Classification Method by Information Loss Minimization for Visualizing Spatial Data

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10409)

Abstract

It is necessary to classify numerical values of spatial data when representing them on a map and so that, visually, it can be clearly understood as possible. Inevitably some loss of information from the original data occurs in the process of this classification. A gate loss of information might lead to a misunderstanding of the nature of original data. In this study, a classification method for organizing spatial data is proposed, in which any loss of information is minimized. When this method is compared with other existing classification methods, some new findings are shown.

Keywords

Information loss Classification Visualization Spatial data 
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Notes

Acknowledgements

A portion of this paper was published in [15]. The author would like to give his special thanks to Mr. Hiroki Nakayama for computer-based numerical calculations. The authors would like to acknowledge the valuable comments and useful suggestions from reviewers of Scientific Program Committee of ICCSA 2017.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Environment and SocietyTokyo Institute of TechnologyTokyoJapan

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