Alternative Visualization of Large Geospatial Datasets
The Cartographic JournalPublished 1 December 2004
Etien Luc Koua, M.J. Kraak
Citations25
SJR quartileQ3
SJR score0.26
SNIP1.14
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TL;DR
This approach is based on the effective application of computational algorithms, such as the Self-Organizing Map (SOM), used to uncover the structure, patterns, relationships and trends in the data, and for the creation of abstractions where conventional methods may be limited.
Abstract
AbstractAbstractExploring large volumes of geospatial data is difficult. This paper presents an approach that combines visual and computational analysis to make this process easier. This approach is based on the effective application of computational algorithms, such as the Self-Organizing Map (SOM). These are used to uncover the structure, patterns, relationships and trends in the data, and for the creation of abstractions where conventional methods may be limited. In addition, graphical representations are applied to portray extracted patterns in a visual form that allows for better understanding of the derived structures and possible geographical processes, and should facilitate knowledge construction.
Keywords
Computer ScienceSocial Sciences
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