研究目的
To test the suitability of Sentinel-2 MultiSpectral Instrument data to monitor water quality in inland waters, specifically for estimating chlorophyll a concentrations and ecological status as required by the EU Water Framework Directive.
研究成果
Sentinel-2 MSI is suitable for estimating chlorophyll a and tracking dynamics in lakes, providing complementary data for WFD monitoring. C2RCC was the most effective atmospheric correction processor, but improvements are needed for small lakes. Empirical algorithms like Three-Band NIR-Red Model and MCI showed good results, but further development is required for optically complex waters.
研究不足
Atmospheric corrections are sensitive to surrounding land and often fail in narrow and small lakes due to adjacency effects. High CDOM absorption can cause processors to fail in deriving accurate ρw. The study is limited to Estonian lakes and specific time periods (2015-2017), and more validation data is needed for broader applicability.
1：Experimental Design and Method Selection:
The study involved comparing atmospheric correction processors (ACOLITE, C2RCC, POLYMER, Sen2Cor) to derive water-leaving reflectance (ρw) from Sentinel-2 MSI data, and testing and developing empirical chlorophyll a algorithms adapted to MSI bands.
2：Sample Selection and Data Sources:
In situ data included radiometric measurements from Estonian lakes (13 match-up points for validation), a global dataset (GLaSS) for algorithm development, and chlorophyll a data from the Estonian National Monitoring database for time series analysis.
3：List of Experimental Equipment and Materials:
RAMSES TriOS radiometers for in situ measurements, Sentinel-2 MSI Level-1C images, SNAP software, and various atmospheric correction processors.
4：Experimental Procedures and Operational Workflow:
Downloaded S2 MSI images, applied atmospheric correction processors, resampled bands to 60 m, used quality flags, and applied statistical analysis (R2, ψ, Δ, δ, S, I) to compare derived and in situ ρw. Algorithms were tested on in situ and satellite data.
5：Data Analysis Methods:
Statistical methods included coefficient of determination, average absolute percentage difference, root-mean-square difference, bias, slope, and intercept. Algorithms were evaluated based on correlation with in situ chlorophyll a.
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Hitachi U-3010 spectrophotometer
U-3010
Hitachi
Measure chlorophyll a concentrations spectrophotometrically.
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RAMSES TriOS radiometers
TriOS
Measure upwelling radiance, downwelling radiance, and downwelling irradiance for in situ radiometric measurements.
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Sentinel-2 MultiSpectral Instrument
MSI
European Space Agency
Satellite sensor measuring in 13 spectral bands for remote sensing of water quality.
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SNAP software
v5
Brockmann Consult, Array Systems Computing and Communication, Systémes (C-S)
Toolbox for processing Sentinel mission data, including atmospheric correction and resampling.
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ACOLITE processor
v20180925.0
Atmospheric correction processor for coastal and inland waters.
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C2RCC processor
v0.15
Case 2 Regional CoastColour processor for optically complex waters using neural networks.
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POLYMER processor
v1.1
Polynomial-based algorithm for atmospheric correction, originally for MERIS data.
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Sen2Cor processor
v2.1.2
Atmospheric correction processor for Sentinel-2 data, designed for vegetation applications.
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Whatman GF/F filters
GF/F ? 25 mm
Whatman
Filtering water samples for chlorophyll a measurement.
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