Visualization techniques for spatial probability density function data

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 co...

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Bibliographic Details
Main Authors:	Udeepta D Bordoloi, David L Kao, Han-Wei Shen
Format:	Article
Language:	English
Published:	Ubiquity Press 2006-01-01
Series:	Data Science Journal
Subjects:	Spatial data uncertainty probability density functions visualization clustering
Online Access:	http://datascience.codata.org/articles/293

id	doaj-04c8b9d2026d4b1184d992f280781e9c
record_format	Article
spelling	doaj-04c8b9d2026d4b1184d992f280781e9c2020-11-24T20:58:21ZengUbiquity PressData Science Journal1683-14702006-01-01315316210.2481/dsj.3.153294Visualization techniques for spatial probability density function dataUdeepta D Bordoloi0David L Kao1Han-Wei Shen2Dept. of Computer and Information Sciences, The Ohio State University, Columbus, OH, USANASA Ames Research Center, Moffet Field, CA, USADept. of Computer and Information Sciences, The Ohio State University, Columbus, OH, USANovel 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.http://datascience.codata.org/articles/293Spatial datauncertaintyprobability density functionsvisualizationclustering
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Udeepta D Bordoloi David L Kao Han-Wei Shen
spellingShingle	Udeepta D Bordoloi David L Kao Han-Wei Shen Visualization techniques for spatial probability density function data Data Science Journal Spatial data uncertainty probability density functions visualization clustering
author_facet	Udeepta D Bordoloi David L Kao Han-Wei Shen
author_sort	Udeepta D Bordoloi
title	Visualization techniques for spatial probability density function data
title_short	Visualization techniques for spatial probability density function data
title_full	Visualization techniques for spatial probability density function data
title_fullStr	Visualization techniques for spatial probability density function data
title_full_unstemmed	Visualization techniques for spatial probability density function data
title_sort	visualization techniques for spatial probability density function data
publisher	Ubiquity Press
series	Data Science Journal
issn	1683-1470
publishDate	2006-01-01
description	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.
topic	Spatial data uncertainty probability density functions visualization clustering
url	http://datascience.codata.org/articles/293
work_keys_str_mv	AT udeeptadbordoloi visualizationtechniquesforspatialprobabilitydensityfunctiondata AT davidlkao visualizationtechniquesforspatialprobabilitydensityfunctiondata AT hanweishen visualizationtechniquesforspatialprobabilitydensityfunctiondata
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Visualization techniques for spatial probability density function data

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