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Visual Analysis of Relevant Fields
in Geoscientific Multifield Data
Anatoliy Antonov and Lars Linsen
Abstract Exploration of multi
eld geoscienti
c data sets is a complex task
involving the investigation of individual
fields and correlations between
fields. We
present an approach to analyze the importance of
fields and their correlations in
multi
fields as multidimensional objects
and projecting these objects to a 2D space, and visually investigating the
eld datasets by treating given or derived
elds
using the projected layout. We demonstrate how our approach supports the analysis
of atmospheric simulation data in two different settings.
Keywords Visualization
Interactive visual data analysis
Multi
eld
Dimen-
sion projection
1 Introduction
Present technical capabilities enable scientists to produce much more data than can
be carefully analyzed. In addition, the visualization techniques that are commonly
employed in the geoscienti
c research do not allow to effectively extract features
from more than a few variables: the independent variables are usually visualized
side-by-side, and changes in values of a single variable over time are usually
depicted with animations. Both approaches do not scale well and impose an
excessive cognitive load on the scientist.
We present an approach to analyze relationships between scalar
fields, with the
goal of
fields, both simulated and derived, that add most
information to each other. When applied to climate data such an approach allows,
among others, for the detection of seasonal changes. For example, temperature
finding and choosing
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