Modelling of land cover and agricultural change in Europe: Combining the CLUE and CAPRI-Spat approaches

W. Britz, P.H. Verburg, A. Leip

    Research output: Contribution to JournalArticleAcademicpeer-review


    Recent European research projects have developed approaches that downscale land use related results of economic models. These results are primarily downscaled from the national or regional scale to a spatial resolution appropriate for environmental impact analysis. Different studies represent the interactions between the economic and geographic components of the land system in different ways. This paper explores how interactions between economic and geographic aspects of the land system can be strengthened in modelling studies. It does so by comparing two existing approaches (CLUE and Capri-Spat) for the European Union (EU27). CLUE focuses on disaggregating national level changes in claims for agricultural and urban area to a 1 km × 1 km grid, explicitly addressing consequences of changing demands for agricultural and urban area for other land uses such as (semi-) natural vegetation. Whereas, CAPRI-Spat is concerned with agricultural land use, disaggregating cropping shares, animal stocking densities, yield and agricultural input use for mapping units. The mapping units are clusters of 1 km × 1 km pixels considered homogenous in terms of soil, slope, land cover and administrative region. This paper discusses differences between the two models relating to geographical units, distribution algorithm and most importantly diverging interpretation of 'agricultural land', in relationship to their respective concepts and objectives. It concludes that a stronger integration of the geographic and economic aspects can be achieved by linking the overall land use dynamics simulated by CLUE to the detailed representation of the agricultural sector by CAPRI-Spat. Therefore, relative changes in land use classes at 1 km × 1 km resolution obtained from CLUE simulations update a priori means in CAPRI-Spat entering a Highest Posterior Density Estimator. The findings of this study contribute to our overall capacity to integrate approaches from different disciplines in the integrated analysis of land change and the ex ante assessment of environmental and economic effects of agricultural policies. © 2010 Elsevier B.V.
    Original languageEnglish
    Pages (from-to)40-50
    JournalAgriculture, Ecosystems and Environment
    Publication statusPublished - 2011


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