Paper
6 November 2019 Post-processing tools for land cover classification of Sentinel-2
Ewa Gromny, Stanisław Lewiński, Marcin Rybicki, Radosław Malinowski, Michał Krupiński, Artur Nowakowski
Author Affiliations +
Proceedings Volume 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019; 111763M (2019) https://doi.org/10.1117/12.2537325
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, 2019, Wilga, Poland
Abstract
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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ewa Gromny, Stanisław Lewiński, Marcin Rybicki, Radosław Malinowski, Michał Krupiński, and Artur Nowakowski "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); https://doi.org/10.1117/12.2537325
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Cited by 1 scholarly publication.
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KEYWORDS
Vegetation

Image classification

Clouds

Buildings

Databases

Earth observing sensors

Image processing

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