Potential of Sentinel-1 time-series data for monitoring the phenology of European temperate forests

Abstract

Time series from optical sensors are frequently used to retrieve phenology information of forests. While SAR (synthetic aperture radar) sensors can potentially provide even denser time series than optical data, their potential to retrieve phenological information of forests is still underexplored. In addition, the backscatter information from SAR is frequently exploited in the same way (e.g., via dynamic thresholding) as optical data to retrieve phenological information. Sentinel-1 backscatter coefficients of VH (vertical–horizontal) and VV (vertical–vertical) polarizations and their ratio were retrieved for temperate deciduous broad-leaf and evergreen needle-leaf forests in Europe. Breakpoints and dynamic thresholds were retrieved in the locally smoothed time-series data and compared to reference data from PhenoCam and fluxtower networks. It was generally found that breakpoints outperform dynamic thresholds in both forest types in terms of root mean squared differences, bias and $R^2$. Best results were achieved using breakpoints on the Sentinel-1 backscatter ratio with RMSEs of 18.4 days for the start of the season (SOS) and 14.0 days for the end of the season (EOS) compared to the 25% dynamic threshold of the seasonal amplitude in the reference data in deciduous broad-leaf forests. Substantially higher RMSE values of 56.7 days for SOS and 56.5 days for EOS were found in evergreen needle-leaf forests. This study suggests the potential of Sentinel-1 for the phenological retrieval of forests, in particular deciduous broad-leaf forests. This information could be used in combination with frequently used optical data to provide comprehensive phenological information on a large scale.