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Integration of Categorical Data using Multivariate Kriging for Spatial Interpolation of Ground Survey Data  

Park, No-Wook (인하대학교 지리정보공학과)
Publication Information
Spatial Information Research / v.19, no.4, 2011 , pp. 81-89 More about this Journal
Abstract
This paper presents a multivariate kriging algorithm that integrates categorical data as secondary data for spatial interpolation of sparsely sampled ground survey data. Instead of using constant mean values in each attribute of categorical data, disaggregated local mean values at target grid points are first estimated by area-to-point kriging and then are used as local mean values in simple kriging with local means. This algorithm is illustrated through a case study of spatial interpolation of a geochemical copper element with geological map data. Cross validation results indicates that the presented algorithm leads to significant respective improvement of 15% and 25% in prediction capability, compared with univariate ordinary kriging and conventional simple kriging with constant mean values. It is expected that the multivariate kriging algorithm applied in this study would be effectively applied for spatial interpolation with categorical data.
Keywords
Kriging; Disaggregation; Spatial Interpolation; Categorical Data; Geological Map;
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Times Cited By KSCI : 4  (Citation Analysis)
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