Vegetation phenology from Sentinel-2 and field cameras for a Dutch barrier island

Remote sensing studies of vegetation phenology increasingly benefit from freely available satellite imagery with high temporal frequency at fine spatial resolution. Particularly for heterogeneous landscapes this good news, given the drawback of medium-resolution sensors commonly used for phenology retrieval (e. g. , ) to properly represent the fine-scale spatial variability of vegetation types. The Sentinel-2 mission acquires data globally at 10 to 60m resolution every five days. To illustrate the mission's potential for vegetation phenology, we retrieved phenological parameters for the Dutch barrier island for a full season of Sentinel-2A observations in 2016. Overlapping orbits resulted in two acquisitions 10 days, similar to what is achieved globally since the launch of Sentinel-2B. For eight locations on island's salt marsh we compared greenness chromatic coordinate (GCC) series derived from digital repeat-cameras with vegetation index series derived from Sentinel-2 (NDVI and GCC). For each series, a double tangent model was fitted and thresholds were applied to the modelled data to estimate start-, peak-, end-of-season (SOS/PS/EOS). Variability in Sentinel-2 derived SOS, when taken as the midpoint between and peak NDVI, was well-explained by camera GCC-based SOS (R2=0. 74, MSD=8. 0 days, =13. 0 days). However, EOS estimates from camera GCC series were on average almost two months NDVI-based estimates. This could partially be explained by the observed exponential relationship between and NDVI, as well as by the combined effect of viewing angle differences and the presence of nonphotosynthetic in the vegetation canopy. A two-layer canopy radiative transfer model incorporating chlorophyll levels in the upper layer provided a physically-based explanation of the viewing angle. Finally, we applied the phenology retrieval approach to NDVI series for all pixels of the island in order to spatial patterns of phenology at fine resolution. Our results demonstrate the potential of the Sentinel-2 for providing spatially-detailed retrievals of phenology.