Visualizing Spatial Distribution Data Sets
Visualizing Spatial Distribution Data Sets
复制标题
可视化空间分布数据集
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
A. Pang
中科院分区：
文献类型：
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作者：
Alison Luo;D. Kao;J. Dungan;A. Pang
在本文中，我们将分布定义为一种新的数据类型，并解决了可视化空间分布数据集的挑战。目前存在许多用于处理标量数据的可视化技术。也就是说，在每个空间位置处存在标量值，其也可以随时间变化。同样，存在用于处理向量、张量和多变量数据集的技术。然而，目前没有系统的方法来处理分布数据，其中在每个位置和时间都有相同变量的值的集合。随着计算机和传感器技术的不断改进，分布数据变得越来越普遍。它们还被用于从农业、工程设计和制造到天气预报的许多领域。本文提出的方法不是开发专门的可视化技术来处理分布数据，而是找到一种系统的方法来扩展现有的可视化方法来处理这种新的数据类型。例如，我们希望能够生成3D标量分布数据集的等值面，或生成矢量分布数据集的流线。为了实现这一目标，我们建议使用一组数学和程序定义的运算符，使我们能够直接对分布进行工作。彩色图像也可以在www.cse.ucsc.edu/research/avis/operator.html上找到。
In this paper, we define distributions as a new data type and address the challenges of visualizing spatial distribution data sets. Numerous visualization techniques exist today for dealing with scalar data. That is, there is a scalar value at each spatial location, which may also be changing over time. Likewise, techniques exist for dealing with vector, tensor and multivariate data sets. However, there is currently no systematic way of dealing with distribution data where there is a collection of values for the same variable at every location and time. Distribution data is increasingly becoming more common as computers and sensor technologies continue to improve. They have also been used in a number of fields ranging from agriculture, engineering design and manufacturing to weather forecasting. Rather than developing specialized visualization techniques for dealing with distribution data, the approach presented in this paper is to find a systematic way of extending existing visualization methods to handle this new data type. For example, we would like to be able to generate isosurfaces of 3D scalar distribution data sets, or generate streamlines of vector distribution data sets. In order to accomplish this goal, we propose the use of a set of mathematically and procedurally defined operators that allow us to work directly on distributions. Color images can also be found in www.cse.ucsc.edu/research/avis/operator.html.