Changes in the timing of phenological events are a critical parameter for quantifying the impact of climate alterations on vegetation development that in reverse alters patterns of biosphere-atmosphere interactions. By the means of remote sensing, numerous approaches have been developed for deriving Land Surface Phenology. This study aims at identifying the best combination of data quality integration, filtering and threshold choice for the Start of Season (SOS) in Germany using MODIS data. The resulting remote sensing based SOS is related to phenological ground observations. For the year 2010, SOS data was produced by 5 different methods and the best method was identified by the comparison of the SOS dates to ground observations of the leaf unfolding of Broad-Leaved forest and beginning of turning green for Pastures, respectively. The results show that the impact of time series data quality screening, filter choice and threshold setting differs among the selected land cover classes.