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Reflectance curves from the 2002 cruise in Peconic Bay, Long Island PowerPoint PPT Presentation


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Retrieval of ocean properties using multispectral methods S. Ahmed, A. Gilerson, B. Gross, F. Moshary Students: J. Zhou, M. Vargas, A. Gill, B. Elmaanaoui, K. Aran.

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Reflectance curves from the 2002 cruise in Peconic Bay, Long Island

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Reflectance curves from the 2002 cruise in peconic bay long island

Retrieval of ocean properties using multispectral methodsS. Ahmed, A. Gilerson, B. Gross, F. Moshary Students: J. Zhou, M. Vargas, A. Gill, B. Elmaanaoui, K. Aran

Spectral Algorithm Development for Sensing of Coastal WatersSeparation of Overlapping Elastic Scattering and Fluorescence from Algae in Seawater through Polarization Discrimination


Reflectance curves from the 2002 cruise in peconic bay long island

Spectral Algorithm Development for Sensing of Coastal Waters

Reflectance curves from the 2002 cruise in Peconic Bay, Long Island


Ratio algorithm performance eastern long island

Ratio algorithm performance –Eastern Long Island

Blue / Green

NIR Spectral Ratio

In homogeneous waters where only Chlorophyll varies Blue / Green works only in Case I (see later) NIR Ratios work well in both Case I and Case II

but may be limited by small signals in open waters


Reflectance curves from the 2002 cruise in peconic bay long island

Absorption/Backscatter features

1- Chlorophyll absorption can be probed effectively using 440-570 band ratios

2- In presence of TSS and CDOM, Blue-Green ratios are contaminated.

3- Red-NIR algorithms are much less sensitive to TSS, CDOM.

4- The 670-710 channels effectively probe the ChL absorption feature and the

730 channel effectively calculates the backscatter since water abs dominates


Reflectance curves from the 2002 cruise in peconic bay long island

Simulation

Blue-Green

Three Band NIR ratios

Very high spread in the Blue-Green Ratio due to CDOM and TSS randomized

variability. This aspect is not relevant to the Red/NIR algorithms


Multispectral versus hyperspectral assessment of goes r coastal water imager

Future sensors (GOES-R) need to decide between multispectral or hyperspectral mode.

Hyperspectral channels are very important for shallow water retrieval

Preliminary tests compared multispectral vs hyperspectral sensing schemes based on Hydrolight Radiative transfer derived bio-optical model.

Multispectral versus Hyperspectral assessment of GOES-R Coastal Water Imager


Shallow water bio optical model based on hydrolight rt simulations carder et al

Shallow Water Bio-Optical ModelBased on Hydrolight RT simulations (Carder et al)

Parameterized Shallow Water Model Parameters

Remote Sensing Reflectance Spectra


Reflectance curves from the 2002 cruise in peconic bay long island

Inversion error versus measurement noise for all 6 parameters

Normalized Parameter Retrieval Error

Noise (%)


Results

Results

  • Hyperspectral channels are absolutely needed to reduce errors in shallow bottom heights and bottom reflectance (Panels 1 and 5)

  • Ocean column parameters are also much better retrieved using Hyperspectal configuration except for spectral slope of backscatter parameter which makes sense since this parameter caused only broad modification of the reflectance spectra. (Panel 6)


Reflectance curves from the 2002 cruise in peconic bay long island

  • Chl retrieval in Productive Case I waters can be obtained by both conventional blue-green type algorithms as well as NIR ratio algorithms

  • TSS and CDOM variability in case II waters makes blue/green ratios useless but three band NIR ratios are very insensitive to these parameters

  • Ratio algorithms for case II waters need thorough testing with in-situ monitoring using a consistent field testing protocol.

  • The effects of atmospheric correction to assess the sensitivity of the various two and three ratio algorithms need to be explored.

  • Development and sensitivity analysis of simultaneous atmosphere /ocean parameter retrieval using both multispectral and hyperspectral algorithms


Reflectance curves from the 2002 cruise in peconic bay long island

Separation of Overlapping Elastic Scattering and Fluorescence from Algae in Seawater through Polarization Discrimination

Objective:Separate overlapping fluorescence and elastic scattering spectra of algae excited by white light

Method: Utilize polarization properties of elastically scattered light and unpolarized nature of excited fluorescence to separate the two

Applications: Use fluorescence obtained as indication of Chl concentration even in turbid waters

Obtain elastic scattering spectra free of overlapping fluorescence for ocean color work


Reflectance curves from the 2002 cruise in peconic bay long island1

Reflectance curves from the 2002 cruise in Peconic Bay, Long Island


Fluorescence height

Fluorescence Height

Reflectance

Wavelength, nm

670

685

745

Fluorescence Height

Traditional method of the fluorescence height calculation over baseline


Experimental setup

Experimental Setup

Illuminator

FP

i2

Spectrometer

i1

P2

L

Nozzle

P1

WL

θ

C

L – lens, FP – fiber probe, A – aperture, P1, P2 – polarizers,

C – cuvette with algae, WL – water level.

Objects tested: algae Isochrysis sp.,Tetraselmis striata,

Thalassiosira weissflogii, “Pavlova”, concentrations up to 4x10^6 cells/mL,

algae with clays.


Polarized illumination

Polarized Illumination

Near zero if no depolarization valid for spherical particles

Generally validated using laser induced fluorescence but significant

error results due to scattering component


Extracted fluorescence

Extracted Fluorescence

Algae Isochrysis sp.

(brown algae spherical d ≈ 5 µm)

Algae Tetraselmis striata

(green algae slightly ellipsoidical d ≈ 12 µm)

Technique with polarized light


Unpolarized source

Unpolarized source

Light scattered by the algae illuminated by unpolarized light has some degree of polarization and can be also analyzed using polarization discrimination with

the same linear regression approach

Algae Isochrysis sp.(brown algae spherical d ≈ 5 µm)


Algae with clay

Algae with clay

Fluorescence magnitude retrieved from algae with different concentrations of clay

Reflectance curves for algae with clay, Cs = 0 - 200 mg/l

Clay – Na-Montmorillonite, particle size 2-4 µm


Extraction of fluorescence in the waters with rough surface lab experiments

Extraction of fluorescence in the waters with rough surface (lab experiments)

Unpolarized light

Probe above the water, probe vertical

No wind

Wind speed above the surface ≈ 9.5 m/s

Sample time increased to 10s from 1s

Algae Isochrysis. Concentration ~4.0 mln cells/ml.


Reflectance curves from the 2002 cruise in peconic bay long island

Extraction of fluorescence in the waters of Shinnecock Bay, Long Island

Ratio between 2 polarization components is close to linear

Chl concentration about 8 µg/l

June 2004


Simulation model for case 2 waters

Simulation Model for Case 2 Waters

Input

-Backscattering coefficient

-Absorption coefficient

[Mobley, 1994]

-Absorption coefficient of phytoplankton

[Morel, 1991]

-Absorption coefficient of CDOM

[Bricaud, et al., 1981]

-Absorption coefficient of minerals

[Stramski, et al., 2001]

-Reflectance

[Morel, 1977]

- Energy of emitted fluorescence

[Gower, et al., 1999]


Simulation model for case 2 waters1

Simulation model for case 2 waters

Output

Polarization components of reflectance are calculated from Mie code for 45° illumination (30° in water) & vertical observation

-scattering function at 150°, which was used as average value for calculating backscattering

where

Polarization components of

were used for calculation of reflectancepolarization components

Half of fluorescence is superimposed on polarization components as a spectrum with Gaussian shape centered at 685 nm

Fluorescence is retrieved using polarization technique

A and B are determined from fitting

outside fluorescence zone


Simulation model results

Simulation Model Results

Fluorescence retrieval from reflectance spectra for different concentrations of mineral particles: a) C = 5 mg/m3, b) C = 50 mg/m3.


Results of fluorescence retrieval comparison with baseline method

Results of fluorescence retrieval, comparison with baseline method

Comparison of retrieved fluorescence peak to assumed values for a range of mineral particle concentrations using both polarization discrimination and baseline subtraction


Conclusions future work

Conclusions/Future Work

  • Separation of Chlorophyll Fluorescence from scattering using polarization discrimination has been demonstrated for 4 types of algae with different shapes, sizes of particles

  • Implementation of the technique using both white light and sun light sources has proven successful in the lab and in the field conditions

  • Fluorescence extraction has been obtained even with the presence of high concentration of scattering medium

  • Validation with laser induced fluorescence has been performed

  • Extraction of fluorescence is successful for all illumination angles with polarized light, up to 50 deg for unpolarized light.


Conclusions future work1

Conclusions/Future Work

  • Magnitude of fluorescence peak extracted from reflectance spectra through polarization technique does not change with the concentration of scattering medium up to 200 mg/l.

  • Computer simulations show that fluorescence can be successfully retrieved for most water conditions typical for coastal zones with accuracy 7-11%.

  • “Fluorescence height” over baseline strongly overestimates actual and retrieved fluorescence height and these values do not correlate with each other for different concentrations of mineral particles.

  • Future simulations should include effects of multiple scattering and atmosphere on polarization components and fluorescence retrieval process.


Long island field measurements

Long Island Field Measurements


Bio optical model 1

Bio-Optical Model 1

Due to column and water floor respectively


Bio optical model 2

is the absorption coefficient due to water

is the absorption coefficient due to gelbstoff

is the backscattering of water

is the backscattering by particulate matters

Bio-Optical Model 2

is the absorption coefficient due to phytoplankton


Bio optical model 3

G is the gelbstoff absorption at 440nm

taken from tabulated values in Lee et all.

is the phytoplankton absorption coefficient at 400 nm

which varies with the CHLOROPHYLL concentration.

is dependent on

Bio-Optical Model 3


Bio optical model 4

Bio-Optical Model 4

Particulate scatter

is the backscattering coefficient of particulates at 440 nm

gives an indication of the size particles.

Water bottom (lambertian)

Using sand based normalized spectral

response

The parameters in the reflectance model to be retrieved are:


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