Remote sensing studies of vegetation phenology increasingly benefit from freely available satellite imageryacquired with high temporal frequency at fine spatial resolution. Particularly for heterogeneous landscapes thisis good news, given the drawback of medium-resolution sensors commonly used for phenology retrieval (e.g.,MODIS) to properly represent the fine-scale spatial variability of vegetation types. The Sentinel-2 mission acquiresspectral data globally at 10 to 60m resolution every five days. To illustrate the mission's potential forstudying vegetation phenology, we retrieved phenological parameters for the Dutch barrier islandSchiermonnikoog for a full season of Sentinel-2A observations in 2016. Overlapping orbits resulted in two acquisitionsper 10 days, similar to what is achieved globally since the launch of Sentinel-2B. For eight locations onthe island's salt marsh we compared greenness chromatic coordinate (GCC) series derived from digital repeatRGB-cameras with vegetation index series derived from Sentinel-2 (NDVI and GCC). For each series, a doublehyperbolic tangent model was fitted and thresholds were applied to the modelled data to estimate start-, peak-,and end-of-season (SOS/PS/EOS). Variability in Sentinel-2 derived SOS, when taken as the midpoint betweenminimum and peak NDVI, was well-explained by camera GCC-based SOS (R2=0.74, MSD=8.0 days,RMSD=13.0 days). However, EOS estimates from camera GCC series were on average almost two monthsbefore NDVI-based estimates. This could partially be explained by the observed exponential relationship betweenGCC and NDVI, as well as by the combined effect of viewing angle differences and the presence of nonphotosyntheticelements in the vegetation canopy. A two-layer canopy radiative transfer model incorporatingreduced chlorophyll levels in the upper layer provided a physically-based explanation of the viewing angleeffect. Finally, we applied the phenology retrieval approach to NDVI series for all pixels of the island in order tomap spatial patterns of ...