Within the framework of ESA's Earth Observation Program, the Medium Resolution Imaging Spectrometer (MERIS) is developed as one of the payload components of the ENVISAT-1. MERIS is a fully programmable imaging spectrometer, however a standard 15 channel band set will be transmitted for each 300 m. pixel (over land) covering the visible and near-infrared wavelength range. Since MERIS is a multidisciplinary sensor providing data that can be input into ecosystem models at various scales, we studied MERIS performance relative to the scale of observation using simulated data sets degraded to various resolutions in the range of 12m. to 300m. Algorithms to simulate MERIS data using airborne imaging spectrometer data sets are presented, including a case study from GERIS 63 channel data over a agricultural site in central Spain (the Almaden test site). Through a pixel purity analysis, end members are derived from the MERIS-type data and subsequently used as input to a spectral unmixing analysis yielding fraction of end member (abundance) images. The original data as well as the abundance images are spatially analyzed using variogram surfaces and mapping accuracy is modeled at various spatial scales. We observe differences between the sampling resolutions (i.e., pixel size) found to be optimal for the different ground cover types. The optimal scale for observing different components of spectral mixtures varies depending on the type of mixture, however, the best possible resolutions in all cases of mixtures studied is below the envisaged 300 m. field of view for the MERIS sensor. The analysis of semivariogram surfaces demonstrates that the spatial distribution of the variance of the mixtures is invariant with scale, thus the observed mapping discrepancies are not related to the data processing but to the observations themselves.