Regional bioenergy models serve to match areas of high biomass production with suitable locations for plants to convert this biomass to energy. Increasingly, digital data for such models is becoming available at finer spatial scales. One important category of data still poses a problem. Agricultural statistics are collected at the farm level but only made available to researchers at the agricultural district level. This paper investigates the economic and environmental need for more spatially detailed models and identifies a number of obstacles in the disaggregation of district-level agricultural statistics. It concludes that various options for disaggregation exist but disaggregation comes at a price. The real benefits of disaggregation can only be assessed if an analysis is repeated at different levels of disaggregation.