Agri-environmental schemes (AES's) are the main policy tool of the European Union to tackle negative spillover effects arising from agriculture. AES's are voluntary – farmers choose whether and how much land to convert. Its low uptake suggest that  all the costs and barriers are not well understood. AES's are designed in a "one size fits for all approach" (Vesterager et al., 2016) without considering how differences in farm structure environmental factors, and personal values factors affect farmers' decision making, as indicated by the literature (Hassler et al., 2022). Thus, acknowledging that farmers have varied motivations, costs and barriers urge for the design of tailored contracts. Segmenting the agricultural populations into a typology is a common approach to explore their heterogeneity and identify specific strategies, preferences, and constraints.

The typology is built in a three steps process: i) firstly we identify farm clusters based on the structural, demographic, and land-use type variables, ii) We, then, focus on the values assessment data to identify functional clusters, and iii) at the final step we check whether the farm and functional typologies are correlated. The data will be collected through a two-parts survey, with the first aiming to capture economic endowments and land use features while the second captures the personal values determinants for pro-environmental behaviour (egoistic, hedonistic, biospheric, and altruistic). It is, then, analysed using multivariate data analysis tools.

 We are currently selecting the most relevant variables for the Danish context and establishing a hypothesis regarding the number of "structural clusters". This is done in consultation with experts from SEGES and researchers.

To the best of our knowledge, the integration of farm and farmer typlogies has been explored once and in a very different context (Hammond et al., 2017). Given, the exploratory nature of this study it is hard to state whether the typologies that emerge from the analysis are correlated. In any case, the results will point directions on how AES's can be designed to target different groups of farms and farmers.