Pixel and object-based land cover mapping and change detection from 1986 to 2020 for Hungary using histogram-based gradient boosting classification tree classifier

The large-scale pixel-based land use/land cover classification is a challenging task, which depends on many circumstances. This study aims to create LULC maps with the nomenclature of Coordination Information Environment (CORINE) Land Cover (CLC) for years when CLC databases are not available. Furthermore, testing predicted use changes in last 30 Hungary. Histogram-based gradient boosting tree (HGBCT) classifier was tested at classification. According results, classifier, texture variance and landscape metrics capable generate accurate maps, comparison provides detailed image changes.