Post-processing is the last and often optional stage of land cover (LC) classification from satellite images. In the traditional approach, it is usually applied to remove the effect of “salt and pepper” from the classified image and also to standardize the image details according to the defined minimum mapping unit (MMU). The proposed post-processing method presented in this paper, has been used in the Sentinel-2 Global Land Cover (S2GLC) project. Its main goal is to remove or minimize typical classification errors that can appear in the classification output. Therefore, a set of functions that are able to improve the result of LC classifications has been developed. These include relatively simply defined rules that operate based on predefined threshold values of selected spectral channels, spectral indexes or auxiliary data. Additionally, logical relations between certain LC classes have been implemented. The proposed post-processing has been applied to the classification results of the S2GLC project and helped to improve LC classification in all test sites representing different parts of the globe.
Gromny E., Lewiński S., Rybicki M., Malinowski R., Krupiński M., and Nowakowski A. (2019), Post-processing tools for land cover classification of Sentinel-2, Proc. SPIE 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, 111763M (6 November 2019)