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Classification methods for spatial data representation

By Toshihiro Osaragi


It is necessary to classify numerical values of spatial data when representing them on a map and visually understanding it. In consequence, loss of information from original data is inevitable 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 of spatial data is proposed, in which the loss of information is minimized. Comparing our method with other existing classification methods, some new findings are shown

Topics: spatial data, visualization, classification, information loss, AIC (Akaike’s Information Criterion)
Publisher: Centre for Advanced Spatial Analysis (UCL)
Year: 2002
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Provided by: UCL Discovery

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