Download final_paper

Tim Wynne
Using Remote Sensing Reflectance as a proxy for Chlorophyll-a Concentration using in
situ Data and Data from a Hydrolight Simulation.
Abstract:
Remote Sensing Reflectance (RRS) was calculated using data obtained from a
Hyperspectral Tethered Radiometer Spectral Radiometer (HTSRB), and from modeling
data from an ac9 with Hydrolight. The RRS values that were obtained from the two
different methods were then compared, and resulted with curves of approximately the
same shape, but with the HTSRB data having a factor of two higher than the Hydrolight
RRS curve. The RRS was then used to calculate the chlorophyll-a concentration, using
the SeaWiFS/OC4v4 and SeaWiFS/OC2v4 algorithms. The derived chlorophyll
concentration compared favorably with the chlorophyll concentration that was measured
with a profiling fluorometer. The Lu sensor on the HTSRB measures the upwelling
radiance 63 cm below the surface. This was corrected for and the resultant RRS curves
and chlorophyll values showed little change.
Introduction:
The ocean optics class went on a cruise on Friday, 9 July 2004 aboard the R/V Ira C.
Among other data the class collected data from a Hyperspectral Tethered Radiometer
Spectral Radiometer (HTSRB), an ac9, and a bb2f from the mouth of the Damariscotta
River Estuary (ME, USA). The HTSRB is a hyperspectral instrument from Satlantic
(www.satlantic.com). The instrument floats at the surface and collects upwelling radiance
(Lu) and downwelling irradiance (Ed). The ac9 is a profiling multispectral instrument
from WETLabs (www.wetlabs.com). The ac9 collects absorption (a) and attenuation (c)
data from nine wavelengths ranging between 412 and 715 nanometers (nm). The bb2f is a
profiling instrument that collects backscatter (bb) information, but also contains a
fluorometer.
Methods:
Calculating RRS with a HTSRB
The first method that was evaluated uses data obtained from a HTSRB to calculate RRS.
Thirteen different deployments of the HTSRB were examined. Ed was graphed for each
deployment with respect to wavelength (figure 1). For ease of analysis the mean was then
calculated and graphed in figure 2. Likewise Lu was graphed and then the mean was
calculated (figure 3).
RRS is defined in equation 1.
RRS = Lw/Ed
(1)
Where Lw is the upwelling water leaving radiance (W m-2 sr-1 nm -1) and Ed as
previously stated is the downwelling plane irradiance (W m-2 nm -1). After the division
the resultant units for RRS are 1/sr.
The instrumentation available did not measure Lw, but Lu, so Lw must be calculated for.
Lw was calculated using equation 2 (Kirk, 1994).
Lw = Lu * (t/n2)
(2)
Where t is the Fresnel Transmittance, which is a constant of 0.98 and n is the index of
refraction of seawater (1.33). We can now rewrite equation one.
RRS = (0.55*Lu)/Ed
(3)
The calculated RRS is graphed in figure 4.
Correction for the Lu measured at 63 cm
The HTSRB measures Lu from a sensor that is 63 cm deep in the water column. This is
not the same as Lu at the surface, and therefore a correction is needed in order to get a
more accurate representation of the value. Equation 4 illustrates the new Lu that should
be calculated.
Lu(at_surface) = Lu(at_0.63 meters) * e^(Klu*0.63)
(4)
Where Klu is defined at the attenuation of water leaving radiance.
In order to solve for this must be Klu calculated. It is assumed that Klu = Kd, where Kd
(attenuation coefficient) is defined by equation 5.
Kd = (a^2 + G*a*b)^1/2
(5)
Where G is a constant equal to 0.256 (Kirk, 1994).
The absorption (a) and scatter (b) values were derived from a depth integrated ac9 cast.
But first the ac9 data were corrected for salinity, temperature, and scattering, using a
spectrally varying correction. Scatter was calculated by equation 6. The results of a,b,and
c are graphed in figure 5
b=c–a
(6)
The ac9 data was integrated over depth (the cast went to 30 meters), so that only one
value per wavelength is calculated. Before the absorption could be used to derive Kd the
absorption of water was added onto the data, using coefficients from Pope and Fry
(1997).
With an accurate representation of Kd available (figure 6) it now becomes possible to
solve for the water leaving radiance (Lu) at the surface using equation 4. Lu at the surface
is in figure 7.
Using a Hydrolight Simulation
The second method of calculating RRS utilized the acquired ac9 data and was modeled
using Sequoia Scientifics’ Hydrolight software. Hydrolight is designed to model the light
field at a user defined place and time and under user defined conditions. Essentially the
user defines the inherent optical properties (IOPs) and a few ancillary inputs, and
Hydrolight outputs the apparent optical properties (AOPs). Hydrolight calculated the sun
angle for the input latitude (43 degrees N), longitude (69 degrees W), and time (15:00
GMT). The software also prompts the user for cloud cover, which was entered at 90% for
a very overcast day. The corrected attenuation and absorption values were entered into
the Hydrolight software. The output values of Lu and Lw from the Hydrolight simulation
were graphed with respect to wavelength and shown in figure 8. The RRS from the
Hydrolight run is graphed in figure 9.
RRS values from the Hydrolight simulation and RRS values calculated using Lu values at
63 cm, and at the surface are show in figures 10 and 11, respectively.
Calculating Chlorophyll with OC2 and OC4
The SeaWiFS OC2v4 algorithm modified for cubic polynomials was used to calculate the
chlorophyll from the remote sensing reflectance1 see equation 7.
Chl-a (ug/l) = 10.0^(a(0) + a(1)*R + a(2)*R^2 + a(3)*R^3) +a(4)
(7)
Where R = log(RRS490/RRS555), a(0)=0.319, a(1)=-2.336, a(2)=0.879, a(3)=-0.135, and
a(4)=-0.071.
For comparison the SeaWiFS OC4v4 algorithm was also used in order to calculate the
chlorophyll-a concentration from RRS, see equation 8.
Chl-a (ug/l) = 10.0^(a(0)+ a(1)*R + a(2)*R^2 + a(3)*R^3 + a(4)*R^4)
(8)
Where R = log((Rrs443>Rrs490>Rrs510)/Rrs555), a(0)=0.366, a(1)=-3.067, a(2)=1.930,
a(3)=0.649, a(4)=-1.532
Results:
There were three different methods used to derive at RRS values, and two different
algorithms were used to derive chlorophyll-a concentration. The values are found in
table 1. The corrected HTSRB values refer to Lu being measured at the surface, while the
uncorrected HTSRB values refer to Lu being measured at 0.63 meters.
Method
HSTRB corrected OC2 algorithm
HTSRB uncorrected OC2 algorithm
HTSRB corrected OC4 algorithm
HTSRB uncorrected OC4 algorithm
Hydrolight OC2 algorithm
Hydrolight OC4 algorithm
Fluorometer
Chlorophyll-a (ug/l)
2.4377
2.4487
3.4757
3.51
1.8786
2.0212
2.48
Assuming that the fluorometer on the bb2f was accurate, the results derived from the
OC2 algorithm are in near perfect agreement.
Discussion:
Ocean color satellite platforms have used RRS to calculate chlorophyll-a concentrations
for years. The Coastal Zone Color Scanner (CZCS), SeaWiFS, and MODIS sensors all
calculate chlorophyll-a concentrations using different ratios of RRS. The estimated
chlorophyll from satellites must be verified by in situ measurements, such as the
measurements described here. There was no available satellite imagery, to compare to the
calculated chlorophyll value for the sampled day, as the local conditions were masked
under heavy cloud cover.
The agreement between the fluorometer and the OC2 algorithms were freakishly close to
one another. Attached to this paper is my code for review. The OC4 algorithm produced
results in the same ball park, but higher relative to the fluorometer. Once again the
Hydrolight simulation produced results in the same ball park, but lower than the
fluorometer.
It does not appear that correcting Lu from 0.63 meter to the surface made any noticeable
difference in calculating the chlorophyll-a concentration. There was a loss of data from
going from the 200 channel HTSRB to the 9 channel ac9.
I have dealt with ocean color satellite data for over two years, and have never done any
validation. This was a truly enlightening exercise and I appreciate all of the people that
helped me along the way.
References
Kirk, J.T.O. Light and Photosynthesis in Aquatic Ecosystems. Second edition. 1994.
Cambridge University Press.
Pope, R. and E. Fry (1997). Absorption spectrum (380-700 nm) of pure water. Integrating
cavity measurements. Applied Optics 36(33): 8710-8723.
(http://seawifs.gsfc.nasa.gov/SEAWIFS/RECAL/Repro3/OC4_reprocess.html)