Landscapes Forest and Global Change - ESA - Escola Superior ...

K. Koschke et al. 2010. Using a multi-criteria approach to fit the evaluation basis of “Pimp Your Landscape”
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2. Methodology
Within PYL the provision of ecosystem services is evaluated in a first step for each land-use
type and infrastructural element. In a second step, the value at the landscape level is calculated
as the average of all cell values; this includes an additional correction of the result from the
point of view of positive or negative aspects gleaned from the landscape structure (cf. Fig. 1 in
Fürst et al., 2010).
Within PYL the land use classification standards of CLC 2000 and the environmental services
(and functions) (LUF) set previously described (Pérez-Soba et al. 2008) are available as initial
settings. The user can modify these initial settings or adopt completely different settings
according to the regional application targets. After having selected a set of LUTs and LUFs, the
resulting value matrix must be filled out. Evaluation of the land-use types follows classification,
on a relative scale from 0 (worst case) to 100 (best case), of the specific regional contribution of
a LUT to a LUF. The introduction of this relative scale aims to facilitate the multi-criteria
evaluation of planning measures.
The value matrix contains initial impact values of the land use types and infrastructural elements
on the environmental services. The initial value of a land use type for an environmental service
represents the maximum in the regional context, which can only be reduced (a) with regard to
environmental cell attributes from additional information layers such as height above sea level,
mean annual precipitation, temperature, soil type and exposition. (b) The impact of the cell
environment (homogeneous land use types vs. different land use types) and neighbourhood type
(edge to edge vs. corner to corner) can impact the original maximum value. The influence of
structural features on the final evaluation is discussed elsewhere (cf. contribution of
Frank et al.).
2.1 Indicator-based assessment
2.1.1 Statistical indicators
Evaluation of ecosystem services is commonly based on indicators. For our assessment the
challenge is to find or generate indicators associated to LUTs which can then be processed in an
aggregation framework to estimate comparative scores.
Despite the general scarcity of indicators, a few economic-evaluation indicators are available
that allow for a comparison of LUT-related land prices. We used standard ground value, land
rent and market price to compute land-use dependent value points. We had two prerequisites for
the choice of an indicator. The first condition was a thematic relation to at least two LUTs.
Second, data had to be available on a per unit area basis due to 100 x 100m grid cells used as
the reference unit in PYL. Quotients of indicator values were calculated to reflect the value of
an LUT in comparison to another LUT (see table 1). For each LUT the mean of quotient-values
was determined and normalised to the scoring scale (0 – 100 value points) using equation 1. The
standard ground value acts as a “cross link” as it integrates information about semi-natural and
artificial (urban) LUTs.
Tab. 1
2.1.2 Measured and modeled indicators
Other sources of indicators are regional studies with a land-use oriented background. Data
relating to N-export (LfULG 2009), soil sealing and run-off coefficient (Arlt 2001) could be
derived from such studies (table 2). Indicator values were normalized using equation 1 or 2.
When an indicator’s link to the performance of an LUF was negative, equation 2 was utilized. In
Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology
Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.)
2010, Instituto Politécnico de Bragança, Bragança, Portugal.