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Mapping Soil Organic Carbon Changes in Hungary: A Novel Approach Using Machine Learning and Space-Time Geostatistics

A new study by the Department of Soil Mapping and Environmental Informatics presents a novel approach for mapping soil organic carbon (SOC) stock changes in Hungary, addressing critical needs in environmental sciences, agriculture, and even policy making. A space-time model has been developed that can predict SOC changes at different spatial scales, from 100×100 m grid to national level, over the period between 1992 and 2016. This approach provides detailed insights into SOC dynamics while also quantifying the associated uncertainty, which is crucial for making informed decisions in areas such as GHG inventories, sustainable soil and land management, and soil health.

The presented methodology stands out by using a hybrid approach that integrates machine learning with space-time geostatistics, addressing key limitations of previous approaches. It allows for reliable SOC predictions along with uncertainty estimates at any spatial and temporal scale, even in years where no direct SOC measurements are available. This comprehensive method offers a more robust and dynamic understanding of SOC changes not just in space but also in time. The compiled map series provide valuable information for researchers, society and even policymakers, helping to tackle environmental challenges such as land and soil degradation, climate change, and ecosystem assessment. These findings support ongoing initiatives like the EU Soil Monitoring Directive and the UN Sustainable Development Goals, offering practical tools for tracking SOC changes and assessing soil health over time.

This research fills a key gap in our understanding of SOC dynamics in Hungary and offers a methodology that can be adapted internationally to improve the accuracy and utility of SOC data to address the environmental challenges and crises of our time.

Szatmári, G., Pásztor, L., Takács, K., Mészáros, J., Benő, A., Laborczi, A. (2024): Space-time modelling of soil organic carbon stock change at multiple scales: Case study from Hungary. Geoderma 451, 117067. https://doi.org/10.1016/j.geoderma.2024.117067

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