Modelling of landscape structure, composition and potential
In this group we include methods aimed at expressing the spatial dimension of landscape effects, which are largely used to represent landscape in terms of composition and structure.
General Purpose and Application
The basic use of these tools is to provide a spatial representation of landscape phenomena, to trace the effects of main drivers (including policy variables) on landscape composition and structure. Methods based on statistical and econometric techniques, which use observed data, use models derived from the relevant theory of the phenomena described by data.
Lessons learned
The data source is important as can be seen from the results of the Märkische Schweiz (Germany), where variogram models and geostatistical simulations have been applied to map landscape services, competition and synergies in the landscape. Probability maps provide a straightforward visualization tool to explore the impact of one or more continuous or ordered categorical covariates on the likelihood of single or joint landscape services potential supply. The assessment of service richness can be made at different aggregation levels in order to support different stakeholder in planning and decision making.
In general these models highlight changes in land use or hot and cold spots enable a better understanding of the consequences of agricultural policy and other drivers on the agricultural economy and land use.