Abstract
Recent studies have shown that the optimal spatial resolution of remotely sensed data for the identification of scene elements is extremely variable depending on several factors. In particular, for the classification of each cover class using satellite sensor imagery there is generally an optimum aggregation level which is mainly related to the average size of the ground plots and to their internal homogeneity. In the present paper a methodology is presented for finding the relative optimum filtering size for the attribution of all pixels to some ground classes based on the maximization of fuzzy membership grades. Since these grades are indicative of the confidence of the pixel attribution to the classes, they can be used to select the best scale among differently filtered images. This hypothesis is investigated by means of a case study concerning a rugged, complex area in Central Italy sensed by bi‐temporal TM scenes. The results testify to the good performance of the approach which also shows promise for the integration of multi‐source data.