Dr. Gelsleichter Yuri - MATE Research
Overview
Dr. Yuri Gelsleichter is a soil and geomatics researcher focused on AI-driven predictive models. His research combines proximal soil sensing, using Vis-NIR and mid-infrared spectroscopy, with multi- and hyperspectral imagery and machine learning to map, and predict soil attributes. Experienced in HPC environments, he builds reproducible workflows using open-source tools such as R, Python and GDAL. He has contributed to international initiatives, including the EU Horizon 2020 Soils4Africa project (soil information system), and the OSIRIS project on science reproducibility. He collaborates with research groups across the Americas, Europe, Africa and Oceania. His broader expertise encompasses pedometrics, soil genesis and classification, data visualization, and spatial analysis.
Research keywords:
Publications
Digital Soil Mapping and Proximal Soil Sensing
Gelsleichter, Y. A., Costa, E. M., dos Anjos, L. H. C., & Marcondes, R. A. T. (2023). Enhancing Soil Mapping with Hyperspectral Subsurface Images generated from soil lab Vis-SWIR spectra tested in southern Brazil. Geoderma Regional, 33, e00641. https://doi.org/10.1016/j.geodrs.2023.e00641
Costa, E. M., Pinheiro, H. S. K., Anjos, L. H. C. D., Marcondes, R. A. T., & Gelsleichter, Y. A. (2020). Mapping soil properties in a poorly-accessible area. Revista Brasileira de Ciência do Solo, 44, e0190107. http://doi.org/10.36783/18069657rbcs20190107
Gelsleichter, Y.A., Toth, A.J., Micheli, E. et al. Digital Soil Mapping of Soil Organic Carbon at Eastern Slopes of Mount Kenya. Eurasian Soil Sc. 58, 140 (2025). https://doi.org/10.1134/S1064229324602749
Soil Organic Carbon
Rotich, B., Szegi, T., Gelsleichter, Y. A., Fuchs, M., Ocansey, C. M., Phenson, J. N., Abdulkadir, M., Kipkulei, H., Wawire, A., Mutuma, E., Mesele, S. A., Michéli, E., & Csorba, Á. (2025). Variation in Soil Organic Carbon and Total Nitrogen Stocks Across Elevation Gradients and Soil Depths in the Mount Kenya East Forest. Land, 14(6), 1217. https://doi.org/10.3390/land14061217
Phenson, Justine Nsima and Csorba, Ádám and Mesele, Samuel Ayodele and Ocansey, Caleb Melenya and Gelsleichter, Yuri Andrei and Rotich, Brian and Lameck, Azaria Stephano and Mwango, Sibaway B. and Michéli, Erika, The Status of Soil Organic Carbon and Carbon Stocks from Agricultural Fields in the Mbeya Region, Tanzania http://doi.org/10.2139/ssrn.4907128
Proximal Soil Sensing for Soil Classification
Michéli, E., Fuchs, M., Gelsleichter, Y., Zein, M., Csorba, Á. (2023). Spectroscopy Supported Definition and Classification of Sandy Soils in Hungary. In: Hartemink, A.E., Huang, J. (eds) Sandy Soils. Progress in Soil Science. Springer, Cham. https://doi.org/10.1007/978-3-031-50285-9_6
Open Science and Computational Reproducibility
Gelsleichter, Y. A., Banzi, R., Naudet, F., Vinatier, C., Kertész, I., & Varga, M. (2025). Survey about Barriers and Solutions for Enhancing Computational Reproducibility in Scientific Research. F1000Research, 14, 1278. https://doi.org/10.12688/f1000research.172013.1
Climate Modeling
Delgado, R. C., de Santana, R. O., Gelsleichter, Y. A., & Pereira, M. G. (2022). Degradation of South American biomes: What to expect for the future?. Environmental Impact Assessment Review, 96, 106815. https://doi.org/10.1016/j.eiar.2022.106815
Projects
Soils4Africa
EU Horizon 2020 project aimed at building an open-access continental Soil Information System for Africa, with standardised field and laboratory methods for soil monitoring across agricultural land. https://www.soils4africa-h2020.eu/
OSIRIS - Open Science to Increase Reproducibility in Science
EU Horizon Europe project developing evidence-based solutions to improve reproducibility in research, through interventions at researcher, institutional, publisher and funder levels across European institutions.
https://osiris4r.eu/
