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DREAM
STEP 1: 2020-2022
Funded by the l’EUR ISbBlue and PNTS
The DREAM project aims to document and understand the past decadal variability of phytoplankton biomass, their assemblages and associated primary production at global scale, as well as the underlying mechanisms. To do this, a methodology combining artificial intelligence with radiometric satellite observations and ocean and atmospheric dynamics is used to reconstruct past time series of phytoplankton biomass.
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Main researchers involved: J. Roussillon & T. Gorgues UMR LOPS; L. Dumetz & R. Fablet IMT-Atlantique, UMR Lab-STICC.
DREAM: Éducation
Associated publications
Martinez, E., Brini, A., Gorgues, T., Drumetz, L., Roussillon, J., Tandeo, P., ... & Fablet, R. (2020). Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean. Remote Sensing, 12(24), 4156.
Martinez, E., Gorgues, T., Lengaigne, M., Fontana, C., Sauzède, R., Menkes, C., ... & Fablet, R. (2020). Reconstructing Global Chlorophyll-a Variations Using a Non-linear Statistical Approach. Frontiers in Marine Science, 7, 464.
DREAM: Expérience
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