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Remote sensing of suspended particulate matter, SPM, from space has long been used to assess its spatio-temporal variability in various coastal areas. The associated algorithms were generally site specific or developed over a relatively narrow range of concentration, which make them inappropriate for global applications (or at least over broad SPM range). In the frame of the GlobCoast project, a large in situ data set of SPM and remote sensing reflectance, Rrs(λ), has been built gathering together measurements from various coastal areas around Europe, French Guiana, North Canada, Vietnam, and China. This data set covers various contrasting coastal environments diversely affected by different biogeochemical and physical processes such as sediment resuspension, phytoplankton bloom events, and rivers discharges (Amazon, Mekong, Yellow river, MacKenzie, etc.). The SPM concentration spans about four orders of magnitude, from 0.15 to 2626 g·m-3. Different empirical and semi-analytical approaches developed to assess SPM from Rrs(λ) were tested over this in situ data set. As none of them provides satisfactory results over the whole SPM range, a generic semi-analytical approach has been developed. This algorithm is based on two standard semi-analytical equations calibrated for low-to-medium and highly turbid waters, respectively. A mixing law has also been developed for intermediate environments. Sources of uncertainties in SPM retrieval such as the bio-optical variability, atmospheric correction errors, and spectral bandwidth have been evaluated. The coefficients involved in these different algorithms have been calculated for ocean color (SeaWiFS, MODIS-A/T, MERIS/OLCI, VIIRS) and high spatial resolution (LandSat8-OLI, and Sentinel2-MSI) sensors. The performance of the proposed algorithm varies only slightly from one sensor to another demonstrating the great potential applicability of the proposed approach over global and contrasting coastal waters. [ABSTRACT FROM AUTHOR]

This study analyzes relationships between concentration of suspended particles represented by dry mass, [SPM], or area, [AC], and optical properties including particulate beam attenuation (cp), side scattering (bs), and backscattering (bbp), obtained from an intensive sampling program in coastal and offshore waters around Europe and French Guyana. First-order optical properties are driven by particle concentration with best predictions of [SPM] by bbp and bs, and of [AC] by cp. Second-order variability is investigated with respect to particle size, apparent density (dry weight-to-wet-volume ratio), and composition. Overall, the mass-specific particulate backscattering coefficient, bmbp ( = bbp : [SPM]), is relatively well constrained, with variability of a factor of 3-4. This coefficient is well correlated with particle composition, with inorganic particles having values about three times greater (bmbp = 0.012 m² g-1) than organic particles (bmbp = 0.005 mm² g-1). The mass-specific particulate attenuation coefficient, cmp ( = cbp : [SPM]), on the other hand, varies over one order of magnitude and is strongly driven (77% of the variability explained) by particle apparent density. In this data set particle size does not affect cmp and affects bmbp only weakly in clear (case 1) waters, despite size variations over one order of magnitude. A significant fraction (40-60%) of the variability in bmbp remains unexplained. Possible causes are the limitation of the measured size distributions to the 2-302-µm range and effects of particle shape and internal structure that affect bbp more than cp and were not accounted for. [ABSTRACT FROM AUTHOR]