@article{85acacf7d87e48309550eee43ca91a3b,
title = "Evaluation of VEGETATION and PROBA-V phenology using phenocam and eddy covariance data",
abstract = "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).",
keywords = "FLUXNET, Land-surface phenology, Leaf area index, PROBA-V, PhenoCam, SPOT-VEGETATION",
author = "Kevin B{\'o}rnez and Richardson, {Andrew D.} and Aleixandre Verger and Adri{\`a} Descals and Josep Pe{\~n}uelas",
note = "Funding Information: This research received no external funding. The LAI products were generated by the Global Land Service of Copernicus, the Earth Observation program of the European Commission. The products are based on 1 km SPOT-VEGETATION data (copyright CNES and distribution by VITO NV) and on PROBA-V 1 km data (copyright Belgian Science Policy and distribution by VITO NV). This research was supported by an FPU grant (Formaci{\'o}n del Profesorado Universitario) from the Spanish Ministry of Education and Professional Training to the first author (FPU2015-04798), the Copernicus Global Land Service (CGLOPS-1, 199494-JRC), the Spanish Government grant PID2019-110521GB-I00, the Catalan Government grant SGR 2017-1005 and the European Research Council Synergy grant ERC-2013-SyG-610028 IMBALANCE-P. We thank our many collaborators, including members of the PhenoCam project team as well as site PIs and technicians, for their efforts in support of PhenoCam. A.D.R. acknowledges for PhenoCam from the Northeastern States Research Cooperative, NSF (EF-1065029, EF-1702697), Department of Energy (DE-SC0016011), and United States Geological Survey (G10AP00129, G16AC00224). Publisher Copyright: {\textcopyright} 2020 by the authors.",
year = "2020",
month = sep,
day = "2",
doi = "10.3390/RS12183077",
language = "English (US)",
volume = "12",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "18",
}