Share Email Print
cover

Proceedings Paper

Visualization and exploration of spatial probability density functions: a clustering-based approach
Author(s): Udeepta D. Bordoloi; David L. Kao; Han-Wei Shen
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We present an interactive visualization technique for spatial probability density function data. These are datasets that represent a spatial collection of random variables, and contain a number of possible outcomes for each random variable. It is impractical to visualize all the information at each spatial location as it will quickly lead to a cluttered image. We advocate the use of hierarchical clustering as a means of summarizing the information, and also as a tool to bring out meaningful spatial structures in the datasets. For clustering, we discuss a distance function which preserves the spatial correlation present in these datasets. To create an informative visualization of the clusters, we introduce a scheme of colors and patterns to represent statistical properties of the clusters.

Paper Details

Date Published: 4 June 2004
PDF: 8 pages
Proc. SPIE 5295, Visualization and Data Analysis 2004, (4 June 2004); doi: 10.1117/12.539250
Show Author Affiliations
Udeepta D. Bordoloi, The Ohio State Univ. (United States)
David L. Kao, NASA Ames Research Ctr. (United States)
Han-Wei Shen, The Ohio State Univ. (United States)


Published in SPIE Proceedings Vol. 5295:
Visualization and Data Analysis 2004
Robert F. Erbacher; Philip C. Chen; Jonathan C. Roberts; Matti T. Gröhn; Katy Börner, Editor(s)

© SPIE. Terms of Use
Back to Top