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Proceedings Paper

Visual data mining of raster data: a volume-rendering-based hierarchical approach
Author(s): Fei Du; A-Xing Zhu; Tao Pei; Cheng-Zhi Qin
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Paper Abstract

Developments of raster data capture technologies and demands from application fields call for advanced raster data analysis methods. Visual data mining that involves human's visual analytical capability in data analysis attracts attention in recent years. Raster datasets usually have large amount of pixels, which may cause serious clotting problem in visualization and thus challenges visual data mining. The research reported here mainly focuses on this problem and tries to construct a hierarchical framework for visual data mining of raster data. In the hierarchical structure, the first level uses volume rendering to visualize the whole raster dataset in attribute space, which can greatly reduce the impact of clotting. To avoid the loss of subtle patterns, the second level makes use of parallel coordinates plot to reflect detailed attribute information. This hierarchical structure ensures that both global and local patterns embedded in data can be detected. In both levels, visualizations of attribute space are linked with that of geographic space. Software prototype was developed and then applied to find small clusters that may relate to possible soil types. Case study result demonstrated the effectiveness of this proposed approach.

Paper Details

Date Published: 29 December 2008
PDF: 11 pages
Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853W (29 December 2008); doi: 10.1117/12.815718
Show Author Affiliations
Fei Du, Institute of Geographic Sciences and Natural Resources Research (China)
Graduate Univ. of Chinese Academy of Sciences (China)
A-Xing Zhu, Institute of Geographic Sciences and Natural Resources Research (China)
Univ of Wisconsin, Madison (United States)
Tao Pei, Institute of Geographical Sciences and Natural Resources Research (China)
Cheng-Zhi Qin, Institute of Geographical Sciences and Natural Resources Research (China)


Published in SPIE Proceedings Vol. 7285:
International Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Deren Li; Jianya Gong; Huayi Wu, Editor(s)

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