Empirical Remote Sensing Algorithms to Retrieve SPM and CDOM in Québec Coastal Waters - Mabit, Raphaël; Araújo, Carlos A. S.; Singh, Rakesh Kumar; Bélanger, Simon (Frontiers in Remote Sensing, 2022)
In most coastal waters, riverine inputs of suspended particulate matter (SPM) and coloured dissolved organic matter (CDOM) are the primary optically active constituents. Moderate and high-resolution satellite optical sensors, such as the Operational Land Imager (OLI) on Landsat-8 and the MultiSpectral Instrument(MSI) on Sentinel-2, offer a synoptic view of these coastal systems at high spatial resolution (10 - 30 m) with weekly revisits allowing the study of coastal dynamics (e.g., river plumes, sediment re-suspension events). Accurate estimations of CDOM and SPM from space requires regionally tuned bio-optical algorithms. Using an in situ data set of CDOM, SPM, and optical properties (both apparent and inherent) from various field campaigns carried in coastal waters of the Estuary and Gulf of St. Lawrence (EGSL) and eastern James Bay (JB) (N = 347), we developed regional algorithms for OLI and MSI sensors. We found that CDOM absorption at 440 nm ($a_g(440)$) can be retrieved using red-to-green band ratio for both the EGSL and the JB. In contrast, SPM algorithm required regional adjustments due to significant differences in mass-specific inherent optical properties. Finally, the application of the regional algorithms to satellite images from OLI and MSI indicated that the atmospheric correction algorithm (AC) C2RCC gives the most accurate remote-sensing reflectance ($R_rs$) absolute values. However, the ACOLITE algorithm gives the best results for CDOM estimation (almost null bias; Median Symetric Accuracy of 45% and $R^2$ of 0.78) as it preserved the $R_rs$ spectral shape, while tend to yield positively bias SPM (88%). C2RCC and spectral shape parameter (SSP) AC algorithms appears as good compromise for SPM retrieval in terms of bias and linearity. We conclude that the choice of the algorithm depends on the parameter of interest.