Mapping Agricultural Land Cover and Land Use for Europe

Spatial disaggregation of the statistical information reduces uncertainty of input data for, and thus enhances the accuracy of biogeochemical models. Within the frame of the project CAPRI-DynaSpat, a methodology is being developed to spatially disaggregate statistical land cover and cropping information to be used within the biogeochemical model DNDC. The methodology estimates crop shares in Regional Land Cover Units (RLCUs) based on the Corine Land Cover Map (CLC2000) and the Land Use/Cover Area Frame Statistical Survey (LUCAS) on one hand, and using geographical information (soil information, land elevation, and climate data) on the other hand. Finally, both estimates are overlaid and a consistent estimation of crop shares is done for the resulting Homogeneous Spatial Mapping Units (HSMUs).JRC.H.2-Climate chang