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請用此 Handle URI 來引用此文件: http://scholars.ntou.edu.tw/handle/123456789/5757
標題: Automatic generation of puzzle tile maps for spatial-temporal data visualization
作者: Lin, Shih-Syun 
Yang, Juo-Yu
Syu, Huang-Sin
Lin, Chao-Hung
Pai, Tun-Wen
關鍵字: 2D
公開日期: 八月-2019
出版社: PERGAMON-ELSEVIER SCIENCE LTD
卷: 82
起(迄)頁: 1-12
來源出版物: COMPUT GRAPH-UK
摘要: 
Tile maps are a visualization tool to display geographic data without the accurate representation of geographic boundaries. Each region in a tile map is represented as a tile of identical shape and size. The tiles are fit in a regular grid at positions that approximate their geographic positions such that large regions do not dominate the map visualization, and information in small regions can be enhanced. In this study, the automatic generation of a tile map composed of puzzle tiles is proposed for spatial-temporal data visualization. A puzzle tile is an extension of a standard square tile. A sequence of connected and directional pieces in a puzzle tile is used to represent time-varying quantities in a geographic region. To generate a puzzle tile map, the proposed method includes algorithms for optimizing district-to-tile mapping according to not only geographic positions but also region orientations and for placing puzzle pieces in a tile. The proposed puzzle tile map can serve as a choropleth map in which the ordered pieces in a tile are shaded in proportion to the measurements of a statistical time variable, such as a time sequence of fertility rates, air pollution (PM2.5), or transfer of residential property, being displayed on a 2D map. Experimental demonstrations of various cases show that the proposed methods for district-to-tile mapping optimization and puzzle generation are feasible for automatic puzzle tile map generation. User studies show the capabilities of the puzzle tile map in terms of usability, readability, and comparability of spatial-temporal data visualization. (C) 2019 Elsevier Ltd. All rights reserved.
URI: http://scholars.ntou.edu.tw/handle/123456789/5757
ISSN: 0097-8493
DOI: 10.1016/j.cag.2019.05.002
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