A Hexagon Tile Map Algorithm for Displaying Spatial Data

IF 2.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
R Journal Pub Date : 2023-08-26 DOI:10.32614/rj-2023-021
Stephanie Kobakian, Dianne Cook, Earl Duncan
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引用次数: 0

Abstract

Spatial distributions have been presented on alternative representations of geography, such as cartograms, for many years. In modern times, interactivity and animation have allowed alternative displays to play a larger role. Alternative representations have been popularised by online news sites, and digital atlases with a focus on public consumption. Applications are increasingly widespread, especially in the areas of disease mapping, and election results. The algorithm presented here creates a display that uses tessellated hexagons to represent a set of spatial polygons, and is implemented in the R package called sugarbag. It allocates these hexagons in a manner that preserves the spatial relationship of the geographic units, in light of their positions to points of interest. The display showcases spatial distributions, by emphasising the small geographical regions that are often difficult to locate on geographic maps.
显示空间数据的六边形贴图算法
多年来,空间分布已经在地图等其他地理表示形式上呈现出来。在现代,交互性和动画使替代显示发挥了更大的作用。在线新闻网站和以公共消费为重点的数字地图集已经普及了其他的表现形式。应用越来越广泛,特别是在疾病制图和选举结果领域。这里介绍的算法创建了一个显示,该显示使用镶嵌六边形来表示一组空间多边形,并在名为sugarbag的R包中实现。它以一种保留地理单元的空间关系的方式分配这些六边形,根据它们到兴趣点的位置。通过强调通常难以在地理地图上定位的小地理区域,展示了空间分布。
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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来源期刊
R Journal
R Journal COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.70
自引率
0.00%
发文量
40
审稿时长
>12 weeks
期刊介绍: The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R. The R Journal intends to reach a wide audience and have a thorough review process. Papers are expected to be reasonably short, clearly written, not too technical, and of course focused on R. Authors of refereed articles should take care to: - put their contribution in context, in particular discuss related R functions or packages; - explain the motivation for their contribution; - provide code examples that are reproducible.
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