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- W2007299332 abstract "The objective of the paper is to demonstrate the value of the multivariate method, Principal Components Analysis (PCA) on data relating to landscape elements, to determine the relative directions of change and illustrate landscape dynamics. Data were retrieved from retrospective studies based on interpretation of aerial photographs and old cadastral maps at three time periods, 1741–1811, 1946 and 1993 covering 56 selected hamlets in a parish in Småland, south Sweden. To carry out the analysis, data were summarised into five principal land cover groups; (1) arable and grassland composite; (2) open semi-natural grasslands; (3) wooded grasslands; (4) water; and (5) forest/remaining land. During the 200-year period investigated, the landscape shifted in most hamlets from a more open rural landscape with fields and areas of semi-natural grassland vegetation, to a non-rural landscape with closed forests and fragmented rural areas dominated by cultivated grasslands. The range and distribution of hamlets along the principal axes over time indicate a reduction of complexity, and suggest a negative relationship between the degree of open agricultural landscape and the relative proportion of semi-natural and wooded grasslands. PCA was shown to be a useful tool to simplify the complex landscape data sets and indicate the character of change in terms of dynamics of spatial organisation, and the direction of change in the rural landscape of Virestad. In the analysis, three hamlet types with diverging development were distinguished; (A) major change from a semi-open rural landscape to a closed non-rural forest landscape; (B) intermediate change, where hamlets were already closely related to the closed forest type landscape from the beginning; (C) intermediate change, where hamlets have remained closer to a relatively open rural landscape over the 200 years of the study period." @default.
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- W2007299332 date "1997-10-01" @default.
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- W2007299332 title "Directions of landscape change (1741–1993) in Virestad, Sweden — characterised by multivariate analysis" @default.
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- W2007299332 doi "https://doi.org/10.1016/s0169-2046(97)00019-4" @default.
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