The present invention provides an estimate of the prior requested in a crop allocation model. The crop allocation model is a mathematical modelling to estimate crop area, yield and production for 42 major crops in the world across a global 5 arc minute grid. The model uses a downscaling approach that accounts for spatial variation in the biophysical conditions influencing the productivity of individual crops, and uses crop gross revenue potential of alternate crops when considering how to prioritize the allocation of specific crops to individual gridcells. The proposed methodology is an entropy-based optimization procedure that imposes a range of consistency and aggregation constraints. A particular feature of this method is the explicit inclusion of error terms. There is inherent uncertainty in many aspects of the model, such as input data, incomplete information on farmers' behavior, spatial heterogeneity of crop varieties and managements cross regions in the world. By explicitly including error terms, this method directly deal with such uncertainties, which leads to better and more reliable estimates.