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- W4313291331 abstract "Vegetation-based landscape classifications reflecting combinations of different types of vegetation promote the understanding of landscape patterns and ecological restoration. However, widespread landscape classifications containing a single thematic resolution may oversimplify landscape patterns. This study aimed at providing a solution for and testing formalized landscape classification, relying on the landscape’s full vegetation potential, i.e. on multiple potential vegetation (MPV). Two areas were studied: the territory of Hungary at a coarse scale and an agriculture-dominated landscape, the Körös-Maros Interfluve (south-eastern Hungary), at a fine scale. Hierarchical clustering and ordination were used to determine landscape types based on potential vegetation type composition of landscapes at each spatial scale. After cutting the resulting dendrogram at several levels and plotting the results on maps and ordination plots, the most relevant thematic resolutions were selected based on the plots and the separation of the groups was tested statistically. The vegetation-based landscape units were reasonably well aligned with biogeographical knowledge at both thematic resolution levels when the study included the whole country. Landscape unit delineation and interpretation based on the typical potential habitats linked to them benefitted from the use of a series of thematic resolutions. For example, in the case of the Körös-Maros Interfluve, apart from well-known grassland vegetation, theMPV-based approach highlighted the distribution of different types of landscape and the potential for woodland in a currently non-wooded area. Furthermore, the finer thematic resolution indicated the possibility of a new type of landscape along temporary small streams. The combined application of clustering and ordination enhanced the interpretation of types of landscape. The use of potential vegetation as an input also enables the classification of currently transformed landscapes. The series of maps with different thematic resolutions allows a flexible choice for specific uses." @default.
- W4313291331 created "2023-01-06" @default.
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- W4313291331 date "2022-01-01" @default.
- W4313291331 modified "2023-09-29" @default.
- W4313291331 title "Multilayer landscape classification based on potential vegetation" @default.
- W4313291331 doi "https://doi.org/10.23855/preslia.2022.631" @default.
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