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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., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

In rural regions, land use changes (LUC) are often the result of the decision-making of individual farmers. To influence this decision-making, compulsory and voluntary mechanisms are implemented. However, farmers' decision-making is a heterogeneous process that depends on their ability and willingness to take certain decisions. Discrepancies between farmers' ability and willingness and the design of voluntary mechanisms occur frequently. This makes it necessary to understand how farmers' participation in these mechanisms can affect LUC. The aim of this paper was to demonstrate an agent-based approach to analyse and explore how voluntary mechanisms can influence LUC processes in rural regions. This approach was applied to a rural region in Australia, where clearing of native vegetation has occurred for agricultural development. Historical land cover data and semi-structured interviews were used to parameterise an agent-based model. Factors that influence farmers' ability and willingness to participate in these mechanisms were identified. Three scenarios were simulated with the model to explore how the implementation of different voluntary mechanisms can affect the landscape structure of the region. This paper identifies how the diversity of farmers' decision-making can influence the landscape structure in the region. The advantages and limitations of an agent-based approach in relation to LUC research and policy are discussed., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Multi-agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. The main goal is to explore the use of MAS to simulate spatial scenarios based on modelling multi-actor decision-making within a spatial planning process. We demonstrate MAS that consists of agents representing organizations and interest groups involved in an urban allocation problem during a land use planning process. The multi-actor based decision-making is modelled by generating beliefs and preferences of actors about the location of and relation between spatial objects. This allows each agent to confront these beliefs and preferences with it's own desires and with that of other agents. The MAS loosely resembles belief, desire and intentions architecture. Based on a case study for a hypothetical land use planning situation in a study area in the Netherlands we discuss the potential and limitations of the MAS to build models that enable spatial planners to include the 'actor factor' in their analysis and design of spatial scenarios. In addition, our experiments revealed the need for further research on the representation of spatial objects and reasoning, learning and communication about allocation problems using MAS.