Physics-Based Modeling of Physics-Based Modeling of Coastal WatersCoastal Waters

Donald Z. TaylorDonald Z. Taylor

RIT College of Imaging ScienceRIT College of Imaging Science

RIT Graduate Seminar2

AgendaAgenda

MotivationMotivation BackgroundBackground Research AreasResearch Areas

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MotivationMotivation

Water QualityWater Quality ConstituentsConstituents Concentration of constituentsConcentration of constituents

Characterize water from a remotely sensed Characterize water from a remotely sensed signal signal

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Clarity of WaterClarity of Water

Secchi DiscSecchi Disc

RIT Graduate Seminar5

Water ColorWater Color

Forel-Ule color scaleForel-Ule color scale Used water color to define water massesUsed water color to define water masses Compares samples to standardsCompares samples to standards NonquantitativeNonquantitative

JerlovJerlov Optical classification using radiometric measurementsOptical classification using radiometric measurements

RecentRecent Spectra of individual constituentsSpectra of individual constituents

RIT Graduate Seminar6

Ocean Water ClassificationOcean Water Classification

Morel and Prieur (1977)Morel and Prieur (1977) Case 1: PhytoplanktonCase 1: Phytoplankton

~90% world’s water surface~90% world’s water surface

Case 2: SM and CDOMCase 2: SM and CDOM Coastal areas Coastal areas

– RecreationRecreation

– ShippingShipping

– Industry-fisheriesIndustry-fisheries

RIT Graduate Seminar7

Water ClassificationWater Classification

PhytoplanktonPhytoplankton Chlorophyll-aChlorophyll-a

Suspended Material (SM)Suspended Material (SM) InorganicInorganic

Sand, mud, clay, ashSand, mud, clay, ash

Yellow substancesYellow substances CDOM, GelbstoffCDOM, Gelbstoff

Decomposition of plankton Decomposition of plankton and other organismsand other organisms

Humic and fulvic acidsHumic and fulvic acids

RIT Graduate Seminar8

Remote SensingRemote Sensing

Airborne imaging systemsAirborne imaging systems MISI MISI

Modular Imaging Spectrometer InstrumentModular Imaging Spectrometer Instrument ~70 bands~70 bands

AVIRISAVIRIS Airborne Visible and Infrared Imaging SpectrometerAirborne Visible and Infrared Imaging Spectrometer

– ~225 bands (390-2500nm) ~225 bands (390-2500nm)

RIT Graduate Seminar9

SatellitesSatellites

CZCS (‘78-’86)CZCS (‘78-’86) 6 bands6 bands

SeaWiFS (‘97)SeaWiFS (‘97) 8 bands 8 bands

Hyperion (‘00)Hyperion (‘00) 220 bands220 bands

Contiguous Contiguous – 400-2500 nm400-2500 nm

RIT Graduate Seminar10

Radiometric Contributions Radiometric Contributions InIn Coastal WatersCoastal Waters

RIT Graduate Seminar11

Water ModelingWater Modeling

HydromodHydromod Combines MODTRAN and HYDROLIGHTCombines MODTRAN and HYDROLIGHT

Simulation of water quality parametersSimulation of water quality parameters Accuracy depends on user inputAccuracy depends on user input Bottom effectsBottom effects

Deep-water algorithmsDeep-water algorithms Extracting chlorophyll-a concentrationsExtracting chlorophyll-a concentrations Some success in determining SM and CDOMSome success in determining SM and CDOM Must be adjusted for use in-shoreMust be adjusted for use in-shore

RIT Graduate Seminar12

Research AreasResearch Areas Extend deep-water algorithmsExtend deep-water algorithms

Atmospheric correctionAtmospheric correction Coastal aerosol characterizationCoastal aerosol characterization

Bottom characterizationBottom characterization BubblesBubbles

Varying sizesVarying sizes– Highly scatteringHighly scattering

Optical interactionsOptical interactions Problematic for unmixingProblematic for unmixing

RIT Graduate Seminar13

Research AreasResearch Areas

Identify possible constituents (IOPs)Identify possible constituents (IOPs) Create libraryCreate library

Spectral signatures of water constituentsSpectral signatures of water constituents Adjust for regional variationsAdjust for regional variations

Stepwise unmixing Stepwise unmixing Assumption of linearityAssumption of linearity Correlation of variables an issueCorrelation of variables an issue

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Research AreasResearch Areas

Hydromod LUTHydromod LUT Create spectral curvesCreate spectral curves

Model varying Model varying concentrations of CHL, concentrations of CHL, CDOM, & SMCDOM, & SM

Match signal with curves of Match signal with curves of known concentrationsknown concentrations

Long run time to generateLong run time to generate May need to include May need to include

regional variations to be regional variations to be usefuluseful

RIT Graduate Seminar15

Thank YouThank You

Questions?Questions?

RIT Graduate Seminar16

ReferencesArnone, Robert A., Wood, A. Michelle, Gould,Jr., Richard W., The Evolution of Optical Water Mass Classification, Oceanography, vol. 17, no.2, June 2004Barbini, R., Colao, F., De Dominicis, L., Fantoni, R., Fiorani, L., Palucci, A., Artamonov, S. Analysis of simultaneous chlorophyll measurements by lidar fluorosensor, MODIS, and SeaWiFS, Int. Journal of Remote Sensing, 10 June, 2004, vol.25, no. 11,

2095-2110Chang, g., Mahoney, K., Briggs-Whitmire, A., Kohler, D.D.R., Mobley, C.D., Lewis, M.,

Moline, M.A., Boss, E., Kim, M., Philpot,W., Dickey,T., The New Age ofHyperspectral Oceanography, Oceanography, vol. 17, no.2, June 2004

Dekker,A.G., Brando, V.E., Anstee, J, Pinnel, N., Held, A., Preliminary assessment of the Performance of Hyperion in coastal waters, CSIRO Land & Water

Dickey, Tommy D., Studies of Coastal Ocean Dynamics and Processes Using EmergingOptical Technologies, Oceanography, vol. 17, no.2, June 2004

Figueras, D., Karnieli,A., Brenner, A., Kaufman, Y.J., Masking turbid water in thesoutheastern Mediterranean Sea utilizing the SeaWiFS 510nm spectral band, Int.Journal of Remote Sensing, 10 October, 2004, vol.25, no. 19, 4051-4059

Gower, J.F.R., In situ measurements of chlorophyll fluorescence and water opticalproperties as surface data for SeaWiFS, MODIS, and MERIS, Int. Journal ofRemote Sensing, 10-20 April, 2004, vol.25, no. 7-8, 1489-1493

Jorgensen, P.V., SeaWiFS data analysis and match-ups with in situ chlorophyllconcentrations in Danish waters, Int. Journal of Remote Sensing, 10-20 April,2004, vol.25, no. 7-8, 1397-1402

Morel, A. and Prieur, 1977, Analysis of variations in ocean colour, Limnology andOceanography, 22(4), 709-722

Philpot, W., Davis, C.O., Bissett, W.P., Mobley, C.D., Kohler, D.D.R., Lee, Z., Bowles, Steward, R.G., Agrawal, Y., Trowbridge,J., Gould,Jr., R.W., Arnone, R., Bottom Characterization from Hyperspectral Image Data, Oceanography, vol. 17, no.2,

June 2004Sathyendranath, Subha, (editor) IOCCG Report 3, Remote Sensing of Ocean Colour in

Coastal, and Other Optically-complex, WatersStegmann, Petra M., Remote monitoring of aerosols with ocean colour sensors: then and now, Int. Journal of Remote Sensing, 10-20 April, 2004, vol. 25, no. 7-8, pp.1409-1413