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}
}