Abstract
A method for the visualization of correlation-based data has been applied for analysis of the set of meteorological and environmental parameters that describe the air pollution. A visual presentation of data stored in the correlation matrix makes it possible for ecologists to discover additional knowledge hidden in it. The method consists of two stages: building of a system of vectors based on the correlation matrix and visualization of these vectors. Sammon’s mapping and the self-organizing map were applied for visualization of the vectors.
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© 2004 Springer-Verlag Berlin Heidelberg
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Dzemyda, G. (2004). Visual Analysis of the Multidimensional Meteorological Data. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science - ICCS 2004. ICCS 2004. Lecture Notes in Computer Science, vol 3036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24685-5_112
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DOI: https://doi.org/10.1007/978-3-540-24685-5_112
Publisher Name: Springer, Berlin, Heidelberg
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