Prediction accuracy of selected spatial interpolation methods for soil texture at farm field scale

Abstract

Abstract Soil texture was examined in four crop fields with areas of 10 to 45 ha located in northern and central Poland. In each field, from 21 to 60 soil samples were collected using stratified sampling. The content (%) of soil particles, i.e., sand, silt and clay, was then evaluated using laboratory methods. The apparent electrical conductivity (ECa) was measured and used as ancillary data for the interpolation of soil texture. The obtained data were used to compare selected spatial interpolation methods according to the accuracy of prediction. The examined methods were evaluated based on the results of cross-validation tests. Two methods of validation were used: leave-one-out cross-validation and validation based on a test set of points, with approximately 30% randomly selected. The smallest root mean square error (RMSE) for the prediction of sand, silt and clay was observed for ordinary cokriging in which ECa was used as a covariate. The other three methods, i.e., inverse distance weighting, radial basis functioning and ordinary kriging, had very similar RMSE values, which were approximately 10% higher compared to ordinary cokriging