correction problem (also called the string-to-string problem). The graph correction is more complex than string correction, as the graphs are 2D while strings are only 1D. We design a strategy based on a dictionary of graph edit operations to automatically identify and correct the errors in the input graph. For each type of error the graph edit dictionary stores a representative erroneous subgraph as well as the corrected version. As an erroneous roof topology graph may contain several errors, a heuristic search is applied to find the optimum sequence of graph edits to correct the errors one by one. The graph edit dictionary can be expanded to include entries needed to cope with errors that were previously not encountered. Experiments show that the dictionary with only fifteen entries already properly corrects one quarter of erroneous graphs in about 4500 buildings, and even half of the erroneous graphs in one test area, achieving as high as a 95% acceptance rate of the reconstructed models. 相似文献