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In recent decades several methods have been proposed to simulate land-use changes in a spatially explicit way. in these models land is generally represented on a lattice with celi states indicating the predominant land use. Since a celi can have only one state, mixed land uses and different densities of one land use can only be introduced superficially, as separate celi states. in this paper vve describe a cellular automata model that simulates dynamics in both land uses and activities, where activities represent quantitative information, such as the number of inhabitants at a location. Therefore each celi has associated with it (1) a value representing one of a finite set of land-use classes, and (2) a vector of numerical values representing the quantity of each modelled activity that is present at that location. This allows simulation of incremental changes as well as mixed land uses. The proposed model is tested vvith a synthetic application that uses two activities: population and jobs. it simulates the emergence of human settlements õver time from local inter-actions between activities and land uses. Assessment of results indicates that the model generates realistic urbanization patterns. [ABSTRACT FROM AUTHOR]

Highlights: [•] Fuzzy Kappa Simulation assesses the predictive accuracy of land use models. [•] It evaluates model results in terms of land use transitions, instead of land use classes. [•] At the same time, Fuzzy Kappa Simulation is sensitive to geographical nuance. [•] These properties overcome major limitations of existing map-comparison methods. [Copyright &y& Elsevier]

This paper presents an intraurban cellular automata model that is an extension to White and Engelen's pioneering model. The paper's main contribution is to distinguish between agglomerative eff ects, determined by the attraction of the neighbourhood, and disagglomerative eff ects, driven by land prices, or land aff ordability. In order to do that, social heterogeneity is introduced in the model at the intraurban level. As a result, we can simulate both the evolution of land use and land prices. An application of the model and a sensitivity analysis indicate that neighborhood infl uence is the main driving force of cities' spatial confi gurations. Prices, however, exert an important countereff ect. Actually, the higher the infl uence of land prices, the faster land succession is observed. Finally, an important conclusion of the model is that intraurban models should not fail to diff erentiate actors by income level. [ABSTRACT FROM AUTHOR]

With about half of its territory being farmed, agriculture is the main land use in the European Union (EU). As over 10% of the total EU manufacturing output comes from the agri-food sector, it also is an economic factor of great importance. Moreover, EU policy in this sector has far-reaching consequences ranging from the EU''s status as a global trade partner to landscape preservation and development. The LUMOCAP Policy Support System is targeted towards policy makers in the European Commission (EC) and its Member States (MS) and aims to provide support in the field of sustainable agricultural and rural development. To this end it incorporates an integrated model with socio-economic and bio-physical processes, operating at different spatial scales. For supporting integrated assessment, a large number of policy levers is included as inputs for these models and outputs are transformed into policy-relevant social, economic and environmental indicators. The whole system is framed in a flexible, modular and easy to use software package that is useable for process experts and policy-analysts alike. This paper describes the integrated model, the individual models and a first calibration of the system. It demonstrates the system's behaviour for typical scenario runs and concludes with a reflection on the current status of the system and some recommendations for further development. [Copyright &y& Elsevier]