Nicola Arndt und Matthias Pohl - Neobiota

To overlay these maps, it was first necessary to transform the raster map of ITE into a polygon vector
map, where the land class values are assigned to polygons, as shown in Figure 3.
Figure 3: ITE map after its transformation from raster to vector format (left) and transformed into Albers
projection (right).
A combination map was produced by clipping the BfN map with the ITE vector transformed map,
giving priority to the boundaries of the ITE map.
Owing to the different geographical area cover, the two maps do not coincide in their outside
boundaries. These mismatched areas were eliminated. In light of the intended DMEER scale of
1:2,500,000, all polygons smaller than 20 km 2 (3 mm² on the map) were eliminated and merged with
the neighbours with whom they shared the longest border. The result is a map covering about
10,480,000 km 2 , with 15,991 polygons, each one with a BfN potential vegetation code and an ITE land
classification value (Figure 4).
3.2 Data analysis
The resulting map has an attribute table that already includes information from both sources,
describing the potential natural vegetation unit and the land class for each portion of the map. This
table was exported to SAS (Statistical Analysis Software) and cross-tabulated, with land classes in
column headings (ITE), potential vegetation units as row headings (BfN), and each cell of the matrix
containing the total area of co-occurrence of a single potential vegetation BfN and land class unit ITE.
The resultant matrix is 580 x 57 cells, since not all the BfN legend types represent real potential
natural vegetation (lakes, glaciers, etc.), and not all the ITE classes were in the identity map and were
therefore excluded from further analysis.
From this rectangular matrix, a square matrix of 580x580 was calculated to evaluate de Lance and
Williams (Dlw) distance between potential vegetation units, according to the area they shared in the
land class:
Dlw = Σ⎥ BfNij-BfNik⎥ / Σ( BfNij+BfNik)
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