 The study compares the performance of various trend estimation methods for quantifying changes in ecosystem productivity using satellite observations of normalized difference vegetation index, NDVI, and demonstrates that performance decreases with increasing inter-annual variability in the NDVI time series. The study recommends applying annual aggregated time series or seasonal trend models for better trend slope estimates and suggests that breakpoint detection analysis can lead to wrong or opposite trend estimates if overestimated. The results indicate that greening NDVI trends are more prevalent in Alaska than browning trends, and detected breakpoints tend to coincide with large fires. Seasonal trend methods need to be improved against inter-annual variability to accurately quantify changing trends in ecosystem productivity. This article was authored by Marcus Reichstein, Miguel de Mahetcha, Christopher S.R.N.A., and others.