Assessment of yield stability patterns using sentinel-2 over a 7-year period

This study employed Sentinel-2 satellite data spanning 2018–2024 to conduct a subfield-level yield stability assessment within the Danubian lowland, Slovakia. A robust spatiotemporal multi-crop framework was implemented based on Normalized Difference Vegetation Index (NDVI) classification, followed by multiyear stability analysis. This resulted in the identification of stable high, medium, low, and unstable yield productivity zones. Stable high yielding zones accounted for only 6.5% of the cropland, whereas unstable yield zones comprised almost 47%. The resulting map revealed scattered fine-scale variations in yield stability at the parcel level, while also identifying some general spatial trends related to climatic and elevation gradients. The key factors for distinguishing the two contrasting classes (stable high versus low yield zones) were analysed. Gradient boosting classification models (XGBoost) were implemented to distinguish these classes, achieving a good performance with a Receiver Operating Characteristic Area Under the Curve (AUC) of 0.86. Shapley additive explanation analysis (SHAP) was applied to enhance model interpretation. Notably, elevation, topsoil spectral reflectance (from a Sentinel-2-based bare soil mosaic), topography and field size have been identified as key predictive features for the classification model. Satellite-based yield stability maps support data-informed policy interventions toward effective implementations of precision management strategies and regenerative programs for sustainable agriculture.Regional-scale yield stability from satellite data serves as a benchmark for farmers, allowing them to compare their productivity across the production region, identify areas for improvement, and optimize management practices, leading to more efficient resource use.The consistency of satellite remote sensing data ensure that yield stability assessments remain objective and comparable across regions and time periods. This ensures a cost-effective way to monitor the impact of applied interventions and adapt strategies for long-term sustainability. Satellite-based yield stability maps support data-informed policy interventions toward effective implementations of precision management strategies and regenerative programs for sustainable agriculture. Regional-scale yield stability from satellite data serves as a benchmark for farmers, allowing them to compare their productivity across the production region, identify areas for improvement, and optimize management practices, leading to more efficient resource use. The consistency of satellite remote sensing data ensure that yield stability assessments remain objective and comparable across regions and time periods. This ensures a cost-effective way to monitor the impact of applied interventions and adapt strategies for long-term sustainability.