EGU24-18218, updated on 11 Mar 2024
https://doi.org/10.5194/egusphere-egu24-18218
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Comparison of predicted soil physical property maps based on (i) LUCAS topsoil database and (ii) Hungarian Soil Information and Monitoring System

András Benő1,2, Gábor Szatmári1, Annamária Laborczi1, Mihály Kocsis1, Zsófia Bakacsi1, and László Pásztor1
András Benő et al.
  • 1Institute for Soil Sciences, Centre for Agricultural Research, Department of Soil Mapping and Environmental Informatics, Budapest, Hungary (beno.andras@atk.hu)
  • 2University of Debrecen, Doctoral School of Earth Sciences

The adaption of our land use and agricultural practices requires more detailed and more reliable spatial soil physical data. The LUCAS topsoil database is an up to date collection of soil physical data, however it is spatially scarce. The soil physical data of the Hungarian Soil Information and Monitoring System (SIMS) is spatially denser and has data from multiple layers from 1992. Harmonizing and combining the two datasets can lead to the creation of better resolution and more accurate maps. Before combining the databases, we must make sure, that the sample points represent the area in the same way. The comparison of the data began with the cleansing of the datasets, followed by the conversion of the many sampling depths of the SIMS data to 0-20 cm using mass preserving splines and the conversion of the particle size limit from FAO/WRB to USDA standard. To make sure, that the sum of the sand, silt and clay fractions was 100% additive log ratio (ALR) transformation was applied on both LUCAS and SIMS. Mapping was carried out using random forest kriging with 10-fold cross-validation on a 100 m * 100 m grid using 28 environmental covariates. The ALR maps were converted back, resulting in the sand, silt and clay maps. Using the three maps, soil texture classes were calculated for both datasets using the USDA soil texture triangle. The soil texture classes were compared to each other pixel-by-pixel using the taxonomical distances of the texture classes. The particle fraction maps were compared to each other also pixel-by-pixel using linear regression. The results let us conclude that the LUCAS and SIMS databases produce very similar maps of both sand, silt a clay. The soil texture class comparison also resulted in a very close match with the majority of the country producing very close or perfect matches.  The two soil monitoring systems produce very similar results when mapping sand, silt, clay and soil texture for the whole country and can safely be combined together for future use and mapping.

How to cite: Benő, A., Szatmári, G., Laborczi, A., Kocsis, M., Bakacsi, Z., and Pásztor, L.: Comparison of predicted soil physical property maps based on (i) LUCAS topsoil database and (ii) Hungarian Soil Information and Monitoring System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18218, https://doi.org/10.5194/egusphere-egu24-18218, 2024.