ORSL The Optical Remote Sensing Laboratory of The City College of New York
138th St. & Convent Ave., New York, NY 10031

ORSL version 2.2.0
ORSL » Ocean and Coastal Waters » Research Areas

Index of Ocean and Coastal Waters Research Areas

The purpose of the Ocean and Coastal ORS Lab is to monitor and investigate the optical properties of complex coastal areas as well as clear open ocean waters. This is accomplished with remotely-sensed data, received from operational and research satellites, observing platforms and in situ data.

PageResearch Area
  1  Tracking of Harmful Algal Blooms
  2  Multiangular Hyperspectral Polarimetry in Case I and Case II Waters
  3  Improvement of Algorithms for Remote Sensing for Oceanic and Coastal Areas
  4  Observing Platforms for Calibration and Validation of Satellite Oceanic Products
  5  Retrieval of Chlorophyll Fluorescence

Tracking of Harmful Algal Blooms

More than 40 species of toxic microalgae live in the Gulf of Mexico, but the most common is the toxic dinoflagellate Karenia brevis (K. brevis), formerly known as Gymnodinium breve. Although K. brevis blooms have been reported throughout the Gulf of Mexico, they are most frequent along the West Florida Shelf (WFS) where they occur nearly every year, usually between late fall and early spring but occasionally at other times of the year as well. K. brevis blooms have many negative impacts due to brevetoxin. This associated toxin causes death in fish, birds, and marine mammals. It also can irritate human eyes and respiratory systems once it becomes airborne in sea spray.

We propose a detection technique for blooms with low backscatter characteristics, which we name the Red Band Difference (RBD) technique, coupled with a selective Karenia brevis bloom classification technique, which we name the Karenia brevis Bloom Index (KBBI). These techniques take advantage of the relatively high solar induced chlorophyll fluorescence and low backscattering of Karenia brevis blooms. The techniques are applied to the detection and classification of K. brevis blooms from Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color measurements off the Gulf of Mexico.


  • R. Amin, J. Zhou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, "Novel optical techniques for detecting and classifying toxic dinoflagellate Karenia brevis blooms using satellite imagery," Opt. Express 17, 9126-9144 (2009).

Multiangular Hyperspectral Polarimetry in Case I and Case II Waters

Since Waterman’s pioneering observations of the underwater polarized light field (Waterman 1954), scientists have made progress in developing radiative transfer models to predict and accurately measure the spectral and angular distribution of the underwater light field. Yet, a major but vastly understudied component of the underwater light field is the polarized light field. At the ORS lab we are investing the underwater polarization combining both experimental data (acquired through custom-built sensors) and vector radiative transfer calculations.

Dependence of the polarized water-leaving radiance on the particles microphysics

The polarization of light in the atmosphere has been used as a tool for gaining information on aerosol optical properties that could not have been obtained by studying the scalar radiance alone (see, for example, Waquet et al. 2009 and references therein). In the atmosphere, polarization mainly comes from single scattering so that angular features of the phase function are mapped directly onto the polarized radiance. Features in the single scattering can be readily identified in the angular distribution of the degree of (linear) polarization (DOP). In the ocean, the features tend to be washed out due to the presence of multiple scattering by hydrosols. In the open ocean (Case I waters), most particles are organic particles (both living and nonliving), covarying with chlorophyll concentration. These suspended particles have a weak effect on the underwater DOP because of usually low concentrations and low refractive indices (Harmel et al. 2008). The underwater polarization is, therefore, mainly driven by Rayleigh scattering by water molecules resulting in a relatively simple pattern, i.e. maximal DOP between 0.6-0.8 (depending on the wavelength) occurring around 90° scattering angle. However, in Case II waters, inorganic particles, having a relative refractive index much higher than chlorophyllic particles, can significantly change the DOP of the water-leaving radiance.

Our aim is to use polarization to systematically retrieve additional and complementary information on the suspended particles (specifically, refractive index and size distribution) that can not be obtained with methods that only analyze the scalar intensity.

Development of biological response to the dynamic spectral-polarized underwater light field (2009 MURI Topic 7)

The Multidisciplinary University Research Initiative program (MURI) is a program designed to address large multidisciplinary topic areas representing exceptional opportunities for future DoD (Department of Defense) applications and technology options.

One of the winners of the MURI 2009 grants is the research group lead by Dr. Molly E. Cummings at University of Texas. For information click here. Several research groups, including the ORS Lab, are involved in this project, specifically:

  • At the University of Connecticut, Dr. Heidi M. Dierssen. For information click here.
  • At the University of Rhode Island, Dr. James M. Sullivan. For information click here.
  • in collaboration with Dr. Michael S. Twardowski of WET Labs. For information click here.
  • At Texas A&M University, Dr. George Kattawar. For information click here.

Many marine animals make use of the underwater polarization to achieve complete camouflage. Effective camouflage relies on matching the background perfectly. The difference between perfect and imperfect camouflage can mean the difference between life and death for many marine animals. For military applications, consequences resulting from complete versus incomplete camouflage are similarly grave and the success of a mission may critically depend upon perfect camouflage. The underwater polarized light field depend both on the IOPs of the water medium and on the time of the day. The biological world has responded to this dynamically changing portion of the electromagnetic spectrum by developing (a) polarization visual sensitivity, and (b) physiological responses to vary skin reflectance properties to mimic or contrast with the background. Having polarized vision, aids target detection underwater due to enhanced target contrast. Consequently, ignoring the polarized component in a camouflage design may increase its detection by unintended viewers with polarized sensitivities.

The aim of this project is to identify the mechanistic pathways that have evolved in the biological realm to send signals or remain concealed against the underwater polarized light field using a comparative approach. Both vertebrates and invertebrates systems are under investigation as well as molecular and hydrosol scattering water bodies, to address these specific objectives:

  • Develop and test a comprehensive spectral subsurface polarization model.
  • Identify static versus dynamic polarization camouflage responses.
  • Identify central versus peripheral control over polarization camouflage.

Field research is conducted in both in open ocean and coastal waters. Biological responses are studied in the lab on invertebrates and vertebrates selecting species that occupy oligotrophic and eutrophic environments. Physiological experiments are also conducted in the lab to determine the regulatory control of polarization camouflage in both vertebrate and invertebrate systems. By combining polarization modeling, field measurements, and physiological measurements of animal response in the lab in a comparative fashion, it might be possible to identify alternative solutions to the problem of camouflage in a polarized environment.


  • A. Tonizzo, J. Zhou, A. Gilerson, M. S. Twardowski, D. J. Gray, R. A. Arnone, B. M. Gross, F. Moshary, and S. A. Ahmed, "Polarized light in coastal waters: hyperspectral and multiangular analysis," Optics Express, 17(7), 5666-5682 (2009).
  • A. Tonizzo, A. Ibrahim, J. Chowdhary, A. Gilerson, and S. Ahmed, "Estimating particle composition from the polarized water-leaving radiance," Proceedings of Ocean Optics XX, 27 September - 1 October 2010, Anchorage, AK.
  • A. Tonizzo, A. Ibrahim, J. Zhou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, "Estimation of the polarized water leaving radiance from above water measurements," Proceedings of SPIE Ocean Sensing and Monitoring II, 5 - 9 April Orlando, FL.
  • A. Tonizzo, A. Ibrahim, J. Zhou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, "The impact of algal fluorescence on the underwater polarized light field," Proceedings of SPIE Ocean Sensing and Monitoring II, 5 - 9 April, Orlando, FL.
  • A. Tonizzo, J. Zhou, A. Gilerson, B. Gross, F. Moshary, and S. Ahmed, "Multiangular hyperspectral investigation of polarized light in case 2 waters," Proceedings of SPIE Remote Sensing of the Ocean, Sea Ice, and Large Water Regions, Berlin, Germany.
  • J. Zhou, A. Tonizzo, A. Gilerson, M. Twardowski, D. Gray, A. Weidemann, R. Arnone, B. Gross, F. Moshary, and S. Ahmed, "Polarization characteristics of coastal waters and their impact on in-water visibility," Proceedings of SPIE Ocean Sensing and Monitoring, 13-14 April, Orlando, FL.
  • A. Tonizzo, R. Dyer, R. Fortich, J. Zhou, A. Gilerson, J. Chowdhary, B. Gross, F. Moshary, and S. Ahmed, "Multi-angular Multi-spectral Polarized Reflectance from Coastal Waters for the Separation of Water Organic and Inorganic Particulate Components," Proceedings of IEEE 2008 International Geosciences and Remote Sensing Symposium (IGARSS 2008), July 6-11, Boston, MA.

Improvement of Algorithms for Remote Sensing for Oceanic and Coastal Areas

Red-NIR algorithms

Recent advances in the development of atmospheric correction models have made the retrieval of reflectance of coastal and inland waters from electromagnetic signals from the top of the atmosphere more accurate and have inspired further development of retrieval algorithms for turbid productive waters and their analysis. This includes algorithms that employ wavebands in the red and near infrared (NIR) range (650-800 nm), which are less sensitive than traditional blue-green (440-550 nm) ratio algorithms to the absorption by colored dissolved organic matter (CDOM) and scattering by mineral particles.

We tested such two-band and three-band red-NIR algorithms using comprehensive synthetic data sets of reflectance spectra and inherent optical properties related to various water parameters and a very consistent in situ data set from several lakes in Nebraska, USA.


  • Alexander A. Gilerson, Anatoly A. Gitelson, Jing Zhou, Daniela Gurlin, Wesley Moses, Ioannis Ioannou, and Samir A. Ahmed, "Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands," Opt. Express 18, 24109-24125 (2010).

Neural networks to retrieve the inherent optical properties of the ocean

Retrieving useful water inherent optical properties from Remote Sensing multispectral reflectance measurements is extremely difficult due to the complex nature of the forward modeling and the inherent nonlinearity of the inverse problem. In such cases, a promising method is the application of Neural Networks (NN). A Neural Network, if trained properly can yield retrievals that are very accurate and relatively insensitive to reasonable noise levels, since noise is introduced during the training process. The process we adopt utilizes 2 NN in parallel. The first neural network is used to relate the Remote Sensing Reflectance at all the available MODIS visible wavelengths, except the channel dedicated to the measurement of fluorescence, to suitable inherent absorption and backscattering coefficients at 442 nm. The second neural network is used to separate the absorption into algal and non algal components effectively outputting the ratio of algal to non-algal absorption. The synthetically trained algorithm is tested using both the NASA Bio-Optical Marine Algorithm Data set (NOMAD) as well as our own field data set from Chesapeake Bay and Long Island New York, with very good agreement.


  • I. Ioannou, W. Rossow, A. Gilerson, B. Gross, F. Moshary and S. Ahmed, "A neural network approach to retrieve the inherent optical properties of the ocean from the observations of MODIS" submitted to Applied Optics, 2011.

Observing Systems (LISCO)

Advances in oceanic bio-optical processes are expected to be more heavily focused on improving satellite retrieval products of inherent optical properties (IOPs) of coastal waters, which, because of their complexity, offer more challenges than open ocean waters, where satellite observations and retrieval algorithms are already reasonably effective. Thus, the validation of the current and future Ocean Color satellite data is important for characterizing the optical environment connected with coastal waters, which are of importance because of population concentrations along them and their susceptibility to anthropogenic impacts.

To address these concerns and support present and future multi- and hyper-spectral calibration and validation activities, as well as the development of new measurement and retrieval techniques and algorithms for coastal waters, the ORS Lab along with the Naval Research Laboratory at Stennis Space Center, Mississippi, has established a new, scientifically comprehensive, off-shore platform, the Long Island Sound Coastal Observatory (LISCO). This site has been designed to serve as a venue and framework for combining multi- and hyperspectral radiometer measurements with satellite and in situ measurements and radiative transfer simulations of coastal waters, helping to provide more effective closure for the whole measurement validation and simulation loop. Measurements are utilized for multi-spectral calibration and validation of current Ocean Color satellites (MERIS, MODIS, SeaWIFS) in coastal waters, and for evaluating future satellites missions (NPOESS, OCM2, Sentinel-2) with extension to hyperspectral calibration and validations of the hyperspectral sensors (HICO), as well as for improvements in coastal IOP retrieval and atmospheric correction algorithms.

The platform combines an AERONET SeaPRISM radiometer (CIMEL Electronique) as a part of AERONET Ocean Color Network (AERONET-OC), with a co-located HyperSAS set of radiometers capable of hyperspectral measurements of water-leaving radiance, sky radiance and downwelling irradiance. Both instruments were installed on the Long Island Sound Coastal Observatory (LISCO) in October 2009 and since then have been providing data. SeaPRISM data are transferred by the satellite link to NASA. Raw SeaPRISM data are also collected at the CCNY-ORSL server. HyperSAS data are transmitted via a broadband cellular service as emails to the CCNY-ORSL Sky server. The instruments are positioned on a retractable tower (Floatograph).

In June 2010 the HyperSAS system was upgraded to its polarization version, i.e. HyperSAS POL, which allows the detection of the Stokes components I, Q and U of the upwelling water-leaving radiance.

Additional in-water measurements:

Field measurements are regularly taken near LISCO for the matchups with the instruments as well to determine variability of water parameters and its impact on the validation of the ocean color satellite data. The instruments currently being deployed are:


  • S. Hlaing, T. Harmel, A. Ibrahim, I. Ioannou, A. Tonizzo, A. Gilerson, and S. Ahmed, "Validation of Ocean Color Satellite Sensors using Coastal Observational Platform in Long Island Sound," Proceedings of SPIE 7825-15.
  • A. Tonizzo, T. Harmel, A. Ibrahim, S. Hlaing, I. Ioannou, A. Gilerson, J. Chowdhary, B. Gross, F. Moshary and S. Ahmed, "Sensitivity of the above water polarized reflectance to the water composition," Proceedings of SPIE 7825-15.

Retrieval of Chlorophyll Fluorescence

The polarization discrimination technique

The NIR peak in the NIR spectrum of the reflectance can be significantly affected by chlorophyll fluorescence depending on the water composition. The accuracy of [Chl] retrieval depends, therefore, on the ability to separate contributions of elastic scattering from fluorescence spectra.

The polarization discrimination technique we developed, shows that it is possible to separate the elastic scattering and the chlorophyll fluorescence signal from the water-leaving radiance by making use of the fact that the elastically scattered components are partially polarized, while the fluorescence signal is unpolarized. The technique has been shown to be applicable to a wide range of water conditions.

The fluorescence component in the reflectance spectra

We conducted detailed analysis (through extensive simulations using HYDROLIGHT of the remote sensing reflectance spectra to reassess existing fluorescence algorithms in order to identify sources of errors. In particular, it is important to understand their limits in coastal waters in the context of optically active constituents, including variations in specific absorption of chlorophyll and accessory pigments, CDOM absorption, and scattering and absorption by nonalgal particles (NAP). We also used field and satellite data to analyze the performance and retrieval limitations of MODIS and MERIS FLH algorithms in the variety of coastal waters and to examine improvements for spectral band selection suitable for future sensors.

Quantum yield of chlorophyll fluorescence

The detection of solar induced chlorophyll fluorescence (SICF) obtained by processing ocean color spectra from satellite sensors (e.g. MODIS and MERIS) has been a very powerful tool for monitoring marine phytoplankton on synoptic scales. As a signal specific to phytoplankton, SICF provides an alternative means to assess the biomass and primary productivity. Our approach for the retrieval of SICF takes advantage of hyperspectral field measurements of absorption and attenuation, which are combined with remote sensing reflectance and used to determine SICF and its quantum yield in highly productive coastal waters.


  1. S. Ahmed, A. Gilerson, A. Gill, B. M. Gross, F. Moshary, and J. Zhou, "Separation of fluorescence and elastic scattering from algae in seawater using polarization discrimination," Opt. Commun. 235, 23–30 (2004).
  2. A. Gilerson, J. Zhou, B. Elmaanaoui, B. Gross, F. Moshary, and S. Ahmed, "Separation of fluorescence and scattering from algae and suspended solids in seawater through polarization: modeling and experiments," in Proceedings of the Eighth International Conference on Remote Sensing for Marine and Coastal Environments (Halifax, Nova Scotia, Canada, 2005).
  3. A. Gilerson, M. Oo, J. Chowdhary, B. M. Gross, F. Moshary, and S. A. Ahmed, "Polarization characteristics of waterleaving radiance: application to separation of fluorescence and scattering components in coastal waters," in Remote Sensing of the Coastal Oceanic Environment, R. J. Frouin, M. Babin, and S. Sathyendranath, eds., Proc. SPIE 5885, 95–105 (2005).
  4. Alexander Gilerson, Jing Zhou, Min Oo, Jacek Chowdhary, Barry M. Gross, Fred Moshary, and Samir Ahmed, "Retrieval of chlorophyll fluorescence from reflectance spectra through polarization discrimination: modeling and experiments," Appl. Opt. 45, 5568-5581 (2006).
  5. A. Gilerson, J. Zhou, S. Hlaing, I. Ioannou, J. Schalles, B. Gross, F. Moshary, and S. Ahmed, "Fluorescence component in the reflectance spectra from coastal waters. Dependence on water composition," Opt. Express 15, 15702-15721 (2007).
  6. J. Zhou, A. Gilerson, I. Ioannou, S. Hlaing, J. Schalles, B. Gross, F. Moshary, and S. Ahmed, "Retrieving quantum yield of sun-induced chlorophyll fluorescence near surface from hyperspectral in-situ measurement in productive water," Opt. Express 16, 17468-17483 (2008).

ORSL/CCNY/CUNY disclaim liability of any kind whatsoever, including, without limitation, liability for quality, performance,
merchantability and fitness for a particular purpose arising out of the use or inability to use the data presented herein.

Program Code Copyright © Thomas Legbandt 2010 - 2016

Locations of visitors to this page