Validation of Visually Interpreted Corine Land Cover Classes with Spectral Values of Satellite Images and Machine Learning

Validation of Visually Interpreted Corine Land Cover Classes with Spectral Values of Satellite Images and Machine Learning

We analyzed the Corine Land Cover 2018 (CLC2018) dataset to reveal the correspondence between land cover categories of the CLC and the spectral information of Landsat-8, Sentinel-2 and PlanetScope images. Level 1 categories of the CLC2018 were analyzed in a 25 km × 25 km study area in Hungary. Spect...

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Bibliographic Details
Main Authors: Orsolya Gyöngyi Varga, Zoltán Kovács, László Bekő, Péter Burai, Zsuzsanna Csatáriné Szabó, Imre Holb, Sarawut Ninsawat, Szilárd Szabó
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Remote Sensing
Subjects:
Landsat
Sentinel
planet
CLC2018
Recursive Feature Elimination
validation
Online Access:https://www.mdpi.com/2072-4292/13/5/857

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