Data from Van Asselen, S. & Verburg, P.H. (2012).  A Land System representation for global assessments and land-use modeling. Global Change Biology, 18(10): 3125-3148

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Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover, often using a resolution of 0.5 degree (approximately 50 x 50 km at the equator). To improve such assessments we have developed a new global representation of land cover and land use, at 5 arcminute resolution (9.25 x 9.25 km in equal area projection Eckert IV, as is used here). The new Land System classification represents land cover and land use in mosaic landscapes with different land-use management intensity and livestock composition, which are important aspects of the land system.

We have also tested if global assessments can be based on globally uniform allocation rules. Logistic regressions were used to analyze variation in spatial determinants of Land Systems. This analysis indicates strong associations between Land Systems and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a Land System differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales.

Using Land Systems in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and livestock composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions.


For more information contact Prof. Dr Peter Verburg