Visual data mining of raster data: a volume-rendering-based hierarchical approach

Fei Du; A-Xing Zhu; Tao Pei; Cheng-Zhi Qin

doi:10.1117/12.815718

29 December 2008 Visual data mining of raster data: a volume-rendering-based hierarchical approach

Fei Du, A-Xing Zhu, Tao Pei, Cheng-Zhi Qin

Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 72853W (2008) https://doi.org/10.1117/12.815718
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China

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.

Citation Download Citation

Fei Du, A-Xing Zhu, Tao Pei, and Cheng-Zhi Qin "Visual data mining of raster data: a volume-rendering-based hierarchical approach", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853W (29 December 2008); https://doi.org/10.1117/12.815718

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available