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Journal Article

The Use of Sentinel-2 for Chlorophyll-a Spatial Dynamics Assessment: A Comparative Study on Different Lakes in Northern Germany

Authors

Ogashawara,  Igor
External Organizations;

Kiel,  Christine
External Organizations;

/persons/resource/jechow

Jechow,  Andreas
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/kkohn

Kohnert,  Katrin
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Ruhtz,  Thomas
External Organizations;

Grossart,  Hans-Peter
External Organizations;

Hölker,  Franz
External Organizations;

Nejstgaard,  Jens C.
External Organizations;

Berger,  Stella A.
External Organizations;

Wollrab,  Sabine
External Organizations;

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Fulltext (public)

5007298.pdf
(Publisher version), 5MB

Supplementary Material (public)
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Citation

Ogashawara, I., Kiel, C., Jechow, A., Kohnert, K., Ruhtz, T., Grossart, H.-P., Hölker, F., Nejstgaard, J. C., Berger, S. A., Wollrab, S. (2021): The Use of Sentinel-2 for Chlorophyll-a Spatial Dynamics Assessment: A Comparative Study on Different Lakes in Northern Germany. - Remote Sensing, 13, 8, 1542.
https://doi.org/10.3390/rs13081542


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5007298
Abstract
Eutrophication of inland waters is an environmental issue that is becoming more common with climatic variability. Monitoring of this aquatic problem is commonly based on the chlorophyll-a concentration monitored by routine sampling with limited temporal and spatial coverage. Remote sensing data can be used to improve monitoring, especially after the launch of the MultiSpectral Instrument (MSI) on Sentinel-2. In this study, we compared the estimation of chlorophyll-a (chl-a) from different bio-optical algorithms using hyperspectral proximal remote sensing measurements, from simulated MSI responses and from an MSI image. For the satellite image, we also compare different atmospheric corrections routines before the comparison of different bio-optical algorithms. We used in situ data collected in 2019 from 97 sampling points across 19 different lakes. The atmospheric correction assessment showed that the performances of the routines varied for each spectral band. Therefore, we selected C2X, which performed best for bands 4 (root mean square error—RMSE = 0.003), 5 (RMSE = 0.004) and 6 (RMSE = 0.002), which are usually used for the estimation of chl-a. Considering all samples from the 19 lakes, the best performing chl-a algorithm and calibration achieved a RMSE of 16.97 mg/m3. When we consider only one lake chain composed of meso-to-eutrophic lakes, the performance improved (RMSE: 10.97 mg/m3). This shows that for the studied meso-to-eutrophic waters, we can reliably estimate chl-a concentration, whereas for oligotrophic waters, further research is needed. The assessment of chl-a from space allows us to assess spatial dynamics of the environment, which can be important for the management of water resources. However, to have an accurate product, similar optical water types are important for the overall performance of the bio-optical algorithm.