Assessment of the topsoil organic carbon saturation in Hungary using machine learning-based pedotransfer function with uncertainty propagation

Gábor Szatmári; Gergely Jakab; Annamária Laborczi; Zoltán Szalai; László Pásztor

doi:https://doi.org/10.5194/egusphere-egu23-6954

[Back] [Session SSS10.6]

EGU23-6954

https://doi.org/10.5194/egusphere-egu23-6954

EGU General Assembly 2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Assessment of the topsoil organic carbon saturation in Hungary using machine learning-based pedotransfer function with uncertainty propagation

Gábor Szatmári

¹, Gergely Jakab

², Annamária Laborczi¹, Zoltán Szalai

², and László Pásztor

¹

Gábor Szatmári et al.

¹Institute for Soil Sciences, Centre for Agricultural Research, Budapest, Hungary (szatmari@rissac.hu)
²Geographical Institute, Research Centre for Astronomy and Earth Sciences, Budapest, Hungary

How to cite: Szatmári, G., Jakab, G., Laborczi, A., Szalai, Z., and Pásztor, L.: Assessment of the topsoil organic carbon saturation in Hungary using machine learning-based pedotransfer function with uncertainty propagation, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6954, https://doi.org/10.5194/egusphere-egu23-6954, 2023.

This abstract has been withdrawn on 17 Apr 2023.