ICES mar. Sei. Sytnp., 197: 104-113. 1993
Estimation of primary production by observation of
solar-stimulated fluorescence
Roland Doerffer
Doerffer, R. 1993. Estimation of primary production by observation of solarstimulated fluorescence. - ICES mar. Sei. Symp., 197: 104-113.
Remote sensing of primary production of the ocean has become an important tool in
biological oceanography. A further development of presently available methods is
expected from the determination of the natural, solar-induced fluorescence of chloro­
phyll. This signal can be derived from radiance spectra, measured with airborne or
spaceborne sensors. It improves not only remote sensing of chlorophyll concentration,
particularly in turbid coastal waters, but opens also for the possibility of determining
the relationship between available light (PA R ) and primary production based on the
remote determination of the fluorescence yield. For this task the following variables
have to be retrieved from the radiance spectrum using an inverse modelling procedure :
chlorophyll concentration, other substances which attenuate light in the sea, irradi­
ance at sea level, fluorescence energy. In situ observations of natural fluorescence
have shown a high correlation with primary production for different water types. For
remote sensing of fluorescence, a num ber of problems have to be solved concerning
the influence of other substances and the impact of the atmosphere. The most critical
restriction comes from the strong absorption of red light caused by pure water, with the
consequence that the emitted fluorescence of approximately only the first 5 m can be
observed from above the surface. Thus, the preferable areas for applying this method
are productive regions with high chlorophyll concentrations in the surface layer or with
a well mixed euphotic zone, such as upwelling, polar, and coastal areas.
Roland Doerffer: G K S S Forschungszentrum, 2054 Geesthacht, Germany.
Introduction
The determination of primary production with the help
of remote-sensing data is one of the new methods in
biological oceanography which will lead to a much better
understanding of the temporal-spatial dynamics of
phytoplankton, its role within the foodweb, and its
impact on the cycle of matter in the biospheregeosphere system. Platt et al. (1991) (see also Sathyendranath and Platt, this volume) have demonstrated the
possibility of calculating primary production with pre­
sently available satellite data, i.e., chlorophyll maps
derived from Coastal Zone Color Scanner (CZCS) data.
Their protocol is based on a chlorophyll-lightphotosynthesis model and requires the knowledge of
additional variables and parameters, such as the vertical
distribution of chlorophyll, the available light at the sea
surface, and the vertical light attenuation. In particular,
one has to know the initial slope of the P -I curve
(production-irradiance relationship) as a measure of the
photosynthetic functioning of the phytoplankton com­
munity. This param eter, which is linked directly to the
quantum efficiency of photosynthesis, is variable and
depends on nutrient conditions and the light climate.
Knowledge of it is the key to the determination of
primary production by satellite data. A t present this
value, i.e., the relationship between production and
light, is determined by in situ or in vitro experiments.
Since the number of these P -I experiments is small
compared to the heterogeneity and temporal variability
of the oceans, the results can be used only as mean
values of different ocean provinces (or basins) and
seasons. Thus, it is highly desirable to determine this
param eter also by remote sensing.
One of the most promising candidates for deriving this
information directly from remotely sensed radiance
spectra is the sunlight-induced natural fluorescence of
phytoplankton chlorophyll. This signal has already been
used for determining chlorophyll concentrations from
airborne radiance spectra (Neville and Gower, 1977;
Doerffer, 1981). It has the advantage of being a much
more specific signal of chlorophyll than the blue/green
color ratio of the water-leaving radiance spectrum,
which is modified also by substances other than the
I C E S m a r . Sei. S y m p ., 197 (1993)
Estimation o f prim ary production by solar-stimulated fluorescence
105
phytoplankton chlorophyll. O ne problem in using the
2.4
Gelb 0 .0 5 m [4 4 0 ]
fluorescence signal for determining the concentration is
Susp M lm g / l
its variablity; it depends partly on the algorithm used to
Chlor.
derive the fluorescence from the radiance spectrum and _=■2 5 (jg /l
partly on the actual variability of the fluorescence yield.
«
1 5 u g /l
The fluorescence yield depends on factors such as the 'E
5[ig/\
species composition of the phytoplankton population §
and the efficiency of its photosynthesis which, on the _
other hand, is a function, for example, of nutrient 2
condition and light climate. There is some evidence from _j
.4
field investigations that the inverse relationship between
fluorescence yield, calculated per unit of chlorophyll
400
500
6 00
700
800
concentration and per unit of irradiance, and the quan­
X [n m ]
tum efficiency of the photosynthesis process can be used
to determine the relationship between available light Figure 1. Calculated radiance spectra of the upward-directed
radiance just above the water surface for three different chloro­
and primary production (Topliss and Platt, 1986; Cham­
phyll concentrations with no fluorescence. They show a maxi­
berlin et al., 1990, see detailed discussion below). The mum in the spectral range 685 to 700 nm, although the fluor­
basic idea concerning remote sensing is retrieval of the escence term was switched off (fluorescence yield set to 0).
fluorescence yield from the radiance spectra by combin­ Furtherm ore, a red shift of the maximum can be observed with
ing the determination of chlorophyll concentration and increasing concentration.
fluorescence with the help of an inverse modelling
procedure. However, the investigation of the sunlightinduced fluorescence and its quantitative relationship to
photosynthesis is in its early stages. A t present, this goal
properties and sun elevation is shown in Figure 2. The
has not been achieved with respect to remote-sensing fluorescence peak clearly shows the shape of a Gaussian
data since a number of problems have still to be solved.
probability curve with a half-width of 25 nm. In order to
In this paper, the present state of remote sensing of simulate this spectrum with the radiative transfer model,
sunlight-stimulated fluorescence and its application to
a fluorescence yield of 0.35% had to be assumed, which
investigations of primary production will be summarized
corresponds to the mean value of other published fluor­
and discussed.
escence efficiencies (Giinther et al. , 1986). Both spectra
(Figs. 1 and 2) answer the question of this section: the
peak around 685 nm is caused by absorption and scatter­
ing as well as fluorescence; as a consequence, both
Can we observe natural fluorescence
effects have to be considered in retrieval algorithms.
A
within radiance spectra above the ocean?
M easured
Hudson C ruise
1 2 .5 .8 8
'g
/V\
Model
Gelb 0 .0 5 m "'[4 4 0 3
; U
£
1
Susp.M. l m g / l
N
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o
rH
There has long been a discussion whether the peak
around 685 nm in radiance spectra is caused by fluor­
escence or only by the absorption and scattering proper­
ties of pure water and phytoplankton (e.g., G ordon,
1979). Figure 1 shows radiance spectra which are ealeulated using a radiative transfer model with varying levels
of chlorophyll but with its associated fluorescence
switched off. It can clearly be seen that the peak which is
caused by scattering and absorption increases with increasing chlorophyll concentration, while its maximum
shifts to the red part of the spectrum. In order to verify
the true fluorescence peak in the upward directed radi­
ation spectrum, measurements of upwelling irradiance
have been carried out in depths of about 10 m, where
sunlight is nearly extinguished by pure water absorption
within the spectral range > 650 nm, so that all upward
directed radiation in this range has to be caused by
fluorescence if other minor effects such as Raman scat­
tering are neglected (Doerffer, 1992). Such a spectrum
together with the model simulation for the same water
Chlor. 7 (jg /l
n 0.35%
J"
'g
5
=
I
s—1
400
A
1
7
500
600
»j. .
700
800
XCnml
Figure 2. Upward-directed radiance spectrum in 10 m depth.
Measurement (broken line) off the Labrador coast, simulation
with a radiative transfer model (solid line) for the same concen­
tration of chlorophyll, suspended matter and gelbstoff as
measured. A fluorescence yield o f 0.35% was assumed.
106
I C E S m a r . Sei. S y m p .. 197 (1 993)
R. Doerffer
H ow to retrieve the fluorescence signal
from radiance spectra?
14
<
0cD
12
a
The fluorescence adds extra energy to the backscattered aœ
radiance which is leaving the water and in this way 1 8
r = 0.98
augments the radiance peak around 685 nm. This extra ua - <1%
6
radiance caused by fluorescence is denoted here F0. It is
not directly measurable because the water-leaving
22.4
17.6
14.4
4.8
11.2
8.0
radiance around 685 nm is composed of the backscat­
Chlorophyll a (fjg/I)
tered radiance, the fluorescence, and the radiance spe­
cularly reflected at the water surface. The common
Figure 4. Relationship between relative FL H , which was
procedure for retrieving the fluorescence from radiance
measured with a spectrom eter from 600 m altitude, and the
chlorophyll concentration, measured in 2 m depth, along a
spectra is to determine the fluorescence line height
profile of 90 km length in the Fladenground (North Sea) during
(FLH). This is calculated as the difference between the
FLEX'76.
radiance at 685 nm and the radiance of the baseline at
this wavelength. The baseline, on the other hand, is
constructed from the radiances at two spectral channels
tration of in situ samples by means of regression analysis.
in the neighborhood of the 685 nm peak, where the
O ne successful example from the early days of this
influence of phytoplankton chlorophyll by absorption
method is presented in Figure 4, which shows the re­
and fluorescence can be neglected (see Fig. 3). The
gression between FLH , measured from an aircraft with a
general FLH algorithm with two different baselines for
multispectral radiom eter at about 600 m altitude, and
A2 is:
the corresponding chlorophyll concentration in the
water at 2 m depth. The data were sampled during the
FLH = L(Af )
- -^f ) + L(A2)(Af ~ -^i )
spring plankton bloom in the northern N orth Sea (Fla­
Å2 ~ A-i
denground Experiment, FLEX 76), along a transect of
FLH = FI: A, = 645 nm, <l2 = 725 nm, AF = 685 nm
80 km length, as part of a one-month survey of the area
FLH = F2:
= 645 nm, A2 = 670 nm, AF = 685 nm
for studying the development of the spring bloom. The
high linear correlation and low scatter, which were
Variations in this procedure use non-linear baselines or
found also during other similar experiments, make it
calculate the difference between the radiance at 670 nm,
possible to use FLH for mapping the horizontal surface
i.e., at the absorption band of chlorophyll, and at 685
distribution of chlorophyll. In turbid coastal waters,
nm, i.e., the fluorescence maximum (F2). It has to be
F LH gives a much better representation of the chloro­
pointed out that the FLH is only an approximation of the
phyll concentration in the water than the blue/green
fluorescence energy, F0, which leaves the water surface
color ratio (Fig. 5). However, as will be shown later, the
(or a layer within the water column). To calibrate the
relationship between chlorophyll concentration and
FLH values, it is compared with chlorophyll concen­
FLH is valid for only a limited period and area.
8
Gelb 0 0 5 m "'C 4 4 0 ]
lm g / l
C hlor 2 5 p g /l
0 - T) 0.35%
The influence of other substances on
FLH
_ Susp.M .
a
6
2
$ 0.8
no FI.
Baseline
600
640
680
720
X[nm]
Figure 3. Simulation of a radiance spectrum with and without
fluorescence. The dashed line indicates the baseline as deter­
mined from the radiance at 650 and 720 nm, the dotted line the
"true” baseline, i.e., radiance without fluorescence.
Determinations of the FL H in various waters and at
different seasons have shown that the specific FLH (i.e.,
normalized to the downwelling irradiance and calcu­
lated per unit chlorophyll concentration) is not constant.
This variability is caused by a variable fluorescence
efficiency (which will be discussed later) and by factors
such as high concentrations of other water constituents
and an inhomogeneous vertical distribution of chloro­
phyll. One reason for the specific FLH variability is the
influence of gelbstoff and suspended m atter on the
absorption and backscatterance of the downwelling ir­
radiance and on the attenuation of the emitted fluor­
escence light. Gelbstoff attenuates solar energy in the
Estimation o f primary production by solar-stimulated fluorescence
I C E S m a r . Sei. S y m p ., 197 (1993)
(b)
2-1
0
107
1
-|--------------- ------------- ,--------- !—
o
i
e
Chlorophyll
12
lpg/l)
Chlorophyll
Ipg/l)
Figure 5. Relationship between (a) the radiance ratio L443/L552 of the upward-directed radiance just below the water surface and
the chlorophyll concentration and (b) between the FLH (F2) and the chlorophyll concentration. The radiances are calculated with
a Matrix O perator Radiative Transfer Model. The concentrations of chlorophyll, suspended matter, and gelbstoff were taken from
measurements in the Germ an Bight during the international Marine Rem ote Sensing Experiment M A R SE N ’79 (from GKSS
1987).
blue-green range of the spectrum, where chlorophyll
has its absorption maximum and its excitation maximum
for fluorescence. Thus, an increasing gelbstoff concen­
tration decreases the water leaving fluorescence energy,
F0, as well as the FLH. Suspended matter augments the
radiance in the red part of the spectrum by scattering,
which changes the slope of the baseline for FLH calcu­
lation. Furtherm ore, it attenuates the excitation energy
in the blue-green spectral range, an d , to a minor degree,
E
a.
uV)
N
I
0)
u
c
D
oK
V
u
o
3
00
yellow sub stan ce ab so rp tio n (l/m)
Figure 6. Calculated influence of gelbstoff absorption on the
water leaving fluorescence, F0, and fluorescence line height
FLH, F I, just below the water surface, chlorophyll concen­
tration 5 mg/m3 (from GKSS 1987).
the emitted light. The influence of both substances on F0
and FLH has been analyzed with radiative transfer
simulations by Fischer and Kronfeld (1990). Figure 6
shows the chlorophyll concentration as derived from F0
and FLH (denoted F I in the figure) as a function of the
absorbing influence of gelbstoff. O ne can clearly see that
the influence on F0 is stronger than on FLH . The reason
for the weaker influence on FLH is a compensation
effect. This is mainly caused by the different attenuation
of the radiances of the two baseline channels due to the
decreasing absorption of gelbstoff with increasing wave­
length. This partly compensates for the loss of fluor­
escence in FLH due to the attenuation of the excitation
energy and, as a minor effect, due to the absorption of
the emitted energy. Figure 7 shows the influence of
suspended m atter on the retrieved chlorophyll concen­
tration. The water-leaving fluorescence (F0) is only
weakly decreased by the attenuation of the excitation
and emitted energy, while the FLH ( F 1) increases due to
the backscatterance of suspended matter which aug­
ments the radiance of the two baseline channels and of
the fluorescence channel. Both simulations indicate that
the FLH method requires a correction for these sub­
stances at least in turbid coastal zone areas and estuar­
ies. But also a determination of F0 (which is not possible
directly) would require corrections.
A nother effect which can be observed is a red shift of
the radiance maximum when the chlorophyll concen­
tration exceeds about 15 mg/m3. This red shift is caused
108
R. Doerffer
I C E S m a r . Sei. S y m p .. 197 (1993)
0 3-
o.a-
0 00-1
00
.
1
1
20 0
,
40 0
1
SOO
.
1
1
00 0
100 0
suspended m a tte r (mg/1)
0
Figure 7. Calculated influence of suspended m atter on the
water leaving fluorescence, FO, and the fluorescence line height
FLH, F I, just below the water surface, chlorophyll concen­
tration 5 mg/m3 (from GKSS 1987).
when chlorophyll reabsorbs the emitted fluorescence at
its short-wave peak-wing (Dirks and Spitzer, 1987).
However, a radiance maximum around 685 nm which is
not caused by fluorescence will also be shifted by the
absorption of chlorophyll, as shown in Figure 1.
A nother cause for a variable chlorophyll-FLH re­
lationship is an inhomogeneous vertical distribution of
chlorophyll. The attenuation spectrum of pure water
with its minimum in the blue range and its steep increase
with increasing wavelength causes the signal depth to
vary also with wavelength. The signal depth is the depth
within which 90% of the water-leaving radiance orig­
inates. It is plotted for different types of water in Figure
8. A nother simulation shows the influence of the depth
of the phytoplankton layer on the water-leaving fluor­
escence (F0) as on the F LH (Fig. 9), the values of which
in this case are nearly identical. First of all, these figures
1
2
3
4
5
8
7
e
9
10
depth (m)
Figure 9. Fluorescence FO and FLH, F I, just below the water
surface depending on the depth of the phytoplankton layer,
simulation with a chlorophyll concentration of 5 mg/m3
(Fischer and Kronfeld, 1990).
show that the possibility for observing chlorophyll fluor­
escence is limited to about the first 5 m of the water
column. This means that the chlorophyll maxima in
greater depths are not observable. This is a severe
limitation of the method and restricts it to cases with a
well-mixed euphotic zone. Furtherm ore, the plot of
Figure 8 shows that the excitation depth for chlorophyll
fluorescence in the blue spectral range is much deeper in
clear ocean waters than the layer from which the fluor­
escence, as observed from above the surface, is emitted.
Thus, concentration gradients in the upper layer may
also modify the specific F0 and FLH when they are
normalized to the surface or depth-integrated chloro­
phyll concentration. A possible way to minimize this
effect is to integrate the absorption of chlorophyll at 670
nm in the evaluation procedure, which can be done by
using an inverse modelling technique (see later under
Inverse modelling procedure).
case II (3)
S -20
Variability of fluorescence yield
case I (2)
S . -30
CD
"O
15 -40
pure sea w a te r (1)
Ol
« -50-60
,4
,45
,5
,55
,6
,65
,7
,75
The most important source for the variability of the
fluorescence signal with respect to the determination of
primary production is the variability of the fluorescence
yield. In general this is defined as the ratio of the emitted
fluorescence energy to the energy absorbed by the
pigments. In the model calculations presented in this
paper it is defined in the following way:
w avelength [nm]
■700
Figure 8. Signal depth z90 of pure sea water ( l) ,o f w a t e r with a
chlorophyll concentration of 1 mg/m3 (2), and (3) of water with
concentrations: suspended m atter = 5 mg/1, chlorophyll = 5
mg/m3 and gelbstoff absorption at 380 nm of 1 m - 1 .
k =400
F„(A)dA
Ea„(A)dA
Estimation o f primary production by solar-stimulated fluorescence
I C E S m a r . Sei. S y m p .. 197 (1993)
with Fo the fluorescence energy emitted from the layer
dz and E a0 the scalar irradiance absorbed by the pig­
ments of the layer dz.
However, other definitions are also in use, such as the
ratio of the emitted fluorescence to P A R (Photosynthe­
tic Available Radiation). Figures of the fluorescence
yield in the literature are often based on different
definitions which are not always exactly represented;
this may be one reason for the wide span of values
ranging from 0.15% to 10% with a mean of 0.35%
(Günther et al., 1986). The variability of the fluor­
escence yield is caused by a number of factors, such as:
• short-term changes in illumination (daily cycle, verti­
cal transport, cloud coverage)
• long-term changes in light climate (season, changing
weather, formation of an upper mixed layer in re­
lation to the depth of the euphotic zone)
• nutrient conditions including the internal nutrient
pool
• species composition
A detailed discussion of the variability is given in R ab­
bani (1984). Details of the biophysics of the quenching
factors are discussed in an overview by Owens (1991).
For the question of remote sensing, the long-term
variations are of particular interest. Short-term light
variations are normally not of interest in this context,
since remote-sensing surveys are carried out under
cloudless sky and constant high sun elevations. This
experience is reflected in Figure 10, which shows mean
regression slopes of the chlorophyll-FLH relationship of
different flight experiments on nine different occasions
109
from 1975 to 1982, all but one in western Canada coastal
waters (British Columbia). These are:
Period o f experiment
16 A pr 1975
Jun/Jul 1976
1-8 Jun 1976
23-26 Jul 1979
7-10 Aug 1979
11 Aug 1979
25 Jun 1981
Jul/Aug 1981
27 A pr 1982
Line
a
b
c
d
e
f
g
h
i
Location
B. C. Saanich Inlet
B. C. Saanich Inlet
B. C. Saanich Inlet
B. C. Coastal inlets
B. C. West coast
B. C. West coast
B. C. West coast
B. C. Coastal inlets
Baltic Sea
The fluorescence line heights were calculated from
reflectance spectra. No corrections for suspended m at­
ter or gelbstoff were performed. From the available
data, these slopes are constant for an area for a period of
some days or weeks (Gower, 1986).
The influence of changing daylight on the fluor­
escence efficiency during the course of a day (due to
changing sun elevation) was also examined by Doerffer
and Fischer (1987). Measurements of the water-leaving
radiance of the same water body were carried out during
one day and the derived fluorescence was compared
with corresponding model simulations assuming a con­
stant fluorescence efficiency. The resulting constant
relationship between concentration and fluorescence is
shown in Figure 11. This result is also confirmed by a
simulation with a photosynthesis-fluorescence model
(Günther, 1984), which shows a constant yield when the
irradiance exceeds a value of 200-300 W/m2.
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200
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o
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o-j
2.0
---------
1--------- ---- ------------------ 1----------------- 1
15
3.0
C hlorophyll [m g
15
20
CHLOROPHYLL a
25
mg.m ^
Figure 10. Mean relations between fluorescence and chloro­
phyll concentration observed on nine occasions at different
experiment sites, see text (Gower, 1986).
3.5
4.0
m-3]
Figure 11. Comparison of measured (solid line) and calculated
(dashed line) fluorescence values determined at different sun
elevations during a one-day observation. The radiative transfer
calculations use the measured chlorophyll and suspended mat­
ter concentrations as well as the measured gelbstoff absorption
coefficient and observed solar zenith angles (Doerffer and
Fischer, 1987).
110
R. Doerffer
I C E S m a r . Sei. S y m p ., 197 (1993)
The influence of the atmosphere
One further problem which has to be analyzed particu­
larly for satellite remote sensing is the influence of the
atmosphere on the small fluorescence signal. The re­
lationship between the water-leaving radiance at the top
of the atmosphere to the total signal is plotted in Figure
12. The plot shows that the radiance which is backscattered by the atmosphere exceeds 90% of the total
radiance at the top of the atmosphere. Thus, a degra­
dation of the signal/noise ratio has to be considered.
However, since the fluorescence channels are located in
the red part of the spectrum close to the spectral chan­
nels used for atmospheric correction, a higher accuracy
of the atmospheric correction can be expected for the
fluorescence channels than for the blue/green spectral
channels, which are used for determining the chloro­
phyll absorption. A nother problem is the strong absorp­
tion bands of oxygen and water vapor in the spectral
range between 688 and 740 nm. These may also cause a
variable attenuation of the fluorescence signal and/or of
the “right” baseline channel, depending on air pressure
and humidity. The influence of these absorption bands
(Fig. 13) has been analyzed by Fischer and Schlüssel
(1990). To minimize the perturbation of these atmos­
pheric gases, it is necessary to place the observation
channels precisely at the appropiate positions of the
spectrum and to keep their spectral bandwidths suf­
ficiently small, either by design of the instrument or, in
the case of an imaging spectrometer, by programming
the spectral channels. In addition, a careful atmospheric
correction is a prerequisite for the retrieval of the small
fluorescence signal from the radiance spectrum at satel­
lite altitude.
L to t
z ToA
sun o 50°
Gelb 0 .0 5 r r f '[ 4 4 0 ]
Susp M l m g / l
Chlor 7 |jg /l
Latm
1 25
L*
1
0 .6 0
1 1 1
0 .6 2 0 .6 4
,- T -
0 .6 6
' 1" ■ '
0 .6 8
1
0 .7 0
FLH 0 9
'
1 ' ---1---
0 .7 2
0 .7 4
Figure 12. Radiance spectra with and without fluorescence. L*
is the water leaving radiance at the top of the atmosphere
(T O A ), Ltot is the total radiance as seen by the sensor, both
lines are shown with and without fluorescence, and Latm the
contribution by the atmosphere (atmospheric path radiance).
60
50
H20
g
co 40
f) 30
X
** 20
chlorophyll
absorption fluorescence]
6 0 8 62 4 6 4 0 656 672 688 70 4 720 736 752 768 78 4
Wavelength (nm)
Figure 13. Calculated gaseous absorption (in % ) in a vertical
path through the total atm osphere containing 10 g cirT2 water
vapour in a vertical column. The spectral positions of absorp­
tion bands and intervals for 18 H 20 and three 0 2 absorption
bands are also indicated as well as the relative chlorophyll
absorption band around 670 nm and the fluorescence band
around 685 nm (Fischer and Schlüssel, 1990).
Inverse modelling procedure
In order to determine the fluorescence yield from the
radiance spectrum, it is necessary to retrieve the fluor­
escence energy as well as the pigment concentration.
Not only phytoplankton pigments but also suspended
material and gelbstoff attenuate the downwelling sun­
light and the backscattered upward directed radiance
and fluorescence; therefore the concentration and the
optical properties of these substances have also to be
taken into account. One method of including all of these
influences in the evaluation procedure is inverse model­
ling. This optimization technique requires a model for
simulating the radiative transfer process in atmosphere
and ocean and a search algorithm. Within the optimiza­
tion loop, the variables, i.e., the concentrations, the
fluorescence yield, and the atmospheric path radiance,
are modified until a minimum in deviation between the
modelled and measured radiance spectrum is achieved.
The scheme of the procedure is sketched in Figure 14.
For the evaluation of satellite or aircraft scanner scenes,
with their large am ount of data, the radiative transfer
model has to be formulated as simply as possible in order
to keep the computing time within the range of a couple
of hours. The inverse modelling m ethod has been suc­
cessfully applied to Coastal Zone Colour Scanner
(CZCS) scenes of the North Sea for mapping the distri­
bution of chlorophyll, suspended matter, gelbstoff, the
signal depth, and the aerosol path radiance (Fischer and
Doerffer, 1987; Doerffer, 1990). The agreement be­
tween mean values and histograms of these maps with
Estimation o f primary production by solar-stimulated fluorescence
I C E S m a r . Sei. S y m p .. 197 (1993)
model parameters
initial values for
concentrations
simulate
■Rayleigh corrected
radiances
search for
better concen­
trations
no
imaging spectrometer
calibrated radiances
calculate
■Rayleigh corrected
radiances
compare
simulated with
measured rad.
o.k.
found
optimum
concentrations
Figure 14. Scheme of the inverse modelling procedure.
ship data of the same area and period is within the
accuracy-range of in situ measurements. Besides
measurements of the specific optical properties (absorp­
tion and backscattering coefficients), no ship data were
used for fitting the evaluation procedure. Experiments
with different starting values in the optimization loop
have shown that the solution was always unique within
the accepted error range. The extension of this pro­
cedure for including fluorescence has been proposed
(Doerffer, 1992) but not tested so far with real data. The
inverse modelling procedure does not require a baseline
calculation since the fluorescence peak (FO) and not the
F LH is calculated by the model. The inclusion of the
fluorescence in the inverse modelling procedure opens
two different applications: with a fixed fluorescence
yield in the model, the calculation of chlorophyll con­
centration is determined by its absorption bands and its
fluorescence energy; this combination helps to improve
the discrimination of chlorophyll and gelbstoff in waters
with high gelbstoff concentrations. The other possibility
is to use the fluorescence yield as a variable in the model
in addition to the chlorophyll concentration in order to
calculate the actual chlorophyll fluorescence yield. In
the latter case, the concentration is determined by the
absorption and scattering properties only. The fluor­
escence yield is then the key to improving the determi­
nation of primary production as described below.
Fluorescence yield for determining
primary production
The solar energy which is absorbed by the pigments of
the phytoplankton cell can be released in different ways.
Of course, the most im portant one is the transformation
into chemical energy by photochemical reactions. The
111
surplus in absorbed energy is quenched in the form of
heat or fluorescence. In addition, other regulatory pro­
cesses are important, such as adaptation and photoinhi­
bition.
Since fluorescence is a mechanism for releasing unus­
able absorbed energy, an inverse relationship exists
between the quantum efficiency of photosynthesis, <p,
and the fluorescence yield, r], which can be simply
formulated as
(f>~ \lr\
The key to converting observed fluorescence into quan­
tum efficiency and, furthermore, into primary pro­
duction is the knowledge of the relationship between
fluorescence yield and quantum efficiency of photosyn­
thesis, which is not necessarily linear. U nder laboratory
conditions a wide range of coefficients describing this
relationship can be produced experimentally by chang­
ing species, light, and nutrient conditions, for example.
The main question here is, how variable is this relation­
ship under “normal” remote-sensing conditions (i.e.,
with respect to illumination conditions which allow re­
mote sensing). Only little experience exists from field
investigations and hardly any attem pt has been made to
use remote-sensing spectrometer data.
The possibility of determining primary production
from in situ measurements of natural solar-stimulated
fluorescence was examined by Topliss and Platt (1986)
during a cruise in the Labrador Sea and Baffin Bay. They
used an underwater spectral irradiance meter to
measure the up welling quanta irradiance. The relative
fluorescence yield was then compared with alpha, the
initial slope of the PI curve, which was determined at the
same time (see Fig. 15). The result of this investigation
confirms the inverse relationship and demonstrates that
it is possible to determine alpha from measurements of
n a tu r a l flu o re s c e n c e . A n o t h e r su ccessful in v e s tig a tio n
concerning this question was carried out by Chamberlin
et al. (1990), who studied the relationship between
natural fluorescence and photosynthesis in several en­
vironments, including the central South Pacific, the
western Sargasso Sea, and two sheltered bays. The
concentration range of chlorophyll was 0.03-4.36 mg/
m3. The results of 76 such measurements between 2 and
150 m depth and covering a 1500-fold range in pro­
duction indicate that photosynthesis is highly correlated
with natural fluorescence (see Fig. 16). The results give
cause to expect these relationships also from remotely
sensed data of fluorescence yields. A simulation of
radiances at the top of the atmosphere for different
fluorescence yields shows that it should be possible to
retrieve the fluorescence yield even from satellite
measurements of radiance (Fig. 17).
112
R. Doerffer
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1
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(£ )
10
1000
100
P re d ic te d P ro d uc tio n [ngA-C m-J s->]
0
1
2
3
4
5
6
ij(W ) ( arbitrary umts )
7
8
Figure 15. Plot of photosynthesis efficiency, alpha, vs fluor­
escence efficiency using total energy with error bars (Topliss
and Platt, 1986)/
Conclusions
Remote sensing of natural, sunlight-induced fluor­
escence of chlorophyll has proved to be a useful tool for
mapping the horizontal distribution of phytoplankton in
a num ber of aircraft experiments. It is an important
alternative to color-ratio algorithms particularly for
water types which contain high concentrations of gelb­
stoff and suspended matter. Natural fluorescence, de­
termined as the fluorescence line height (FLH) of the
water-leaving radiance spectrum, is a param eter which is
much more specific to chlorophyll than color ratios. The
relative accuracy of the method is comparable to the
chlorophyll determination from water samples for con­
centrations > 1 mg/m3.
However, there are some restrictions which have to be
considered. The most im portant one is the limitation of
the signal depth to about 5 m because of the high
attenuation of red light by pure water. This limits the
application to conditions with well mixed waters where
the upper layer represents the chlorophyll concentration
of the euphotic zone. Factors which change FLH other
Figure 16. Measured photosynthesis vs predicted photosyn­
thesis using measurements of fluorescence, vertical attenuation
coefficient, and downwelling irradiance (Chamberlin et al.,
1990).
than fluorescence itself are high concentrations of sus­
pended m atter and/or gelbstoff. However, these factors
are automatically taken into account if one uses an
inverse modelling procedure in which not FLH but the
total fluorescence energy can be calculated.
Field investigations have shown that the fluorescence
yield, as determined with a radiance spectrometer from
z ToA
sun o 5 0°
Gelb 0 .0 5 m ~ '[4 4 0 ]
Susp.M . l m g / l
T
E
12
Chlor 7 (jg /l
|
1| | :.
n o. 1-0.6%
E
£
6 85nm
0
600
640
680
720
XCnm]
Figure 17. Simulated radiances at the top of the atmosphere
for different fluorescence yields from 0.1 to 0.6% with 0.1%
intervals.
ICES mar. Sci. Syrap.. 197(1993)
Estimation o f prim ary production by solar-stimulated fluorescence
above the water surface, is constant at least for a number
of days or weeks and for an area with similar conditions
with respect to the nutrient availability, state of phyto­
plankton development, and composition of the popu­
lation. In these cases the chlorophyll concentration can
be deduced with the FLH algorithm with an accuracy
which is comparable to that of in situ samples. For
calculation of primary production, the fluorescence can
be used in two different ways. One way is to determine
just the chlorophyll concentration from the fluorescence
in addition to the blue/green radiance ratio and then
follow the protocol developed by Platt and Sathyendranath (see Sathyendranath and Platt, this volume); the
other way includes the determination of the fluor­
escence yield for determining parameters of the
production/light relationship (PI curve) for its use in the
primary production model. In waters with high concen­
trations of suspended matter and gelbstoff, this requires
an inverse modelling procedure for deriving simul­
taneously the chlorophyll concentration, the energy
emitted by fluorescence, and the attenuation of sunlight
and fluorescence caused by other substances. Although
the inverse modelling technique has been successfully
tested with data of aircraft scanners and with Coastal
Zone Color Scanner data, no field experience exists so
far with its extension to include fluorescence. However,
investigations with in situ spectrometers have proven
that primary production can be derived from sunlight
stimulated fluorescence with an accuracy which is com­
parable to conventional techniques. In order to decide
to what extent the fluorescence yield derived from
remotely sensed radiance spectra can be used for deter­
mining primary production, investigations with airborne
high resolution spectrometers, imaging spectrometers,
and simultaneous observations from ships are necessary.
In the event of a success, this method would reduce the
high number of in situ measurements of parameters of
the light-photosynthesis relationship (PI curve) which
are presently necessary to determine primary pro­
duction from satellite data. Future spaceborne imaging
spectrometers, capable of measuring the sunlight stimu­
lated chlorophyll fluorescence, may give a new perspec­
tive in studying seasonal and spatial patterns of primary
production on a global scale.
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H . , and Murphy, R. C. 1990. Evidence for a simple relation­
ship between natural fluorescence, photosynthesis and
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Dirks, R. W ., and Spitzer, D. 1987. O n the radiative transfer in
the sea, including fluorescence and stratification effects.
Limnol. O ceanogr., 32(4): 942-953.
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Doerffer, R. 1981. Factor analysis in ocean color interpre­
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