A. Jellema

TL;DR: In this paper, the authors present the Landscape IMAGES methodology for spatially explicit exploration of options for multifunctional agriculture in landscapes at a scale of a few km2, which provides explicit insight in the trade-off between the objectives and is implemented in a visual application that enables the comparison of alternative options.

TL;DR: An application of the explorative Landscape IMAGES framework, which employs the Differential Evolution optimization strategy and the concepts of Pareto optimality that are relatively easy to implement and to combine with spatially explicit indicator assessments is presented.

TL;DR: A new methodology for landscape character assessment is presented using the pattern of landscape features as stored in a GIS to delineate, characterize and evaluate landscapes using a region growing algorithm to elucidating features that are important for the identity of a region.

TL;DR: In this paper, a set of criteria are proposed for the evaluation of the potential contribution of modelling tools to strengthening the multifunctionality of agriculture, including policy relevance, the temporal resolution and scope, the degree to which spatial and socio-institutional scales and heterogeneity are addressed, and the level of integration in the assessment of scientific dimensions and of the multiple functions of agriculture.

TL;DR: Although the model portfolio did not completely satisfy the demands of the set of evaluative criteria, it is concluded that, due to their complementarities, in combination the three models could significantly contribute to further development and strengthening of multifunctionality.