Local adaptation of a national digital soil map for use in precision agriculture

Abstract

The publicly available Digital Soil Map of Sweden (DSMS) contains topsoil clay content information in a 50m× 50m grid, and can be used as decision support in precision agriculture. However, it is also common that farmers have undertaken their own soil sampling (one sample per hectare with texture analysed in every third sample). In the present study, such soil samples from 403 farms were used to validate topsoil clay content information derived from 1) DSMS, 2) DSMS locally adapted by residual kriging, 3) DSMS locally adapted by regression kriging and 4) inverse distance weighting interpolation of the soil sample data without using DSMS. The latter has been common practice until now. The best method differed depending on the local accuracy of DSMS, the quality of the soil sampling and the spatial variation structure of the topsoil texture. The ‘Best method’ strategy, which meant to apply all the above methods and choose the one that performed best at each farm, significantly reduced the mean absolute error. We recommend using this strategy to locally adapt regional digital soil maps to derive accurate decision support for use in precision agriculture.