Background: The aim of the maps was to develop one such “new
geography” which supports their territorial identity through the identification
of natural and environmental assets. The characterisation of territories
provides baseline information about the environmental “value” of a specific
region, i.e. if the region owns environmental assets that make it unique and
that hence could support the development of the region by properly and
sustainably exploiting the asset item.
Urban – rural typologies / Rural
High nature value farmlands
Proximity to natural areas (CLC
semi-natural classes, N2000, CLC water)
Air quality (PM10)
Degree of soil sealing
range of values in the different input data sets was standardised to five
classes. These five classes were assumed to represent a gradient of “natural
and environmental assets” for each grid cell.
distribution of input data values to the five output classes were based on the
median of the original data and their standard deviation. Scores are attributed
to each class.
degree of “natural and environmental assets” is calculated from the sum of the
five individual input layers. The range of values is between 5 (= 5 x 1) and 75
(= 5 x 15). The resulting layer was classified into five classes:
1 Very low natural assets
5 – 22 points
2 Low natural assets
23 – 35 points
3 Average natural assets
36 – 48 points
4 High natural assets
49 – 60 points
5 Very high natural assets
61 – 75 points
next step, the “natural and environmental assets”-classification was clipped to
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(TV, DVD player, stereo system) into a single multi-socket electrical bar. When not in use, simply switch off the bar and save on the electrical consumption by as much as 10 % (approximately 200 000 W a year). Appliances left on standby still use quite a lot of electricity.
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