Aquatic reflectance derived from Sentinel‐2 Multispectral Imager data for inland waters in the conterminous United States

Abstract Satellite‐based earth observation is a robust tool for tracking change in ecosystems. While terrestrially focused applications of remote sensing have empowered wide adoption for research and management, remote sensing of inland aquatic ecosystems remains comparably nascent. This divergence, in part, stems from the lack of standardized, accessible, and near real‐time remotely sensed surface reflectance, atmospherically corrected for aquatic environments. To date, surface reflectance products at national scales and with minimal latency are typically designed exclusively for terrestrial environments. Rectifying this situation can be accomplished by applying aquatic‐focused atmospheric correction algorithms independent of those used for terrestrial ecosystems. As a first step to filling this data gap, we present the first national scale, dynamically updated, analysis‐ready, aquatic reflectance dataset for inland water derived from Sentinel‐2 for the conterminous United States.

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Publication Details

Journal
Limnology and Oceanography Letters
Published
2026-02-22
DOI
https://doi.org/10.1002/lol2.70112
Primary Topic
Marine and coastal ecosystems
Type
article
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article

Aquatic reflectance derived from Sentinel‐2 Multispectral Imager data for inland waters in the conterminous United States

Grady Ball, Stephen A. Hundt, Konrad C. Hafen, Tyler King et al.
Limnology and Oceanography Letters
Marine and coastal ecosystems
article

Aquatic reflectance derived from Sentinel‐2 Multispectral Imager data for inland waters in the conterminous United States

Grady Ball, Stephen A. Hundt, Konrad C. Hafen, Tyler King, Scott D. Ducar, Quinten Vanhellemont, Victoria Stengel, Dulcinea Avouris, Michael F. Meyer, Brendan F. Wakefield
article en

Abstract

Abstract Satellite‐based earth observation is a robust tool for tracking change in ecosystems. While terrestrially focused applications of remote sensing have empowered wide adoption for research and management, remote sensing of inland aquatic ecosystems remains comparably nascent. This divergence, in part, stems from the lack of standardized, accessible, and near real‐time remotely sensed surface reflectance, atmospherically corrected for aquatic environments. To date, surface reflectance products at national scales and with minimal latency are typically designed exclusively for terrestrial environments. Rectifying this situation can be accomplished by applying aquatic‐focused atmospheric correction algorithms independent of those used for terrestrial ecosystems. As a first step to filling this data gap, we present the first national scale, dynamically updated, analysis‐ready, aquatic reflectance dataset for inland water derived from Sentinel‐2 for the conterminous United States.

Limnology and Oceanography LettersVol. 11(2)
United States Geological Survey (US), Institute of Natural Sciences (BE), California Water Science Center, Oregon Water Science Center
Openalex Percentile: Top 54%
Marine and coastal ecosystems
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