satellIte phytoplaNkton Drivers In the Global Ocean over 1998-2015 (INDIGO Benchmark dataset)
This benchmark dataset contains the physical data used as predictors to reconstruct global chlorophyll-a concentrations (Chl, a proxy of phytoplankton biomass) in Roussillon et al., as well as the reference satellite Chl target fields. The nine physical predictors' data (Short-Wave radiations, Sea Surface Temperature, Sea Level Anomaly, Zonal and meridional surface currents, Zonal and meridional surface wind stress, Bathymetry, Binary continental mask) were extracted from publicly available datasets over [1998-2015] and resampled to the same spatio-temporel resolution as Chl, i.e. monthly on a 1°x1° grid between 50°N and 50°S. Missing values were gap-filled using the heat diffusion equation. Each variable was normalized by substracting its mean from the original values and dividing by its standard deviation over [1998-2015].
This dataset was used to train and validate the Multi-Mode Convolutional Neural network (CNNMM8) introduced in Roussillon et al. ; reconstructed monthly Chl fields over the [2012-2015] test period are also provided here.
We hope this benchmark dataset can help to promote the improvements of methods as well as the emergence of new ideas, as building datasets is sometimes more time-consuming than the implementation of machine learning tools themselves. This would also facilitate the quantitative comparison of models performances' on the exact same datasets.
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Citation proposal
Roussillon Joana (UMR6523 Laboratoire d'Oceanographie Physique et Spatiale (LOPS), France) - Fablet Ronan (IMT Atlantique, Lab-STICC, UMR CNRS 6285, France) - Gorgues Thomas (UMR6523 Laboratoire d'Oceanographie Physique et Spatiale (LOPS), France) - Drumetz Lucas (IMT Atlantique, Lab-STICC, UMR CNRS 6285, France) - Littaye Jean (UMR6523 Laboratoire d'Oceanographie Physique et Spatiale (LOPS), France) - Martinez Elodie (UMR6523 Laboratoire d'Oceanographie Physique et Spatiale (LOPS), France) (2022) . satellIte phytoplaNkton Drivers In the Global Ocean over 1998-2015 (INDIGO Benchmark dataset). https://services.mspdata.eu:/geonetwork/srv/api/records/seanoe:91910 |
Simple
- Date ( Publication )
- 2022-11
- Date ( Revision )
- 2023-03-24
- Other citation details
- Roussillon Joana, Fablet Ronan, Gorgues Thomas, Drumetz Lucas, Littaye Jean, Martinez Elodie (2022). satellIte phytoplaNkton Drivers In the Global Ocean over 1998-2015 (INDIGO Benchmark dataset). SEANOE. https://doi.org/10.17882/91910
Publisher
- Keywords ( Theme )
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- phytoplankton physical drivers , satellite ocean color , time-series regression , global scale , deep learning , benchmark , Biological oceanography , Physical oceanography
- ODATIS aggregation parameters and Essential Variable names ( Theme )
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- Phytoplankton , Ocean colour , Pigments
- SeaDataNet Parameter Disciplines ( parameter )
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- Biological oceanography , Physical oceanography
- Type de jeux de donnée ODATIS ( Theme )
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- Aggregate data
- Use constraints
- Other restrictions
- Other constraints
- Date ( Publication )
- 2023
Publisher
Author
Author
Author
Author
Author
Author
- Association Type
- Cross reference
- Initiative Type
- document
- Metadata language
- English
- Topic category
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- Oceans
- Distribution format
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- NUMPY ARRAY ( )
- OnLine resource
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Processed data
Normalized physical input data over 1998-2015 - 945 MB
- OnLine resource
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Processed data
Reference target satellite Chl over 1998-2015 - 105 MB
- OnLine resource
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Processed data
Reconstructed Chl over 2012-2015 test period - 23 MB
- OnLine resource
- DOI of the product
- OnLine resource
- Seanoe
- Hierarchy level
- Dataset
- Statement
Metadata
- File identifier
- seanoe:91910 XML
- Metadata language
- English
- Character set
- UTF8
- Hierarchy level
- Dataset
- Date stamp
- 2023-03-24
- Metadata standard name
- ISO 19115:2003/19139
- Metadata standard version
- 1.0
Metadata catalogue