The aim of this paper is to demonstrate how a spatial fuzzy clustering mean expands the knowledge of the European agri-environmental initiative impact, named Measure 214, in the Sardinia Region. While sketching out the geographic area covered by the measure for analysis and investigation using fcm is a fruitful approach, their integration with social and economic factors is an essential step in understanding agricultural growth and how it is influenced by environmental policy. This integrated approach shows how agri-environmental measures tend to develop in the region and, geographically, describes the spatial effects. Fuzzy clustering analysis demonstrates how decisions, whether they are related to the pursuit of policies moving towards the agri-environmental initiatives of organic farming and sustainable agriculture, or whether they concern ways of financing the measure’s activities, belong to the sphere of information, able to influence the new phase of agri-environmental financing and to keep it going. The spatial expansion of the measure all over the Region can help identify where the measure has taken root and in which directions it should be steered to achieve sustainable agri-environmental development in the area. Furthermore, the fuzzy cluster analysis highlights the relevance of the results, showing the policy direction that clusters should take in order to improve the measure’s effectiveness.
Keywords: Agri-environmental measure, fuzzy c-means, geographical information system, cap
Jel Code: Q15, Q18