A European soil organic carbon monitoring system leveraging Sentinel 2 imagery and the LUCAS soil data base

[Display omitted] •SOC content monitoring system with continuous cover over Europe provided with graphical user interface.•Combination of spectral models for croplands and digital soil mapping approach for forest and grassland.•Pixel-based uncertainty measures provided at 50 m resolution for pilot regions and 100 m resolution for Europe.•Predicted SOC contents evaluated against data from National Reporting Centres in three regions.•Realistic spatial patterns in SOC detected both within and between fields. The Worldsoils project has developed a pre-operational Soil Organic Carbon (SOC) monitoring system in a cloud environment. The system predicts topsoil organic carbon content at regional and continental scales from Earth Observation (EO) satellite data with a continuous cover over Europe. The system utilizes spectral models for croplands and a digital soil mapping approach for permanently vegetated areas such as grasslands and forests. Models strongly rely on soil reflectance composites from the Sentinel 2 multispectral instrument providing the median reflectance for all valid pixels over a period of three years. The bare soil frequency, a proxy for the degree of crop cover, is clearly lower in a Mediterranean pilot region compared to croplands in temperate regions. This is due to the extensive crop cover in the Mediterranean with winter cereals and fodder crops. The graphical user interface provides SOC content and the prediction interval ratio (i.e. 90 % uncertainty interval divided by the median) for 50 m pixels in three pilot regions and 100 m pixels for the rest of Europe. The SOC prediction algorithms are reasonable compared to others at the continental scale (R2: 0.41 for croplands and 0.28 for permanently vegetated areas). Apart from tree crops in Macedonia (Greece) the soil reflectance composite attributes the correct model to validation sets of cropland and grassland in the pilot regions. The SOC prediction is satisfactory in Wallonia (Belgium; R2 0.51) but is less accurate in Greece and the Czech Republic. In particular in Greece, the poor performance is linked to the low bare soil frequency due to the abundance of tree crops, cereals and fodder crops. The monitoring system can reproduce spatial patterns in SOC content similar to the ones obtained from a detailed regional algorithm using the new generation of hyperspectral satellites. However, the very high values in kettle holes in a morainic landscape of Northern Germany are underestimated.