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ACIX-Aqua: A Global Assessment of Atmospheric Correction Methods for Landsat-8 and Sentinel-2 Over Lakes, Rivers, and Coastal WatersAtmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances (ρ̂w). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in ρ̂w560 and ρ̂w664 were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15–30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20–30% uncertainties in ρ̂w490≤λ≤743nm yielded 25–70% uncertainties in derived Chla and TSS products for top-performing AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems.
Document ID
20210011543
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Nima Pahlevan
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Antoine Mangin
(ACRI-ST)
Sundarabalan V. Balasubramanian
(Geosensing and Imaging Solution Consultancy)
Brandon Smith
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Krista Alikas
(University of Tartu Tartu, Estonia)
Kohei Arai
(Saga University Saga, Japan)
Claudio Barbosa
(National Institute for Space Research São José dos Campos, Brazil)
Simon Bélanger
(University of Quebec Québec, Quebec, Canada)
Caren Binding
(Environment and Climate Change Canada)
Mariano Bresciani
(National Research Council of Italy)
Claudia Giardino
(National Research Council of Italy)
Daniela Gurlin
(Wisconsin Department of Natural Resources Madison, Wisconsin, United States)
Yongzhen Fan
(Stevens Institute of Technology Hoboken, New Jersey, United States)
Tristan Harmel
(Géosciences Environnement Toulouse Toulouse, France)
Peter Hunter
(University of Stirling Stirling, Stirling, United Kingdom)
Joji Ishikaza
(Nagoya University Nagoya, Japan)
Susanne Kratzer
(Stockholm University Stockholm, Sweden)
Moritz K. Lehmann
(University of Waikato Hamilton, New Zealand)
Martin Ligi
(University of Tartu Tartu, Estonia)
Ronghua Ma
(Nanjing Institute of Geography and Limnology Nanjing, China)
François-Régis Martin-Lauzer
(ACRI-ST)
Leif Olmanson
(University of Minnesota Minneapolis, Minnesota, United States)
Natascha Oppelt
(Kiel University Kiel, Germany)
Yanqun Pan
(University of Quebec Québec, Quebec, Canada)
Steef Peters
(Water Insight (Netherlands) Wageningen, Netherlands)
Nathalie Reynaud
(UR RECOVER)
Lino A. Sander de Carvalho
(Federal University of Rio de Janeiro Rio de Janeiro, Brazil)
Stefan Simis
(Plymouth Marine Laboratory Plymouth, United Kingdom)
Evangelos Spyrakos
(University of Stirling Stirling, Stirling, United Kingdom)
François Steinmetz
(Hygeos)
Kerstin Stelzera
(Brockmann Consult GmbH)
Sindy Sterckx
(Flemish Institute for Technological Research Mol, Belgium)
Thierry Tormos
(Unité ECosystèmes LAcustres)
Andrew Tyler
(University of Stirling Stirling, Stirling, United Kingdom)
Quinten Vanhellemont
(Royal Belgian Institute of Natural Sciences Brussels, Belgium)
Mark Warren
(Plymouth Marine Laboratory Plymouth, United Kingdom)
Date Acquired
March 18, 2021
Publication Date
March 9, 2021
Publication Information
Publication: Remote Sensing of Environment
Publisher: Elsevier
Volume: 258
Issue Publication Date: June 1, 2021
ISSN: 0034-4257
URL: https://www.sciencedirect.com/science/article/pii/S0034425721000845?via%3Dihub
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: 80HQTR19C0015
CONTRACT_GRANT: 80GSFC20C0044
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
Professional Review
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