In the current context of climate change and increasing pressure on resources, the agricultural production model is being questioned. The challenge of a more autonomous, efficient and sustainable production of proteins must be met by increasing the use of legumes in French cropping systems. The pea (Pisum sativum L.) crop model “AzodynPea” will be used to identify zones and management techniques favorable to the crop in Burgundy-Franche-Comté (eastern France), taking into account abiotic stresses, such as winter frost or water deficit. The first step in this process is the mapping of current soil properties and current and future climate characteristics of the region. Regionalized daily climate data at 8 km resolution were obtained by simulation for the historical period 1980-2005 and for the prospective period 2006-2100, exploring two climate change trajectories: an optimistic (RCP 4.5) and a pessimistic one (RCP 8.5). The soil data were extracted from the Regional Soil Geographical DataBase and then processed to create a new semantic database in addition to the spatial data (Soil Map Unit polygons-SMU). The characteristics of the majority Soil Typological Units (STU) in each SMU have been kept. Variables such as soil depth, pH and organic matter were directly read from the database while others such as the soil available water capacity (AWC) or the bulk density were deduced from the semantic data using pedotransfer functions. The second step of the process was the mapping, in Burgundy-Franche-Comté, of historical (1980-2005) and prospective (2006-2100) flowering dates using climatic data for two pea varieties (one winter and one spring) and one sowing date per variety.