Harmonisation of a large-scale historical database with the actual Czech soil classification system

The possibility of the adequate use of data and maps from historical soil surveys depends, to a large measure, on their harmonisation. Legacy data originating from a large-scale national mapping campaign, "Systematic soil survey of agricultural soils in Czechoslovakia (SSS, 1961-1971)", were harmonised and converted according to the actual system of soil classification and descriptions used in Czechia - the Czech taxonomic soil classification system (CTSCS). Applying the methods of taxonomic distance and quantitative analysis and reclassification of the selected soil properties, the conversion of two types of mapping soil units with different detailed soil information (General soil representative (GSR), and Basic soil representative (BSR)) to their counterparts in the CTSCS has been effectuated. The results proved the good potential of the used methods for the soil data harmonisation. The closeness of the concepts of the two classifications was shown when a number of soil classes had only one counterpart with a very low taxonomic distance. On the contrary, soils with variable soil properties were approximating several related units. The additional information on the soil skeleton content, texture, depth and parent material, available for the BSR units, showed the potential in the specification of some units, though the harmonisation of the soil texture turned out to problematic due to the different categorisation of soil particles. The validation of the results in the study region showed a good overall accuracy (75% for GSR, 76.1% for BSR) for both spatial soil units, when better performance has been observed in BSR. The conversion accuracy differed significantly in the individual soil units, and ranged from almost 100% in Fluvizems to 0% in Anthropozems. The extreme cases of a complete mis-classification can be attributed to inconsistencies originating in the historical database and maps. The study showed the potential of modern quantitative methods in the legacy data harmonisation and also the necessity of a critical approach to historical databases and maps.