Geographically weighted regression residual Kriging method applicable for the spatial prediction of sediment grain size compositions
SUN Sijia
LIU Fucheng
ZHOU Yi
LI Rong
Abstract：In view of characteristics of autocorrelation and environmental correlation of the spatial distri-bution of grain size components in offshore surface sediments,a geographically weighted regression re-sidual Kriging(GWRRK)method is proposed with its application feasibility analyzed and evaluated in spatial prediction of grain size compositions and sediment types using the grain size composition data of surface sediment in Haizhou Bay,north Jiangsu Province.The results showed that GWRRK method can obtain a higher spatial prediction accuracy of sediment grain size components and mapping accuracy of sediment types than the ordinary Kriging method.The overall predictive mapping accuracy of sedi-ment types by GWRRK method reached 89.6％.Its corresponding Kappa coefficient is 0.873,indica-ting that the mapping types of sediments are in good agreement with their actual types.As the new method can comprehensively consider the spatial autocorrelation and environmental correlation of varia-bles,it has practical value in quantitative spatial prediction of sediment particle size components and mapping of sediment types.
Keywords：geographically weighted regression residual Krigingspatial prediction mappingsediment grain size compositionsediment type mapping
Publication Date：2023-12-28
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：9( 34-42 )