Generation of agricultural maps for yield potential by fusion of yield mapping, remote sensing, digital relief maps and cultivation data One of the most important parameter for agricultural crop production is the expected yield potential of a specific crop species at each location. Based on the yield potential an optimization of the cultivation method and the specific production intensity can be performed. One of the biggest current obstacles is the efficient and synergistic processing and use of large amounts of spatial data of different spatial and temporal dimension, data availability and qualities (BigData). At this point, the planned project AgriFusion sets and aims on the synergy of previously underutilized data sources (remote sensing, yield data, and digital terrain models) with existing data (for example, data of the soil evaluation, soil sampling) to make these data directly usable for agricultural production. For this purpose methods of data fusion will be used, which meet the challenges in agricultural holdings. The results of data interpretation and -fusion can be used directly by farmers and can be integrated into operational data structures. An outstanding feature of the fusion algorithm used - Transferable Belief Model (TBM)- is in addition to the resulting map for example, the expected yield) to generate a map of the reliability of the result of the data fusion. The method should be developed within the project AgriFusion and will be implemented and validated on two large (Mecklenburg-Vorpommern, Brandenburg) and also small scale farms (Bavaria). AP - 1: preparation of data base and GIS structure AP - 2: Method exploratory and development, integration of methods AP - 3: Data collection and laboratory analysis AP - 4: Data Analysis AP - 5: Data Fusion AP - 6: Validation of the fusion results AP - 7: Build-up of the analysis module and providing a client for data implementation in farm management systems and GIS applications