High resolution suspended particulate matter maps generated from landsat-8/OLI and sentinel-2/MSI data in the gironde estuary

Gironde estuary environmental parameters and SPM maps generated from 41 Landsat-8/OLI and Sentinel-2/MSI images acquired over the period 2013-2018. Except bathymetry and daily river discharge data, that are accessible on public platforms, the dataset includes all of the time seris used in the publication: Analysis of suspended sediment variability in a large highly-turbid estuary using a 5-year-long remotely-sensed data archive at high resolution, Journal of Geophysical Research: Oceans, DOI:10.1029/2019JC015417.
 
Citation proposal
NORMANDIN Cassandra (University of Bordeaux, UMR 5805 EPOC, Allée Geoffroy St Hilaire, Pessac, FRANCE) - LUBAC Bertrand (University of Bordeaux, UMR 5805 EPOC, Allée Geoffroy St Hilaire, Pessac, FRANCE) - SOTTOLICHIO Aldo (University of Bordeaux, UMR 5805 EPOC, Allée Geoffroy St Hilaire, Pessac, FRANCE) - FRAPPART Frederic (Université de Toulouse, CNES, CNRS, IRD, UPS, Observatoire Midi Pyrénées, LEGOS, 14 Avenue Edouard Belin, 31400 Toulouse, FRANCE) - YGORRA Bertrand (University of Bordeaux, UMR 5805 EPOC, Allée Geoffroy St Hilaire, Pessac, FRANCE) - MARIEU Vincent (University of Bordeaux, UMR 5805 EPOC, Allée Geoffroy St Hilaire, Pessac, FRANCE) (2019) . High resolution suspended particulate matter maps generated from landsat-8/OLI and sentinel-2/MSI data in the gironde estuary. https://services.mspdata.eu:/geonetwork/srv/api/records/seanoe:62691

Simple

Date ( Publication )
2019-09-25
Date ( Revision )
2021-05-12
Other citation details

Normandin Cassandra, Lubac Bertrand, Sottolichio Aldo, Frappart Frederic, Ygorra Bertrand, Marieu Vincent (2019). High resolution suspended particulate matter maps generated from landsat-8/OLI and sentinel-2/MSI data in the gironde estuary. SEANOE. https://doi.org/10.17882/62691

In addition to properly cite this dataset, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :

Normandin C., Lubac B., Sottolichio A., Frappart F., Ygorra B., Marieu V. (2019). Analysis of suspended sediment variability in a large highly‐turbid estuary using a 5‐year‐long remotely‐sensed data archive at high resolution. Journal of Geophysical Research: Oceans, -. https://doi.org/10.1029/2019JC015417

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Keywords ( Theme )
  • Gironde esturay , Ocean color , Landsat-8/OLI , Sentinel-2/OLI , SPM , PCA , Physical oceanography
ODATIS aggregation parameters and Essential Variable names ( Theme )
  • Suspended matter , Sedimentary fluxes
SeaDataNet Parameter Disciplines ( parameter )
  • Physical oceanography
Centre de données ODATIS ( Theme )
  • CDS-IS-OMP
Type de jeux de donnée ODATIS ( Theme )
  • Observational data
Use constraints
Other restrictions
Other constraints
Date ( Publication )
2019

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Association Type
Cross reference
Initiative Type
document
Metadata language
English
Topic category
  • Oceans
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Distribution format
  • CSV ( )

OnLine resource
Processed data  

Gironde estuary SPM maps generated from Landsat-8/OLI and Sentinel-2/MSI data - 134 MB

OnLine resource
Processed data  

Environmental parameters associated with Landat-8/OLI and Sentinel-2/MSI images - 5 KB

OnLine resource
DOI of the product  
OnLine resource
Seanoe  
Hierarchy level
Dataset
Statement
A full description of sensors and methods used to generate the dataset can be found in the publication: Analysis of suspended sediment variability in a large highly-turbid estuary using a 5-year-long remotely-sensed data archive at high resolution, Journal of Geophysical Research: Oceans, DOI:10.1029/2019JC015417.

Metadata

File identifier
seanoe:62691   XML
Metadata language
English
Character set
UTF8
Hierarchy level
Dataset
Date stamp
2021-05-12
Metadata standard name
ISO 19115:2003/19139
Metadata standard version
1.0

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  Overviews

T_mode PCA applied to 41 Gironde estuary SPM maps generated from Landsat-8/OLI and Sentinel-2/MSI data over the period 2013-2018. First (a), second (b), and third (c) principal components explaining 43.5%, 15.0%, and 7.2% of the total variance, respectively. Component scores are normalized and vary between -1 and +1.

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