Research Papers
Visualization techniques for spatial probability density function data
Authors:
Udeepta D Bordoloi ,
Dept. of Computer and Information Sciences, The Ohio State University, Columbus, OH, USA, US
David L Kao,
NASA Ames Research Center, Moffet Field, CA, USA, US
Han-Wei Shen
Dept. of Computer and Information Sciences, The Ohio State University, Columbus, OH, USA, US
Abstract
Novel visualization methods are presented for spatial probability density function data. These are spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We use clustering as a means to reduce the information contained in these datasets; and present two different ways of interpreting and clustering the data. The clustering methods are used on two datasets, and the results are discussed with the help of visualization techniques designed for the spatial probability data.
How to Cite:
Bordoloi, U.D., Kao, D.L. & Shen, H.-W., (2006). Visualization techniques for spatial probability density function data. Data Science Journal. 3, pp.153–162. DOI: http://doi.org/10.2481/dsj.3.153
Published on 05 Jan 2006.
Peer Reviewed
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