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Climate change poses one of the greatest challenges of our time, with greenhouse gas (GHG) emissions significantly contributing to global warming. The agriculture, forestry, and land-use (AFOLU) sectors not only emit GHGs but also offer the potential for carbon sequestration, which can mitigate climate change. This study presents a methodological framework for estimating soil organic carbon (SOC) changes based on carbon farming practices in northern Lithuania. Using satellite-derived indicators of cover crops, no-till farming, and residue retention combined with soil and climate data, SOC dynamics were modeled across the Joniškis municipality for the period 2019–2020 using the Rothamsted Carbon Model (RothC) model. The integration of geospatial data and process-based modeling allowed for spatial estimation of SOC change, revealing positive trends ranging from 0.23 to 0.32 t C ha−1 year−1. Higher increases were observed in areas where multiple carbon farming practices overlapped. The proposed workflow demonstrates the potential of combining Earth observation and modeling approaches for regional-scale carbon assessment and provides a basis for future applications in sustainable land management and climate policy support.
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Gudelė et al. (2025) studied this question.
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