A comparison of prediction methods for the creation of field-extent soil property maps

We compare various prediction methods for mapping of soil cation exchange capacity using different combinations of secondary information. The prediction methods used are statistical analysis (generalised additive model, regression tree, multiple linear regression), geostatistical interpolation (ordinary kriging) and the hybrid techniques (regression-kriging and kriging with external drift). The secondary spatial information used are terrain attributes, bare soil colour aerial photograph, bare soil LANDSAT TM imagery, crop yield data and soil apparent electrical conductivity (ECa). A modification of jackknifing was used as the validation method. This involved 100 jackknife partitions to examine the stability of the validation indices with different realisations of the data set. Root-mean-square error (RMSE) was used as the validation index, with the mean RMSE used to judge the prediction quality. The best prediction methods were kriging with external drift, multiple linear regression and generalised additive models. They were best in combination with soil ECa or the bare soil colour aerial photograph.