Assessment of Atmospheric Correction Algorithms for Sentinel-3 OLCI in the Amazon River Continuum-Reference-Cited by-同舟云学术

Assessment of Atmospheric Correction Algorithms for Sentinel-3 OLCI in the Amazon River Continuum

Published:2024-07-20 Issue:14 Volume:16 Page:2663
ISSN:2072-4292
Container-title:Remote Sensing
language:en
Short-container-title:Remote Sensing

Author:

Valerio Aline M.¹²^ORCID,Kampel Milton¹^ORCID,Vantrepotte Vincent³⁴,Ballester Victoria²,Richey Jeffrey⁵^ORCID

Affiliation:

1. Monitoring Oceans from Space Laboratory, Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São José dos Campos 12227-010, SP, Brazil

2. Center for Nuclear Energy in Agriculture, São Paulo University (CENA-USP), Piracicaba 13400-970, SP, Brazil

3. Institut de Recherche et Développement (IRD), Centre National de la Recherche Scientifique (CNRS), Université Lille, Université Littoral Côte d’Opale (ULCO), UMR 8187, Laboratoire d’Océanologie et de Géosciences (LOG), 59000 32 Avenue Foch, 62930 Wimereux, France

4. Tropical Atlantic Interdisciplinary Laboratory on Physical, Biogeochemical, Ecological and Human Dynamics (IJL TAPIOCA), Departamento de Oceanografia, Universidade Federal de Pernambuco, Avenida Arquitetura, S/N, Recife 50670-901, PE, Brazil

5. School of Oceanography, University of Washington (UW), Seattle, WA 98195, USA

Abstract

Water colour remote sensing is a valuable tool for assessing bio-optical and biogeochemical parameters across the vast extent of the Amazon River Continuum (ARC). However, accurate retrieval depends on selecting the best atmospheric correction (AC). Four AC processors (Acolite, Polymer, C2RCC, OC-SMART) were evaluated against in situ remote sensing reflectance (Rrs) measurements. K-means classification identified four optical water types (OWTs) that are affected by the ARC. Two OWTs showed seasonal differences in the Lower Amazon River, influenced by the increase in suspended sediment concentration with river discharge. The other OWTs in the Amazon River Plume are dominated by phytoplankton or by a mixture of optically significant constituents. The Quality Water Index Polynomial method used to assess the quality of in situ and orbital Rrs had a high failure rate when the Apparent Visible Wavelength was >580 nm for in situ Rrs. OC-SMART Rrs products showed better spectral quality compared to Rrs derived from other AC processors evaluated in this study. These results improve our understanding of remotely sensing very turbid waters, such as those in the Amazon River Continuum.

Funder

São Paulo Research Foundation

U.S. National Science Foundation

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil

Agência Espacial Brasileira (AEB) and Instituto Nacional de Pesquisas Espaciais

Publisher

MDPI AG

Link

https://www.mdpi.com/2072-4292/16/14/2663/pdf

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