Centrum Geo-informatie, Centrum Landschap - Mens en Maatschappij, Leerstoelgroep Bos- en natuurbeleid, Laboratorium voor Geo-informatiekunde en remote sensing
In the last decade policy makers have increasingly recognized the need to include people’s perceptions in methods for describing landscape quality. At the same time, a third wave of Geographic Information Systems (GIS) has become available that make it technically possible to model landscape quality in a realistic manner. However, as there is often a mismatch between science and policy, it remains unclear to what extent perception-based models developed by scientists can be useful to policy makers. The aim of the present study was to evaluate the usefulness to policy making of a GIS-based procedure for describing perceived landscape openness. To this end, a workshop was organized which was attended by eight Dutch policy makers who acted as representatives of their province (region). The Group Decision Room (GDR) technique was used to elicit the policy makers’ evaluations of the procedure in an anonymous and reliable manner. The procedure was presented to the policy makers using cases from their own province, which they assessed using a mixture of qualitative and quantitative methods. The results show that policy makers rated the procedure as being highly relevant to policy making, scientifically credible, usable by policy makers and feasible to implement in the policy making process. They especially appreciated the flexibility and transparency of the procedure. The policy makers concluded that the procedure would be of most value for monitoring landscape changes and for analysing impacts on landscape openness in land use scenario studies. However, they requested guidelines for proper implementation of the various options in the procedure. In general, the current study shows that explicit and transparent evaluation of the usefulness of GIS-based tools can aid integration at the science–policy interface and help to ensure that both scientists and policy makers are informed of interrelated options and requirements.