Bornez, K; Richardson, AD; Verger, A; Descals, A; Penuelas, J (2020). Evaluation of VEGETATION and PROBA-V Phenology Using PhenoCam and Eddy Covariance Data. REMOTE SENSING, 12(18), 3077.

High-quality retrieval of land surface phenology (LSP) is increasingly important for understanding the effects of climate change on ecosystem function and biosphere-atmosphere interactions. We analyzed four state-of-the-art phenology methods: threshold, logistic-function, moving-average and first derivative based approaches, and retrieved LSP in the North Hemisphere for the period 1999-2017 from Copernicus Global Land Service (CGLS) SPOT-VEGETATION and PROBA-V leaf area index (LAI) 1 km V2.0 time series. We validated the LSP estimates with near-surface PhenoCam and eddy covariance FLUXNET data over 80 sites of deciduous forests. Results showed a strong correlation (R-2 > 0.7) between the satellite LSP and ground-based observations from both PhenoCam and FLUXNET for the timing of the start (SoS) and R-2 > 0.5 for the end of season (EoS). The threshold-based method performed the best with a root mean square error of similar to 9 d with PhenoCam and similar to 7 d with FLUXNET for the timing of SoS (30th percentile of the annual amplitude), and similar to 12 d and similar to 10 d, respectively, for the timing of EoS (40th percentile).