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      Validation and Comparison of Water Quality Products in Baltic Lakes Using Sentinel-2 MSI and Sentinel-3 OLCI Data

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          Abstract

          Inland waters, including lakes, are one of the key points of the carbon cycle. Using remote sensing data in lake monitoring has advantages in both temporal and spatial coverage over traditional in-situ methods that are time consuming and expensive. In this study, we compared two sensors on different Copernicus satellites: Multispectral Instrument (MSI) on Sentinel-2 and Ocean and Land Color Instrument (OLCI) on Sentinel-3 to validate several processors and methods to derive water quality products with best performing atmospheric correction processor applied. For validation we used in-situ data from 49 sampling points across four different lakes, collected during 2018. Level-2 optical water quality products, such as chlorophyll-a and the total suspended matter concentrations, water transparency, and the absorption coefficient of the colored dissolved organic matter were compared against in-situ data. Along with the water quality products, the optical water types were obtained, because in lakes one-method-to-all approach is not working well due to the optical complexity of the inland waters. The dynamics of the optical water types of the two sensors were generally in agreement. In most cases, the band ratio algorithms for both sensors with optical water type guidance gave the best results. The best algorithms to obtain the Level-2 water quality products were different for MSI and OLCI. MSI always outperformed OLCI, with R 2 0.84–0.97 for different water quality products. Deriving the water quality parameters with optical water type classification should be the first step in estimating the ecological status of the lakes with remote sensing.

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          Lakes and reservoirs as sentinels, integrators, and regulators of climate change

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            A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: Validation

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              • Record: found
              • Abstract: not found
              • Article: not found

              Remote sensing of inland waters: Challenges, progress and future directions

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                29 January 2020
                February 2020
                : 20
                : 3
                : 742
                Affiliations
                [1 ]Institute for Environmental Solutions, Lidlauks, LV-4101 Priekuļu Parish, Latvia; dainis.jakovels@ 123456videsinstituts.lv (D.J.); agris.brauns@ 123456videsinstituts.lv (A.B.); matiss.zagars@ 123456videsinstituts.lv (M.Z.)
                [2 ]Tartu Observatory, University of Tartu, Observatooriumi 1, 61602 Tõravere, Estonia; kristi.uudeberg@ 123456ut.ee
                [3 ]Estonian Marine Institute, University of Tartu, Mäealuse 14, 12618 Tallinn, Estonia; tiit.kutser@ 123456ut.ee
                Author notes
                Author information
                https://orcid.org/0000-0002-3297-6652
                https://orcid.org/0000-0002-2969-5972
                https://orcid.org/0000-0001-8011-3125
                Article
                sensors-20-00742
                10.3390/s20030742
                7038399
                32013214
                2057523f-e430-4da3-9431-da6e61e4949f
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 December 2019
                : 27 January 2020
                Categories
                Article

                Biomedical engineering
                water quality,optical properties,lakes,optically complex waters,remote sensing,sentinel-2,sentinel-3,msi,olci,optical water types

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