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Fuzzy Classification for Mapping Forest Vegetation
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Many spatial phenomena can not be represented properly with conventional deterministic classification techniques. Instead, the elaboration of a fuzzy set approach with regards to mapping can be of particular advantage for representing complex spatial systems. The method can generally be used for mapping any multidimensional spatial data.

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Source data on percent vegetative cover of 78 forest species were collected at 57 sampling sites in a nature reserve in Western Flevoland, The Netherlands. Non-hierarchical fuzzy cluster analysis was used for classi-fication, so that each site was finally characterised by a set of membership values, each corresponding to a particular class. Between the sampling locations member-ship values were interpolated by conventional kriging
and adjusted to ensure that the sum of values for each location always equaled to one. The resulting fuzzy map consists of cells each containing 100 randomly distributed coloured pixels. The total number of pixels of a certain colour in a cell corresponds to the member-ship value of this cell with respect to a class represented by this colour. The method is implemented as a stand-alone software operating under MS-DOS and was developed during the authorís stay at Winland Staring Center, Wageningen, The Netherlands.

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A map of forest vegetation classification based on a fuzzy mapping algorithm: nature reserve in Western Flevoland (The Netherlands).

Fuzzy classification map
of forest vegetation

approximate scale 1:10,000.
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Contact : Victor B. Wagner, V.V. Dokuchaev Soil Institute, Russian Academy of Agriculture
Pyzhevsky lane 7 , Moscow, 109017 Russia
Phone: + 7 095 230 80 61 Fax: + 7 095 230 80 42
E-mail: vitus@agropc.msk.su