Visual Analysis of Hurricane Data Using Joint Contour Net

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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Topology provides a rigorous foundation for identifying features and transitions within data. However, computing and presenting topological features in multi-dimensional range space is still a difficult problem. The Joint Contour Net therefore is proposed as a data structure which quantizes the variation of multiple variables and presents multiple-field topology. In this paper, we apply the Joint Contour Net to real-world applications in order to present, analyse and explore features related to phenomenon. We have proposed a framework based on Joint Contour Net for iterative data exploration and knowledge discovery. The data set we investigate is from a simulation of Isabel Hurricane. We are able to demonstrate that the multi-field topological features such as rainbands, air flow and hurricane eye, as well as their relationship, can be exploited from a global topological view.
Description

        
@inproceedings{
:10.2312/cgvc.20141205
, booktitle = {
Computer Graphics and Visual Computing (CGVC)
}, editor = {
Rita Borgo and Wen Tang
}, title = {{
Visual Analysis of Hurricane Data Using Joint Contour Net
}}, author = {
Geng, Zhao
and
Duke, David
and
Carr, Hamish
and
Chattopadhyay, Amit
}, year = {
2014
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-905674-70-5
}, DOI = {
/10.2312/cgvc.20141205
} }
Citation