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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A three-step semi analytical algorithm (3SAA) for estimating inherent optical properties over oceanic, coastal, and inland waters from remote sensing reflectance

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Author(s):
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Jorge, Daniel S. F. [1] ; Loisel, Hubert [1] ; Jamet, Cedric [1] ; Dessailly, David [2] ; Demaria, Julien [3] ; Bricaud, Annick [4] ; Maritorena, Stephane [5] ; Zhang, Xiaodong [6] ; Antoine, David [4, 7] ; Kutser, Tiit [8] ; Belanger, Simon [9, 10] ; Brando, Vittorio O. [11] ; Werdell, Jeremy [12] ; Kwiatkowska, Ewa [2] ; Mangin, Antoine [3] ; D'Andon, Odile Fanton [3]
Total Authors: 16
Affiliation:
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[1] Univ Littoral Cote dOpale, CNRS, Univ Lille, UMR 8187, LOG Lab Oceanol & Geosci, F-62930 Wimereux - France
[2] EUMETSAT, Darmstadt - Germany
[3] ACRI ST, F-06904 Sophia Antipolis - France
[4] Sorbonne Univ, CNRS, Lab Oceanog Villefranche, LOV, Villefranche Sur Mer - France
[5] Univ Calif Santa Barbara, Earth Res Inst, Santa Barbara, CA 93106 - USA
[6] Univ Southern Mississippi, Sch Ocean Sci & Engn, Div Marine Sci, Stennis Space Ctr, MS 39529 - USA
[7] Curtin Univ, Sch Earth & Planetary Sci, Remote Sensing & Satellite Res Grp, Perth, WA 6845 - Australia
[8] Univ Tartu, Estonian Marine Inst, Tartu - Estonia
[9] Univ Quebec Rimouski, Dept Biol Chim & Geog, Rimouski, PQ - Canada
[10] Univ Quebec Rimouski, BOREAS, Rimouski, PQ - Canada
[11] Natl Res Council Italy CNR ISMAR, Inst Marine Sci, Rome - Italy
[12] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 - USA
Total Affiliations: 12
Document type: Journal article
Source: REMOTE SENSING OF ENVIRONMENT; v. 263, SEP 15 2021.
Web of Science Citations: 1
Abstract

We present a three-step inverse model (3SAA) for estimating the inherent optical properties (IOPs) of surface waters from the remote sensing reflectance spectra, Rrs(lambda). The derived IOPs include the total (a(lambda)), phytoplankton (aphy(lambda)), and colored detrital matter (acdm(lambda)), absorption coefficients, and the total (bb(lambda)) and particulate (bbp(lambda)) backscattering coefficients. The first step uses an improved neural network approach to estimate the diffuse attenuation coefficient of downwelling irradiance from Rrs. a(lambda) and bbp(lambda) are then estimated using the LS2 model (Loisel et al., 2018), which does not require spectral assumptions on IOPs and hence can assess a (lambda) and bb(lambda) at any wavelength at which Rrs(lambda) is measured. Then, an inverse optimization algorithm is combined with an optical water class (OWC) approach to assess aphy(lambda) and acdm(lambda) from anw(lambda).The proposed model is evaluated using an in situ dataset collected in open oceanic, coastal, and inland waters. Comparisons with other standard semi-analytical algorithms (QAA and GSM), as well as match-up exercises, have also been performed. The applicability of the algorithm on OLCI observations was assessed through the analysis of global IOPs spatial patterns derived from 3SAA and GSM. The good performance of 3SAA is manifested by median absolute percentage differences (MAPD) of 13%, 23%, 34% and 34% for bbp(443), anw(443), aphy(443) and acdm(443), respectively for oceanic waters. Due to the absence of spectral constraints on IOPs in the inversion of total IOPs, and the adoption of an OWC-based approach, the performance of 3SAA is only slightly degraded in bio-optical complex inland waters. (AU)

FAPESP's process: 14/23903-9 - Bio-optical spatio-temporal characterization and development of analytical algorithms for the systematic monitoring of water masses circulating on the floodplain of medium and lower Amazon
Grantee:Cláudio Clemente Faria Barbosa
Support type: Regular Research Grants