In this study, the performances of hyperspectral airborne and superspectral spaceborne spectral imaging to derive selected Soil Organic Carbon (SOC) were analyzed and compared in agricultural sites of the Czech Republic. The main aim was to assess the potential of superspectral Sentinel-2 satellite for the prediction and mapping of the attribute. The prediction accuracy based on airborne and spaceborne techniques in majority of the sites was adequate for SOC. Comparing the spatial distribution maps of SOC derived from the airborne and spaceborne data showed a similar trend at both platforms. The SOC maps also confirmed that in areas with a high level of SOC, Sentinel-2 was able to detect SOC even more precisely than the airborne sensors. Although a decrease in the model and map performances was obvious in the case of parameters with low contents. The findings of the current research showed that superspectral Sentinel-2 allows for the estimation and mapping of SOC. The study also emphasized the importance of the superspectral Sentinel-2 data in soil characteristics assessment with a frequent revisit-time over larger areas than it currently is with laboratory and airborne instruments. Certainly, the repeatability of the Sentinel-2 products is still a work in progress and with the Sentinel-2B, a revisit-time of five-day and the temporal frequency of cloud-free acquisitions will be further increased. Accordingly, much more data will be freely available in the near future, which will have a significant influence on the obtaining of high-quality soil data.