Title: Geo-spatial data viewer: from familiar land-covering to arbitrary distorted geo-spatial quadtree maps
Authors: Sips, Mike
Keim, Daniel A.
Panse, Christian
Schneidewind, Jörn
Citation: Journal of WSCG. 2004, vol. 12, no. 1-3, p. 213-220.
Issue Date: 2004
Publisher: UNION Agency
Document type: článek
URI: http://wscg.zcu.cz/wscg2004/Papers_2004_Full/H11.pdf
ISSN: 1213-6972
Keywords: geografické informační systémy;prostorová data;data mining;vizualizace dat
Keywords in different language: geographical information systems;spatial data;data mining;data visualization
Abstract: In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. A noteworthy trend is the increasing size of data sets in common use, such as records of business transactions, environmental data and census demographics. These data sets often contain millions of records, or even far more. This situation creates new challenges in coping with scale. In this paper we propose a novel pixel-oriented visual data mining approach for large spatial datasets. It combines a quadtree based distortion of map regions and a local reposition of pixels within these map regions to avoid overlap in the display. Experiments shows that it produces visualizations of large data sets for the discovery of local correlations, and is practical for exploring geography-related statistical information in a variety of applications including population demographics, epidemiology, and marketing.
Rights: © UNION Agency
Appears in Collections:Volume 12, number 1-3 (2004)

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/1718

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