Visual Analysis of Hurricane Data Using Joint Contour Net
| dc.contributor.author | Geng, Zhao | en_US |
| dc.contributor.author | Duke, David | en_US |
| dc.contributor.author | Carr, Hamish | en_US |
| dc.contributor.author | Chattopadhyay, Amit | en_US |
| dc.contributor.editor | Rita Borgo and Wen Tang | en_US |
| dc.date.accessioned | 2014-12-15T15:53:07Z | |
| dc.date.available | 2014-12-15T15:53:07Z | |
| dc.date.issued | 2014 | en_US |
| dc.description.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. | en_US |
| dc.description.seriesinformation | Computer Graphics and Visual Computing (CGVC) | en_US |
| dc.identifier.isbn | 978-3-905674-70-5 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/cgvc.20141205 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Joint Contour Net [Application] | en_US |
| dc.subject | Hurricane Data | en_US |
| dc.title | Visual Analysis of Hurricane Data Using Joint Contour Net | en_US |
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