Igor Yu. Savin

The current state of the problem of soil mapping is considered. It is shown that there has been a replacement of traditional soil mapping methods by methods based on geoinformation digital and remote sensing technologies. The main advantages and disadvantages of the currently used soil mapping methods are outlined, and the necessity of taking into account the level of generalization of the information used in the process of soil mapping is demonstrated. We demonstrated the errors arising in soil maps when digital spatial data with different levels of information generalization is used. The most promising directions in the development of soil mapping methods are identified. It is shown that the primary attention should be paid to the development of digital soil mapping methods based on remote sensing data, which contain the most accurate information on the spatial variation of the surface soil horizon properties. The use of methods of spatial interpolation of point data is less accurate than the use of remotely sensed data. But the latter allows us to confidently detect only certain soil properties and not all of those necessary to create soil maps in the traditional form. Mapping individual soil properties is a more promising approach. Maps of individual soil properties are more convenient and accurate for evaluating soil and land resources. In the future, they can be used as a basis both for the re-creation of soil units in terms of accepted soil classification and for the creation of soil maps in traditional form (with the reflection of classification units of soils on them). But for a complete transition to the mapping of soil properties, it is necessary to deepen research in studying the spectral reflectance of the soil surface and its relationship with the properties of the underlying soil horizons.

Digital soil mapping (DSM) incorporates the most advanced approaches and methods in the computer analysis and modeling of spatial soil data. Currently, over 90% of all publications in the field of soil mapping are related to DSM. An analysis of scientometric databases and publications shows that the number of publications is growing annually, yet the declared quality of the resulting soil maps remains virtually unchanged. This is due to a number of factors, and the purpose of this article is to identify them through a review of scientific publications. The conducted research has shown that maps created using DSM approaches vary in quality. The accuracy of the models used to create 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 can 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 greatest potential for significant improvement in the quality of digital soil maps of surface soil horizon properties is present, while the least promising is for maps of soil classification names. The presence of errors in soil maps created using digital soil mapping methods should be disclosed during the creation of any soil map, including masking out areas of the map with the greatest errors.