Deriving phenological layers for Germany from remote sensing data: spatio-temporal analysis ans validity

Abstract

Information on the timing of phenological events and their changes are critical parameters for quantifying the impact of climate alterations and of major relevance for terrestrial ecosystem models. Spatially consistent phenological information can be derived from remote sensing based vegetation indices by calculating phenological metrics such as Start of Season (SOS), End of Season and Length of Season (LOS). Different approaches exist for preprocessing of time series from medium resolution satellite data as well as for derivation of phenological metrics, but these methods often lack any biophysical or ecological meaning and qualitative comparisons between different methods are rare. This study aims at (1) deriving SOS as an indicator for the onset of spring in Germany, (2) comparing the phenological layers with phenological ground observations and the global MODIS “Land Surface Dynamics” product and (3) developing value added phenological layers from the data to (4) characterize spatiotemporal variations.