Uncertainties in Digital Soil Mapping and Possibilities of Overcoming Them

Digital soil mapping (DSM) incorporates the most advanced approaches and methods in the computer analysis and modeling of spatial soil data. Over 90% of all published works in the field of soil mapping are currently related to DSM. The analysis of scientometric databases and published works shows that the number of works annually grows, but the declared quality of the resulting soil maps remains virtually unchanged. This is related to a number of factors, and the purpose of this article is to identify them by a review of scientific published works. The conducted research has shown that maps created by DSM approaches vary in quality. The accuracy of the models used to compile digital soil maps, as declared by the authors, typically ranges from 30–40 to 70–80%. Sixteen potential sources of error in digital soil maps were identified, grouped into errors in the initial data on soil properties, initial data on predictors, errors in model selection, and errors in soils as a modeling object. Some sources of error may be eliminated now or in the near future, but there are errors, whose elimination seems impossible at the current stage of scientific and technological development. The potential for significant improvement in the quality is the greatest for digital soil maps of the properties of surface soil horizon and is the smallest for maps of soil classification names. The presence of errors in soil maps compiled by digital soil mapping methods should be disclosed during the creation of any soil map, including masking out of map areas with the greatest errors.