Comparison of scale and scaling issues in integrated land-use models for policy support

Recently an increasing number of integrated land-use models have become available that support policy making. Inevitably, their model components represent processes that act on different scales and that use different levels of detail to represent those processes. Therefore, it is a challenge to integrate them properly. In this paper we analyse and compare scaling issues from four integrated models that are explicitly spatial and dynamic. All have a strong agricultural component and are developed to support policy making. From these examples we find that scaling issues in model integration typically involve trade-offs among four factors: (1) the scale at which end users or policy makers require information; (2) the scale at which processes take place and the representation of those processes in a single model; (3) the way to integrate model components representing processes occurring at different scales; and (4) the limitations posed by practical restrictions such as data limitations and computation speed. Furthermore we conclude that the complexity of the model components and the spatial and temporal resolutions applied in the models are generally related to the size of the study area, while its thematic resolution is mostly driven by user requirements. Finally we argue that more detail does not necessarily generate better results and might even give a false impression of the modelʹs accuracy.