Environmental Engineering Reference
In-Depth Information
the Habitats map; quality and singularity of the units in the Landscape map; quality
and singularity of the units in the Soil map; total vegetation and forest cover; and
forest fragmentation.
A basic panel of 15 experts (from the Technical and Complutense Universities of
Madrid) was consulted in order to obtain a set of four raster layers: naturalness of the
units in the Corine Land Cover and Landscape maps; and quality of the units in the
Soil map. A raster layer of naturalness of the units in the Habitats map was generated
using the naturalness value for each polygon on the map, which were previously
assigned by the experts who participated in the European Habitat Project.
We assess the territorial basic singularity of the different categories or classes in
these maps, using an objective index of basic singularity Eq. 1
[10]
.
Max
−
x
(1)
S
= −
Ln
1
×+
100 1
Max Min
−
where S = territorial basic singularity index; Max = ha of the map's largest cate-
gory; Min = ha of the map's smallest category; x = ha of the map category being
evaluated.
This continuous scale is then transformed into a discrete scale of five classes
(rounding each decimal value up to the next whole number). We thus obtain a
higher singularity value for the least represented classes in the territory, in order to
safeguard biodiversity.
We evaluate the degree of territorial basic fragmentation of the different catego-
ries in the Forestry and Habitats maps, using an objective classification calculated
with the GIS
[10]
:
1. We calculate the surface area of each of the polygons on these maps.
2. We assign a scale of four discrete values which correspond to each of the four per-
centiles of the numeric distribution of frequencies of surface sizes: Fragmentation
class 1 = those sizes of polygons corresponding to the irst percentile (0-25%)…
fragmentation class 4 = those sizes of polygons corresponding to the fourth
percentile (75-100%). The greatest value of the fragmentation variable is assigned
to the polygons in the fourth percentile.
Normalisation of the 12 Variables
The 12 variables are normalised (transformed into a common final continuous scale
from 0 to 1) to avoid overlapping during their subsequent integration into the
model. Formula 2 is used to convert the discrete scales.
x
−
0.5
(2)
Xn
=
Max
