海量地形技术对于数字地球的实现起着举足轻重的作用。
Massire terrain technology is very important to the realization of digital-earth.
本文提出了一个有效的基于外存的海量地形数据实时可视化框架。
In this paper, we propose an efficient framework for large-scale terrain real-time visualization.
实验结果表明，该研究成果能够实现真实感海量地形数据的实时可视化与交互操作。
The experiment results show that this approach can achieve good performance for real-time rendering of massive terrain dataset.
国内外对海量地形数据的研究比较深入，但对具有一般意义的海量地层数据研究较少。
There are deeper research and study about large-scale terrain data all over the world, but the study about large-scale stratum data with common interest is little.
国内外对海量地形数据的研究比较深入，但对具有一般意义的海量地层数据研究较少。
The research on massive-scale geographic data was carried on for a long time. But general formation data has not been studied carefully.
海量地形影像数据的快速浏览是GIS、虚拟现实、数字地球等领域应用的关键技术与难点之一。
Walkthrough in massive terrain and image data is a key technology and a difficult problem of GIS, VR and Digital Earth, etc.
设计了一种适合网络实时传输海量地形数据的传输协议，使系统充分利用网络带宽同时又不浪费带宽。
Furthermore, one type of protocol real-timely transferring massive terrain data on network is introduced for plenty using but not wasting the bandwidth resource of network.
三维表现系统，是建立在计算机图形绘制技术的基础上，对地球表面的海量地形和城市中的大规模建筑群进行实时绘制的系统。
A 3D rendering system is such a system that draws the massive terrain and cities on the earth based on computer graphic technology.
为满足基于网络的大规模地形漫游系统中有限的网络带宽与海量地形数据之间的矛盾，提出了一种三维地形流式渐进传输方法。
To solve the contradictions between the limited network bandwidth and the mass of terrain data, a new approach of terrain data streaming transformation was proposed.
随着分布式虚拟GIS在仿真和军事中的应用需求，大范围，海量地形数据在网络环境下实时绘制技术成为GIS研究的重点之一。
The increasing application demand of distributed virtual GIS in terrain landscape and military has made real-time interactive browsing massive terrain data in large areas under network environment.
随着分布式虚拟GIS在仿真和军事中的应用需求，大范围，海量地形数据在网络环境下实时绘制技术成为GIS研究的重点之一。
The increasing application demand of distributed virtual GIS in terrain landscape and military has made real-time interactive browsing massive terrain data in large areas under network environment.
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