Evaluation of VEGETATION and PROBA-V phenology using phenocam and eddy covariance data

Kevin Bórnez, Andrew D. Richardson, Aleixandre Verger, Adrià Descals, Josep Peñuelas

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

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).

Original languageEnglish (US)
Article number3077
JournalRemote Sensing
Volume12
Issue number18
DOIs
StatePublished - Sep 2 2020

Keywords

  • FLUXNET
  • Land-surface phenology
  • Leaf area index
  • PROBA-V
  • PhenoCam
  • SPOT-VEGETATION

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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