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Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

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Comparison of linear and nonlinear kriging methods for characterization and interpolation of soil data

Asa, Eric and Saafi, Mohamed and Membah, Joseph and Billa, Arun (2012) Comparison of linear and nonlinear kriging methods for characterization and interpolation of soil data. Journal of Computing in Civil Engineering, 26 (1). ISSN 0887-3801

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Abstract

Characterization and analysis of large quantities of existing soil data represent highly complicated tasks due to the spatial correlation, uncertainty and complexity of the processes underlying soil formation. In this work, three linear kriging (simple kriging, ordinary kriging and universal kriging) and three nonlinear kriging (indicator kriging, probability kriging and disjunctive kriging) algorithms are compared to discover which is best suited for the characterization and interpolation of soil data for applications in transportation projects. A spherical model is employed as the experimental variogram to aid the spatial interpolation and cross-validation. The kriged data is subjected to leave-one-out cross-validation. The data used are in both vector and raster format. Statistical measures of correctness (mean prediction error, root-mean-square error, standardized root-mean-square error, average standard error) from the cross-validation are used to compare the kriging algorithms. Using indicator and probability kriging with the vector data set yielded the best results.