DocumentCode
2208715
Title
An adaptation of the GAIA visualization method for cartography
Author
Lidouh, Karim ; De Smet, Yves ; Zimányi, Esteban
Author_Institution
Comput. & Decision Eng. (CoDE) Dept., Univ. Libre de Bruxelles (ULB), Brussels, Belgium
fYear
2011
fDate
11-15 April 2011
Firstpage
29
Lastpage
35
Abstract
Dimensionality reduction has always been important within disciplines that focus on visual representation of multivariate information. In the case of cartography this has been achieved several times by the use of statistics charts and diagrams, but these are limited in the number of components that can be combined in a single glyph. On the other hand, Multicriteria Decision Aid (MCDA) has developed tools to visually represent multidimensional information, yet these cannot be directly applied on geographical maps. In this paper we present a way to adapt the GAIA visualization tool to the representation and comparison of multicriteria profiles on maps. The process involves the use of a Principal Component Analysis (PCA) and the conversion of its result by applying a HSV color chart. We illustrate this process by applying it to two case studies: an evaluation of the Human Development Index (HDI) and of the Environmental Performance Index (EPI) of the European countries.
Keywords
cartography; charts; data visualisation; principal component analysis; GAIA visualization method; HSV color chart; MCDA; PCA; cartography; dimensionality reduction; environmental performance index; human development index; multicriteria decision aid; multivariate information; principal component analysis; Air pollution; Color; Humans; Image color analysis; Indexes; Principal component analysis; Visualization; Cartography; Color models; Dimensionality reduction; GAIA; MCDA; PROMETHEE; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence in Multicriteria Decision-Making (MDCM), 2011 IEEE Symposium on
Conference_Location
Paris
Print_ISBN
978-1-61284-068-0
Type
conf
DOI
10.1109/SMDCM.2011.5949270
Filename
5949270
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