View in EDS

Inversion of satellite ocean colour imagery and geoacoustic characterization of seabed properties: Variational data inversion using a semi-automatic adjoint approach

Saved in:
Bibliographic Details
Title: Inversion of satellite ocean colour imagery and geoacoustic characterization of seabed properties: Variational data inversion using a semi-automatic adjoint approach
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
Description
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]
ISSN:09247963
DOI:10.1016/j.jmarsys.2007.02.018