Summary
In order to detect boundaries in vegetation the moving window algorithm (MWA) was applied to point-quadrat data obtained from a meadow classified as Lolio-Cynosuretum. Squared Euclidean distance was used as a dissimilarity measure. The phytosociologicai classification into a mown and an unmown area by character species was confirmed by the results of MWA. MWA is a suitable multivariate method for the detection of spatial discontinuities in vegetation data.
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Balzter, H., Braun, P., Köhler, W. (1996). Detection of Spatial Discontinuities in Vegetation Data by a Moving Window Algorithm. In: Gaul, W., Pfeifer, D. (eds) From Data to Knowledge. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79999-0_24
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DOI: https://doi.org/10.1007/978-3-642-79999-0_24
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