Visual Analysis of Hurricane Data Using Joint Contour Net

Files

033-040.pdf (3.01 MB)

Date

2014

Authors

Geng, Zhao
Duke, David
Carr, Hamish
Chattopadhyay, Amit

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.

        @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
}
}