A Linear-Time Algorithm for the Aggregation and Visualization of Big Spatial Point Data

Christian Beilschmidt, T. Fober, Michael Mattig, B. Seeger
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引用次数: 7

Abstract

The visualization of spatial data becomes increasingly important in science, business and many other domains. In geography, data often corresponds to a large number of point observations that should be displayed on a constrained screen with limited resolution. This causes, however, a loss of information due to an overloaded and occluded visualization. In this paper we present a new visualization algorithm that avoids this problem by aggregating point data into a set of non-overlapping circles that capture all important information. Our algorithm based on a quadtree computes the circles in linear time with respect to the number of points.
空间大点数据聚合与可视化的线性时间算法
空间数据的可视化在科学、商业和许多其他领域变得越来越重要。在地理学中,数据通常对应于大量的点观测,这些点观测应该以有限的分辨率显示在受限的屏幕上。然而,这将导致信息的丢失,这是由于一个过载和闭塞的可视化。在本文中,我们提出了一种新的可视化算法,通过将点数据聚合到一组不重叠的圆中来捕获所有重要信息,从而避免了这个问题。我们基于四叉树的算法根据点的数量在线性时间内计算圆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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