Approaches to soil classification have evolved in recent years, driven by a growing need for quantitative, accurate data and detailed soil maps, as well as changes in general understanding of soils and their functions. This study presents methods for innovating the existing Czech soil classification system through various analyses of an extensive database of legacy data from different soil surveys, with the aim of clarifying and refining soil diagnostics and increasing the usability of soil classification in diverse applications. The approaches included establishing precise quantitative limits for diagnostic criteria based on statistical analysis of the dataset, compiling and testing the key to soil types, and evaluating the consistency and taxonomic relationships of the resulting soil units using taxonomic distance analyses. The results demonstrated the importance of legacy data as a basis for quantifying diagnostic criteria, as they allow the setting of thresholds that correspond to actual land cover. Exact limits and the organisation of soil groups into a classification key led to redistribution of studied profiles between units, often in favour of less developed soil types (kambizem, regozem). However, the newly proposed and actual soil units are taxonomically very close; thus, despite the change in the approach to classification, continuity between the two systems has been maintained.
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Zádorová et al. (2026) studied this question.
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