This study presents a three-step methodology to generate, map and simulate indicators of agricultural activity for use in landscape-scale analyses. Step one is the farm data set up combining digital agricultural registers and national statistics. Step two is the geographical mapping based discrete field-blocks, defined as geographical units including one or more fields surrounded by relatively permanent boundaries such as roads, streams or hedgerows. Step three is the actual modelling, where agricultural activity is simulated with the agricultural sector model ESMERALDA, and the following animal manure application ex store is calculated. As an example the current and expected future distribution of gross margins and manure-nitrogen (N) applications are mapped for the 330 km2 study area of Bjerringbro and Hvorslev municipalities in Denmark. Within these municipalities, a significantly higher manure-N application is foundin areas of special interest for clean groundwater, indicating a higher N-pollution. However, the highest average gross margin is also found within these areas, so political weighting of socio-economic benefits against environmental costs is necessary. This conclusion might not be true in other areas, but the methodology has general application, and provides a framework for producing landscape-scale maps from a range of available national databases. Further development and verification of the methodology is recommended, thereby allowing more extensive analysis of geographical distributions in agricultural activity and environmental effects.