Spatial allocation of farming systems and farming indicators in Europe

In this article an approach to spatially allocate farm information to a specific environmental context is presented. At this moment the European wide farm information is only available at a rather aggregated administrative level. The suggested allocation approach adds a spatial dimension to all sample farms making it possible to aggregate farm types both to natural and to lower scale administrative regions. This spatial flexibility allows providing input data to economic or bio-physical models at their desired resolution. The allocation approach is implemented as a constrained optimization model searching for an optimal match between farm attributes and spatial characteristics subject to consistency constraints. The objective functions are derived from a Bayesian highest posterior density framework. The allocation procedure recovers the spatial farm type distributions satisfactorilly thereby providing information of significant value for further analysis in a multidisciplinary context.

Research highlights▶ EU wide allocation of representative sample farms to natural endowment. ▶ Results can serve as input data for models working with European coverage. ▶ Various sources of prior information combined in a high posterior density estimator. ▶ Accuracy of results increases when additional prior information is used.