A neural network approach to the estimation of in-water attenuation to absorption ratios from PACE mission measurements

Agagliate, J.; Foster, R.; Ibrahim, A.; Gilerson, A.

doi:10.3389/frsen.2023.1060908

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A neural network approach to the estimation of in-water attenuation to absorption ratios from PACE mission measurements

2023
By Agagliate, J. ; Foster, R. ; Ibrahim, A. ; ...
Source: Front. Remote Sens. 4:1060908

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Journal Title:

Frontiers in Remote Sensing
Personal Author:

Agagliate, J. ; Foster, R. ; Ibrahim, A. ; Gilerson, A.

Agagliate, J. ; Foster, R. ; Ibrahim, A. ; Gilerson, A. Less -
NOAA Program & Office:

NESDIS (National Environmental Satellite, Data, and Information Service) ; JPSS (Joint Polar Satellite System Program Office) ; CESSRST (Cooperative Science Center for Earth System Sciences and Remote Sensing Technologies)

NESDIS (National Environmental Satellite, Data, and Information Service) ; JPSS (Joint Polar Satellite System Program Office) ; CESSRST (Cooperative Science Center for Earth System Sciences and Remote Sensing Technologies) Less -
Description:

In preparation for the upcoming PACE mission, we explore the feasibility of a neural network-based approach for the conversion of measurements of the degree of linear polarization at the top of the atmosphere as carried out by the HARP2 instrument into estimations of the ratio of attenuation to absorption in the surface layer of the ocean. Polarization has been shown to contain information on the in-water inherent optical properties including the total attenuation coefficient, in contrast with approaches solely based on remote sensing reflectance that are limited to the backscattered fraction of the scattering. In turn, these properties may be further combined with inversion algorithms to retrieve projected values for the optical and physical properties of marine particulates.
Keywords:

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Neural Networks (Computer Science) Ocean Color Polarization (Light) Remote Sensing Inherent Optical Properties (IOPs) Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE)
Source:

Front. Remote Sens. 4:1060908
DOI:

https://doi.org/10.3389/frsen.2023.1060908
Format:

PDF
Document Type:

Journal Article
Funding:

Grant no. NA16SEC4810008
License:

https://creativecommons.org/licenses/by/4.0/
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CC BY
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Submitted
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urn:sha256:70e5b8e8389a8139f621898b7767c2c7c528d195af386f60c2d566bfe19a7e93
Download URL:

https://repository.library.noaa.gov/view/noaa/55986/noaa_55986_DS1.pdf
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