Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence
The similarity of mesoscale and submesoscale features observed in different ocean scalars indicates that they undergo some common non-linear processes. As a result of quasi-2D turbulence, complicated patterns of filaments, meanders, and eddies are recognized in remote sensing images. A data fusion m...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/7/1153 |
| _version_ | 1797571441715052544 |
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| author | Marta Umbert Sebastien Guimbard Joaquim Ballabrera Poy Antonio Turiel |
| author_facet | Marta Umbert Sebastien Guimbard Joaquim Ballabrera Poy Antonio Turiel |
| author_sort | Marta Umbert |
| collection | DOAJ |
| description | The similarity of mesoscale and submesoscale features observed in different ocean scalars indicates that they undergo some common non-linear processes. As a result of quasi-2D turbulence, complicated patterns of filaments, meanders, and eddies are recognized in remote sensing images. A data fusion method used to improve the quality of one ocean variable using another variable as a template is used here as an extrapolation technique to improve the coverage of daily Aqua MODIS Level-3 chlorophyll maps by using MODIS SST maps as a template. The local correspondence of SST and Chl-a multifractal singularities is granted due to the existence of a common cascade process which makes it possible to use SST data to infer Chl-a concentration where data are lacking. The quality of the inference of Level-4 Chl-a maps is assessed by simulating artificial clouds and comparing reconstructed and original data. |
| first_indexed | 2024-03-10T20:40:43Z |
| format | Article |
| id | doaj.art-1c7a023021684c23a6e5dd9b23dd0df7 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T20:40:43Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-1c7a023021684c23a6e5dd9b23dd0df72023-11-19T20:41:01ZengMDPI AGRemote Sensing2072-42922020-04-01127115310.3390/rs12071153Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration CoherenceMarta Umbert0Sebastien Guimbard1Joaquim Ballabrera Poy2Antonio Turiel3Departament of Physical and Technological Oceanography, Institut de Ciències del Mar, CSIC, 08003 Barcelona, SpainOcean Scope, Plouzané, 29280 Brest, FranceDepartament of Physical and Technological Oceanography, Institut de Ciències del Mar, CSIC, 08003 Barcelona, SpainDepartament of Physical and Technological Oceanography, Institut de Ciències del Mar, CSIC, 08003 Barcelona, SpainThe similarity of mesoscale and submesoscale features observed in different ocean scalars indicates that they undergo some common non-linear processes. As a result of quasi-2D turbulence, complicated patterns of filaments, meanders, and eddies are recognized in remote sensing images. A data fusion method used to improve the quality of one ocean variable using another variable as a template is used here as an extrapolation technique to improve the coverage of daily Aqua MODIS Level-3 chlorophyll maps by using MODIS SST maps as a template. The local correspondence of SST and Chl-a multifractal singularities is granted due to the existence of a common cascade process which makes it possible to use SST data to infer Chl-a concentration where data are lacking. The quality of the inference of Level-4 Chl-a maps is assessed by simulating artificial clouds and comparing reconstructed and original data.https://www.mdpi.com/2072-4292/12/7/1153remote sensingocean colordata fusiondata mergingphysical oceanographysingularity analysis |
| spellingShingle | Marta Umbert Sebastien Guimbard Joaquim Ballabrera Poy Antonio Turiel Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence Remote Sensing remote sensing ocean color data fusion data merging physical oceanography singularity analysis |
| title | Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence |
| title_full | Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence |
| title_fullStr | Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence |
| title_full_unstemmed | Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence |
| title_short | Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence |
| title_sort | synergy between ocean variables remotely sensed surface temperature and chlorophyll concentration coherence |
| topic | remote sensing ocean color data fusion data merging physical oceanography singularity analysis |
| url | https://www.mdpi.com/2072-4292/12/7/1153 |
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