Bio-optical characterization of the Salish Sea, Canada, towards improved chlorophyll algorithms for MODIS and Sentinel-3
Date
2015-12-22
Authors
Phillips, Stephen Robert
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Abstract
The goal of this research was to improve ocean colour chlorophyll a (Chla) retrievals in the coastal Case 2 waters of the Salish Sea by characterizing the main drivers of optical variability and using this information to parameterize empirical algorithms based on an optical classification. This was addressed with three specific objectives: (1) build a comprehensive spatio-temporal data set of in situ optical and biogeochemical parameters, (2) apply a hierarchical clustering analysis to classify above-water remote sensing reflectance (Rrs) and associated bio-optical regimes, (3) optimize and validate class-specific empirical algorithms for improved Chla retrievals.
Biogeochemical and optical measurements, acquired at 145 sites, showed considerable variation; Chla (mean=1.64, range: 0.10 – 7.20 µg l-1), total suspended matter (TSM) (3.09, 0.82 – 20.69 mg l-1), and absorption by chromophoric dissolved organic matter (a_cdom (443)) (0.525, 0.007 – 3.072 m-1), thus representing the spatial and temporal variability of the Salish Sea. A comparable range was found in the measured optical properties; particulate scattering (b_p (650)) (1.316, 0.250 – 7.450 m-1), particulate backscattering (b_bp (650)) (0.022, 0.005 – 0.097 m-1), total beam attenuation coefficient (c_t (650)) (1.675, 0.371 – 9.537 m-1), and particulate absorption coefficient (a_p (650)) (0.345, 0.048 – 2.020 m-1). Empirical orthogonal function (EOF) analysis revealed 95% of the Rrs variance was highly correlated to b_p (r = 0.90), b_bp (r = 0.82), and TSM concentration (r = 0.80), suggesting a strong influence from riverine systems in this region. Hierarchical clustering on the normalized Rrs revealed four spectral classes. Class 1 is defined by high overall Rrs magnitudes in the red, indicating more turbid waters, Class 2 showed high Rrs values in the red and well defined fluorescence and absorption features, indicated by a high Chla and TSM presence, Class 3 showed low TSM influence and more defined Chla signatures, and Class 4 is characterized by overall low Rrs values, suggesting more optically clear oceanic waters. Spectral similarities justified a simplification of this classification into two dominant water classes – (1) estuarine class (Classes 1 and 2) and (2) oceanic class (Classes 3 and 4) – representing the dominant influences seen here.
In situ Chla and above-water remote sensing reflectance measurements, used to validate and parameterize the OC3M/OC3S3, two-band ratio, FLH and, modified FLH (ModFLH) empirical algorithms, showed a systematic overestimation of low Chla concentrations and underestimation of higher Chla values for all four algorithms when tuned to regional data. FLH and ModFLH algorithms performed best for these data (R2 ~ 0.40; RMSE ~ 0.32). Algorithm accuracy was significantly improved for the class-specific parametrizations with the two-band ratio showing a strong correlation to the Chla concentrations in the estuarine class (R2 ~ 0.71; RMSE ~ 0.33) and the ModFLH algorithm in the oceanic class (R2 ~ 0.70; RMSE ~ 0.26). These results demonstrated the benefit of applying an optical classification as a necessary first step into improving Chla retrievals from remotely sensed data in the contrasted coastal waters of the Salish Sea. With accurate Chla information, the health of the Salish Sea can be viably monitored at spatial and temporal scales suitable for ecosystem management.
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Keywords
optical, Salish Sea, chlorophyll algorithm, MODIS, Sentinel-3, ecosystem, empirical algorithms, remote sensing, hierarchical clustering, empirical orthogonal function analysis, coastal waters