Szatmári Gábor

- Pedometrics, digital soil mapping

- Geostatistics and environmental statistics

- Machine learning algorithms

- Model-based sampling optimization

- Quantification, evaluation and communication of uncertainty in spatial modelling

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Five Selected publications

Szatmári G., Pásztor L., Laborczi A., Illés G., Bakacsi Zs., Zacháry D., Filep T., Szalai Z., Jakab G. (2023): Countrywide mapping and assessment of organic carbon saturation in the topsoil using machine learning-based pedotransfer function with uncertainty propagation. CATENA 227: 107086 [link]

Szatmári G., Pásztor L., Heuvelink G.B.M. (2021): Estimating soil organic carbon stock change at multiple scales using machine learning and multivariate geostatistics. GEODERMA 403: 115356 [link]

Szatmári G., Bakacsi Zs., Laborczi A., Petrik O., Pataki R., Tóth T., Pásztor L. (2020): Elaborating Hungarian Segment of the Global Map of Salt-Affected Soils (GSSmap): National Contribution to an International Initiative. REMOTE SENSING 12: 4073 [link]

Szatmári G., Pirkó B., Koós S., Laborczi A., Bakacsi Zs., Szabó J., Pásztor L. (2019): Spatio-temporal assessment of topsoil organic carbon stock change in Hungary. SOIL & TILLAGE RESEARCH 195: 104410 [link]

Szatmári G., Pásztor L. (2019): Comparison of various uncertainty modelling approaches based on geostatistics and machine learning algorithms. GEODERMA 337: 1329-1340 [link]