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Title: Evaluation of VEGETATION and PROBA-V Phenology Using PhenoCam and Eddy Covariance Data
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 (R2 > 0.7) between the satellite LSP and ground-based observations from both PhenoCam and FLUXNET for the timing of the start (SoS) and R2 > 0.5 for the end of season (EoS). The threshold-based method performed the best with a root mean square error of ~9 d with PhenoCam and ~7 d with FLUXNET for the timing of SoS (30th percentile of the annual amplitude), and ~12 d and ~10 d, respectively, for the timing of EoS (40th percentile).  more » « less
Award ID(s):
1832210 1637685 1702697
PAR ID:
10213482
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Remote Sensing
Volume:
12
Issue:
18
ISSN:
2072-4292
Page Range / eLocation ID:
3077
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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