The possibilities of using MERIS full resolution (FR) data to extract sub-pixel land cover composition over The Netherlands are explored in this paper. More precisely, the use of MERIS FR time series is explored in this paper since it should facilitate the discrimination of spectrally similar land cover types because of their seasonal variations. The main steps of the methodology used to extract sub-pixel information can be summarized as follows. First, a set of seven MERIS FR Level 1b images that covered the period February to December 2003 were selected. Second, the images were projected into the Dutch national coordinate system. Special attention was paid to this process in order to account for the orbital differences of each MERIS acquisition. Third, a cloud screening algorithm was applied to all MERIS images. Next, the MERIS level 1b TOA radiances were converted into surface reflectance. After that, the latest version of the Dutch land use database (LGN5) was used to support the selection of the endmembers from the MERIS images. Finally, a constrained linear unmixing algorithm was applied to each of the MERIS scenes and to the multi-temporal dataset. The results were validated both at sub-pixel and per-pixel scales using the LGN5 as a reference. The paper concludes by describing the potential and limitations of the selected approach to extract sub-pixel land cover information over heterogeneous and frequently clouded areas.