Estimating the Bulk Refractive Index and Related Particulate Properties of Natural Waters From Remote-Sensing Data

A proof-of-concept method is developed to estimate bulk refractive index (η<sub>bp</sub>) of particles for deriving information on their composition and optical properties of natural waters using satellite ocean color data. It estimates η<sub>bp</sub> as a function of the backscattering ratio (B<sub>p</sub>), hyperbolic slope of the particle size distribution (ξ derived from the beam attenuation slope β), and apparent density of particles (ρ<sub>a</sub>) as described in our previous inversion model. For deriving these parameters from remote-sensing data, large in situ measurement data of the remote-sensing reflectance (R<sub>rs</sub>), particulate scattering (b<sub>p</sub>), backscattering (b<sub>bp</sub>) beam attenuation (c<sub>p</sub>), and seawater constituents' concentrations are used to establish the required relationships and derive the model parameters (i.e., η<sub>bp</sub> ← B<sub>p</sub>, ξ, ρ<sub>a</sub>; B<sub>p</sub> ← R<sub>rs</sub>; ξ ← β ← c<sub>p</sub> ← Turbidity; Turbidity - R<sub>rs</sub>; and ρ<sub>a</sub> ← c<sub>p</sub>). When validated with those derived from in situ data spanning the large dynamic range in water optical properties and relevant water constituents impacting the remote-sensing signal, the derived model parameters and bulk refractive index had errors of a few percent which falls well within the benchmark for a validated uncertainty of ±35% endorsed for the remote-sensing retrieval of chlorophyll-a in oceanic waters. The model was applied to regional and global images of satellite ocean color observations provided by the MODIS-Aqua sensor. Global images of seasonal climatology over a decade of MODIS-Aqua ocean color observations provided interesting insights into the seasonal variability of η<sub>bp</sub> in coastal and open ocean waters. To further investigate the bulk particulate assemblages in some regional waters, several MODIS-Aqua imageries from different regional waters dominated by sediment-laden river plumes and phytoplankton blooms were analyzed. Satellite retrievals of the η<sub>bp</sub> varied from 1.035 to 1.05 for clear oceanic waters, 1.045- 1.07 for phytoplankton-dominated waters (higher water content), 1.05-1.15 for floating algal blooms and Cocolithophore blooms, 1.07-1.10 for coastal waters dominated by detrital particles, and 1.10-1.28 for river plume and sediment-laden coastal waters (lower water content). These results were consistent with those expected for the waters examined, being in excellent agreement with the previous reports and estimates based on the laboratory/in situ measurements and modeling studies. Given the fact that there is currently no satellite-based method to differentiate between bulk particulate compositions, the new method provides a valuable tool for estimating η<sub>bp</sub> values as a proxy for the apparent density and composition of particles and such information when derived from satellite ocean color data provides new tools for improving our current understanding of particle dynamics of pelagic ecosystems, advancing biogeochemical modeling, assessing the global ocean ecosystem, and elucidating the coastal processes.

[1]  P. Utgoff,et al.  Potential Interactions Among Ocean Acidification, Coccolithophores, and the Optical Properties of Seawater , 2009 .

[2]  Dariusz Stramski,et al.  Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration , 2003 .

[3]  F. Gohin,et al.  Turbidity retrieval and monitoring of Danube Delta waters using multi-sensor optical remote sensing data: An integrated view from the delta plain lakes to the western–northwestern Black Sea coastal zone , 2013 .

[4]  Hervé Claustre,et al.  Phytoplankton pigment distribution in relation to upper thermocline circulation in the eastern Mediterranean Sea during winter , 2001 .

[5]  M. S. Finch,et al.  A biogeochemical study of the coccolithophore, Emiliania huxleyi, in the North Atlantic , 1993 .

[6]  Palanisamy Shanmugam,et al.  A new theory and its application to remove the effect of surface-reflected light in above-surface radiance data from clear and turbid waters , 2014 .

[7]  H. Gordon,et al.  Computed relationships between the inherent and apparent optical properties of a flat homogeneous ocean. , 1975, Applied optics.

[8]  Michael S. Twardowski,et al.  Microscale Quantification of the Absorption by Dissolved and Particulate Material in Coastal Waters with an ac-9 , 1999 .

[9]  Annick Bricaud,et al.  Light backscattering efficiency and related properties of some phytoplankters , 1992 .

[10]  Sean G. Herring,et al.  Shape of the particulate beam attenuation spectrum and its inversion to obtain the shape of the particulate size distribution. , 2001, Applied optics.

[11]  Andrew H. Barnard,et al.  A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters , 2001 .

[12]  R. Davies‐Colley,et al.  Predicting light penetration into river waters , 2008 .

[13]  Dariusz Stramski,et al.  Measurements and characterization of particle size distributions in coastal waters , 2010 .

[14]  Y. C. Agrawal,et al.  Instruments for particle size and settling velocity observations in sediment transport , 2000 .

[15]  U. K. Pradhan,et al.  Influence of anthropogenic activities on the existing environmental conditions of Kandla Creek (Gulf of Kutch) , 2010 .

[16]  H. Loisel,et al.  Variability and classification of remote sensing reflectance spectra in the eastern English Channel and southern North Sea , 2007 .

[17]  J. Ronald V. Zaneveld,et al.  Temperature-dependent absorption of water in the red and near-infrared portions of the spectrum , 1993 .

[18]  D. Stramski,et al.  Modeling the optical properties of mineral particles suspended in seawater and their influence on ocean reflectance and chlorophyll estimation from remote sensing algorithms. , 2004, Applied optics.

[19]  A. Morel.  Optical modeling of the upper ocean in relation to its biogenous matter content (case I waters) , 1988 .

[20]  O. Chauhan.  Influence of macrotidal environment on shelf sedimentation, Gulf of Kachchh, India , 1994 .

[21]  David Doxaran,et al.  Role of measurement uncertainties in observed variability in the spectral backscattering ratio: a case study in mineral-rich coastal waters. , 2009, Applied optics.

[22]  Michael S Twardowski,et al.  Use of optical scattering to discriminate particle types in coastal waters. , 2005, Applied optics.

[23]  D. Doxaran,et al.  Spectral signature of highly turbid waters: Application with SPOT data to quantify suspended particulate matter concentrations , 2002 .

[24]  Palanisamy Shanmugam,et al.  OSABT: An Innovative Algorithm to Detect and Characterize Ocean Surface Algal Blooms , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[25]  Y. Ahn,et al.  Detecting the red tide algal blooms from satellite ocean color observations in optically complex Northeast-Asia Coastal waters , 2006 .

[26]  Trevor Platt,et al.  Remote sensing of phytoplankton functional types , 2008 .

[27]  R. P. Mathur,et al.  Heavy metals in water and sediments of upper Ganga , 1988 .

[28]  Palanisamy Shanmugam,et al.  Monitoring of ocean surface algal blooms in coastal and oceanic waters around India , 2014, Environmental Monitoring and Assessment.

[29]  Annick Bricaud,et al.  Analysis of in-situ spectral absorption meter data , 1992, Optics & Photonics.

[30]  Sonia Gallegos,et al.  Development of Suspended Particulate Matter Algorithms for Ocean Color Remote Sensing , 2001 .

[31]  K. Carder,et al.  Physical, Chemical, and Optical Measures of Suspended-Particle Concentrations: Their Intercomparison and Application to the West African Shelf , 1974 .

[32]  V. P. Rao,et al.  On the possibility of high-velocity tidal streams as dynamic barriers to longshore sediment transport: Evidence from the continental shelf off the Gulf of Kutch, India , 1982 .

[33]  Andrew H. Barnard,et al.  Spectral particulate attenuation and particle size distribution in the bottom boundary layer of a continental shelf , 2001 .

[34]  Watson W. Gregg,et al.  Interannual Variation in Phytoplankton Primary Production at A Global Scale , 2013, Remote. Sens..

[35]  Palanisamy Shanmugam,et al.  A New Inversion Model to Retrieve the Particulate Backscattering in Coastal/Ocean Waters , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[36]  J R Zaneveld,et al.  Absorption and attenuation of visible and near-infrared light in water: dependence on temperature and salinity. , 1997, Applied optics.

[37]  W. Steen.  Absorption and Scattering of Light by Small Particles , 1999 .

[38]  C. Mobley,et al.  Estimation of the remote-sensing reflectance from above-surface measurements. , 1999, Applied optics.

[39]  Palanisamy Shanmugam,et al.  A novel method for estimation of aerosol radiance and its extrapolation in the atmospheric correction of satellite data over optically complex oceanic waters , 2014 .

[40]  E. Boss,et al.  Relationship of light scattering at an angle in the backward direction to the backscattering coefficient. , 2001, Applied optics.

[41]  Kenneth J. Voss,et al.  A spectral model of the beam attenuation coefficient in the ocean and coastal areas , 1992 .

[42]  Palanisamy Shanmugam,et al.  An evaluation of inversion models for retrieval of inherent optical properties from ocean color in coastal and open sea waters around Korea , 2010 .

[43]  V. P. Rao,et al.  Distribution and dispersal of clay minerals on the western continental shelf of India , 1982 .

[44]  R. Bukata,et al.  Optical Properties and Remote Sensing of Inland and Coastal Waters , 1995 .

[45]  A. Bricaud,et al.  Modeling the inherent optical properties of the ocean based on the detailed composition of the planktonic community. , 2001, Applied optics.

[46]  Michael S. Twardowski,et al.  Particulate backscattering ratio at LEO 15 and its use to study particle composition and distribution , 2004 .

[47]  L. Prieur,et al.  Analysis of variations in ocean color1 , 1977 .

[48]  P. Shanmugam.  New models for retrieving and partitioning the colored dissolved organic matter in the global ocean: Implications for remote sensing , 2011 .

[49]  Michael J. Behrenfeld,et al.  Coherence of particulate beam attenuation and backscattering coefficients in diverse open ocean environments. , 2010, Optics express.

[50]  G Chebbo,et al.  Relationship between turbidity and total suspended solids concentration within a combined sewer system. , 2011, Water science and technology : a journal of the International Association on Water Pollution Research.

[51]  David A. Siegel,et al.  Retrieval of the particle size distribution from satellite ocean color observations , 2009 .

[52]  Robert J Olson,et al.  Flow cytometric determination of size and complex refractive index for marine particles: comparison with independent and bulk estimates. , 2003, Applied optics.

[53]  E. Boss,et al.  Spectral beam attenuation coefficient retrieved from ocean color inversion , 2003 .

[54]  J. Kirk,et al.  Monte Carlo study of the nature of the underwater light field in, and the relationships between optical properties of, turbid yellow waters , 1981 .

[55]  Deborah J. Cedeño-Maldonado.  Spectral properties and population dynamics of the harmful dinoflagellate Cochlodinium polykrikoides (Margalef) in southwestern Puerto Rico , 2008 .

[56]  James C. Kitchen,et al.  The variation in the inherent optical properties of phytoplankton near an absorption peak as determined by various models of cell structure , 1995 .

[57]  Eyvind Aas,et al.  Refractive index of phytoplankton derived from its metabolite composition , 1996 .

[58]  G. Müller,et al.  Geogenic distribution and baseline concentration of heavy metals in sediments of the Ganges River, India , 2003 .

[59]  David Doxaran,et al.  Estimating turbidity and total suspended matter in the Adour River plume (South Bay of Biscay) using MODIS 250-m imagery , 2010 .

[60]  Palanisamy Shanmugam,et al.  A New Inversion Model to Estimate Bulk Refractive Index of Particles in Coastal Oceanic Waters: Implications for Remote Sensing , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[61]  D. Roberts,et al.  Remote sensing of suspended sediment concentration during turbid flood conditions on the Feather River, California—A modeling approach , 2012 .

[62]  Dariusz Stramski,et al.  Spectral dependency of optical backscattering by marine particles from satellite remote sensing of the global ocean , 2006 .

[63]  C. Yentsch.  A note on the fluorescence characteristics of particles that pkss through glass‐fiber filters1 , 1983 .

[64]  Dariusz Stramski,et al.  Effects of microbial particles on oceanic optics: A database of single‐particle optical properties , 1997 .

[65]  Patrick M. Holligan,et al.  The 1991 coccolithophore bloom in the central North Atlantic. 2. Relating optics to coccolith concentration , 1996 .

[66]  Elamurugu Alias Gokul,et al.  Modelling the inherent optical properties and estimating the constituents׳ concentrations in turbid and eutrophic waters , 2014 .