Inversion of satellite ocean colour imagery and geoacoustic characterization of seabed properties: Variational data inversion using a semi-automatic adjoint approach
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| Title: | Inversion of satellite ocean colour imagery and geoacoustic characterization of seabed properties: Variational data inversion using a semi-automatic adjoint approach |
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| Authors: | Badran, F.1, Berrada, M.1, Brajard, J.1, Crépon, M.1, Sorror, C.1, Thiria, S.1, Hermand, J.-P.2 jean-pierre.hermand@ulb.ac.be, Meyer, M.2, Perichon, L.2, Asch, M.3 |
| Source: | Journal of Marine Systems. Jan2008, Vol. 69 Issue 1/2, p126-136. 11p. |
| Subjects: | Optical oceanography, Ocean bottom, Ocean, Speed of sound |
| Abstract: | Abstract: In this paper a semi-automatic adjoint approach for variational data inversion is proposed. To demonstrate the effectiveness of the approach two illustrative examples are presented: the geoacoustic characterization of a Mediterranean shallow water environment using realistic experimental conditions and the estimation of oceanic and atmospheric constituents from satellite ocean colour imagery. In the first case geoacoustic parameters of the seabed (density, sound speed and attenuation) are determined from long/medium range underwater acoustic propagation data in the water column. In the second case the aerosol optical thickness in the atmosphere and the phytoplankton concentration in the ocean (chlorophyll-a) are estimated from solar reflectance measurements obtained with ocean colour sensors on board satellites. The general methodology for both applications is based on a modular graph concept that allows a straightforward adjoint computation by means of gradient backpropagation. Generation and coding of the adjoint models in both cases are accomplished with an algorithmic tool. [Copyright &y& Elsevier] |
| Copyright of Journal of Marine Systems is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 27667608 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Inversion of satellite ocean colour imagery and geoacoustic characterization of seabed properties: Variational data inversion using a semi-automatic adjoint approach – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Badran%2C+F%2E%22">Badran, F.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Berrada%2C+M%2E%22">Berrada, M.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Brajard%2C+J%2E%22">Brajard, J.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Crépon%2C+M%2E%22">Crépon, M.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Sorror%2C+C%2E%22">Sorror, C.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Thiria%2C+S%2E%22">Thiria, S.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Hermand%2C+J%2E-P%2E%22">Hermand, J.-P.</searchLink><relatesTo>2</relatesTo><i> jean-pierre.hermand@ulb.ac.be</i><br /><searchLink fieldCode="AR" term="%22Meyer%2C+M%2E%22">Meyer, M.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Perichon%2C+L%2E%22">Perichon, L.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Asch%2C+M%2E%22">Asch, M.</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Marine+Systems%22">Journal of Marine Systems</searchLink>. Jan2008, Vol. 69 Issue 1/2, p126-136. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Optical+oceanography%22">Optical oceanography</searchLink><br /><searchLink fieldCode="DE" term="%22Ocean+bottom%22">Ocean bottom</searchLink><br /><searchLink fieldCode="DE" term="%22Ocean%22">Ocean</searchLink><br /><searchLink fieldCode="DE" term="%22Speed+of+sound%22">Speed of sound</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: In this paper a semi-automatic adjoint approach for variational data inversion is proposed. To demonstrate the effectiveness of the approach two illustrative examples are presented: the geoacoustic characterization of a Mediterranean shallow water environment using realistic experimental conditions and the estimation of oceanic and atmospheric constituents from satellite ocean colour imagery. In the first case geoacoustic parameters of the seabed (density, sound speed and attenuation) are determined from long/medium range underwater acoustic propagation data in the water column. In the second case the aerosol optical thickness in the atmosphere and the phytoplankton concentration in the ocean (chlorophyll-a) are estimated from solar reflectance measurements obtained with ocean colour sensors on board satellites. The general methodology for both applications is based on a modular graph concept that allows a straightforward adjoint computation by means of gradient backpropagation. Generation and coding of the adjoint models in both cases are accomplished with an algorithmic tool. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Marine Systems is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.jmarsys.2007.02.018 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 126 Subjects: – SubjectFull: Optical oceanography Type: general – SubjectFull: Ocean bottom Type: general – SubjectFull: Ocean Type: general – SubjectFull: Speed of sound Type: general Titles: – TitleFull: Inversion of satellite ocean colour imagery and geoacoustic characterization of seabed properties: Variational data inversion using a semi-automatic adjoint approach Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Badran, F. – PersonEntity: Name: NameFull: Berrada, M. – PersonEntity: Name: NameFull: Brajard, J. – PersonEntity: Name: NameFull: Crépon, M. – PersonEntity: Name: NameFull: Sorror, C. – PersonEntity: Name: NameFull: Thiria, S. – PersonEntity: Name: NameFull: Hermand, J.-P. – PersonEntity: Name: NameFull: Meyer, M. – PersonEntity: Name: NameFull: Perichon, L. – PersonEntity: Name: NameFull: Asch, M. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2008 Type: published Y: 2008 Identifiers: – Type: issn-print Value: 09247963 Numbering: – Type: volume Value: 69 – Type: issue Value: 1/2 Titles: – TitleFull: Journal of Marine Systems Type: main |
| ResultId | 1 |
