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Article

Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake

1
Earth Observation and Modelling, Department of Geography, Christian-Albrechts-Universität zu Kiel, Ludewig-Meyn-Str. 14, Kiel D-24098, Germany
2
German Aerospace Center, Remote Sensing Technology Institute, Münchner Str. 20, Oberpfaffenhofen, Weßling D-82234, Germany
3
Remote Sensing Technology, Technische Universität München, Arcisstr. 21, München D-80333, Germany
4
German Aerospace Center, Remote Sensing Technology Institute, Rutherfordstr. 2, Berlin-Adlershof D-12489, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Clement Atzberger, Deepak R. Mishra and Pradad S. Thenkabail
Remote Sens. 2016, 8(11), 941; https://doi.org/10.3390/rs8110941
Received: 30 August 2016 / Revised: 17 October 2016 / Accepted: 3 November 2016 / Published: 11 November 2016
Satellite remote sensing may assist in meeting the needs of lake monitoring. In this study, we aim to evaluate the potential of Sentinel-2 to assess and monitor water constituents and bottom characteristics of lakes at spatio-temporal synoptic scales. In a field campaign at Lake Starnberg, Germany, we collected validation data concurrently to a Sentinel-2A (S2-A) overpass. We compared the results of three different atmospheric corrections, i.e., Sen2Cor, ACOLITE and MIP, with in situ reflectance measurements, whereof MIP performed best (r = 0.987, RMSE = 0.002 sr−1). Using the bio-optical modelling tool WASI-2D, we retrieved absorption by coloured dissolved organic matter (aCDOM(440)), backscattering and concentration of suspended particulate matter (SPM) in optically deep water; water depths, bottom substrates and aCDOM(440) were modelled in optically shallow water. In deep water, SPM and aCDOM(440) showed reasonable spatial patterns. Comparisons with in situ data (mean: 0.43 m−1) showed an underestimation of S2-A derived aCDOM(440) (mean: 0.14 m−1); S2-A backscattering of SPM was slightly higher than backscattering from in situ data (mean: 0.027 m−1 vs. 0.019 m−1). Chlorophyll-a concentrations (~1 mg·m−3) of the lake were too low for a retrieval. In shallow water, retrieved water depths exhibited a high correlation with echo sounding data (r = 0.95, residual standard deviation = 0.12 m) up to 2.5 m (Secchi disk depth: 4.2 m), though water depths were slightly underestimated (RMSE = 0.56 m). In deeper water, Sentinel-2A bands were incapable of allowing a WASI-2D based separation of macrophytes and sediment which led to erroneous water depths. Overall, the results encourage further research on lakes with varying optical properties and trophic states with Sentinel-2A. View Full-Text
Keywords: WASI; atmospheric correction; bathymetry; submerged vegetation; sun glint; water quality; validation; inland waters; inverse modelling WASI; atmospheric correction; bathymetry; submerged vegetation; sun glint; water quality; validation; inland waters; inverse modelling
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MDPI and ACS Style

Dörnhöfer, K.; Göritz, A.; Gege, P.; Pflug, B.; Oppelt, N. Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake. Remote Sens. 2016, 8, 941. https://doi.org/10.3390/rs8110941

AMA Style

Dörnhöfer K, Göritz A, Gege P, Pflug B, Oppelt N. Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake. Remote Sensing. 2016; 8(11):941. https://doi.org/10.3390/rs8110941

Chicago/Turabian Style

Dörnhöfer, Katja, Anna Göritz, Peter Gege, Bringfried Pflug, and Natascha Oppelt. 2016. "Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake" Remote Sensing 8, no. 11: 941. https://doi.org/10.3390/rs8110941

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