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Underwater light characterisation for correction of remotely
sensed images
EVANTHIA KARPOUZLI{, TIM MALTHUS{, CHRIS PLACE{,
ANTHONY MITCHELL CHUI{, MARTHA INES GARCIA{and
JAMES MAIR§
{Department of Geography, University of Edinburgh, Drummond St,
Edinburgh EH8 9XP, Scotland, UK; ?e-mail: e.karpouzli@hw.ac.uk
{Corporation for the Sustainable Development of the Archipelago of San
Andres, Old Providence and Santa Catalina-CORALINA, San Andres Island,
Colombia
§Department of Civil and Offshore Engineering, Heriot-Watt University,
Edinburgh EH14 4AS, Scotland, UK
Abstract. Objective measurement of habitat change using remote sensing
requires processing of the images to enhance the bottom reflectance signal. This
process typically uses correction techniques to remove the influence of the water
column on bottom reflectance, and to enable the accurate correction of the
imagery for varying bathymetry. Such correction measures depend on reliable
estimates of water column light attenuation.
An investigation into the spatial variation in attenuation in a typical tropical
region was undertaken. Measurements of gross spatial variations in downwelling
attenuation around San Andres and Old Providence islands in the western
Caribbean were made using a PAR sensor. Measurements of specific attenuation
were also made for blue, green and red light using filters fitted to the sensor.
High spectral resolution attenuation measurements were also made using a
spectroradiometer. Results showed a four-fold variation in light attenuation in
shallow littoral regions alone. Spectral attenuation measurements suggested that
this variation was largely the result of scattering by particulate matter rather
than varying concentrations of dissolved yellow substances.
These findings suggest that the results of studies where single measurements of
‘average’ attenuation have been used to depth-correct remotely sensed imagery
should be interpreted with a high degree of caution. The paper goes on to show
that simple models can be empirically obtained where attenuation can be
spatially predicted with confidence, based on the variables of water depth,
distance to and size of mangrove beds, and distance to and size of towns. The
models obtained showed high statistical significance, with 89% and 78% of the
spatial variation in attenuation explained for San Andres and Old Providence,
respectively. It is postulated that the use of such approaches for the estimation of
attenuation will lead to more accurate depth correction and hence improved
interpretation of remotely sensed imagery for littoral regions.
International Journal of Remote Sensing
ISSN 0143-1161 print/ISSN 1366-5901 online #2003 Taylor & Francis Ltd
http://www.tandf.co.uk/journals
DOI: 10.1080/0143116031000066972
Presented at the Remote Sensing of the Marine Littoral Environment Meeting, Linnean
Society, London, 15–16 December 1999.
INT.J.REMOTE SENSING, 2003, VOL. 24, NO. 13, 2683–2702
1. Introduction
Optical remote sensing offers a non-invasive technique with which to rapidly
monitor changes in the cover and health of submerged habitats. However, its full
potential is still to be exploited in littoral environments, where the strong attenuating
influence of the water column has been a limiting factor. A combination of optical
properties in the water column (absorption, scattering) results in a significantly reduced
and spectrally altered bottom reflectance. This impact gets greater with increasing
depths and with waters of greater turbidity (Spitzer andDirks 1987, Gould and Arnone
1998). To extend the potential of optical remote sensing in littoral applications, such as
for monitoring coral reef health and for qualitative and quantitative monitoring of
seagrass habitats, the influence of the water column must be removed from the remotely
sensed image. Such a process also significantly improves the accuracy of classification
of such habitats (Mumby et al. 1998).
Despite the existence for some time of a number of algorithms for correcting for
water column depth and turbidity effects (e.g. Lyzenga 1978, 1981, Moussa et al. 1989,
Bierwirth et al. 1993), few studies of tropical marine habitats attempt such correction
techniques before classification. Mumby et al. (1998) reported only four studies out of
forty-five (9%) that attempted such pre-processing methods and concluded that
authors were generally unaware of such correction methods.
In order to address the confounding influence of the water column in images of
the littoral zone, a knowledge of water depth and the local light attenuation (Kd)is
necessary. Few studies have used independently acquired estimates of attenuation,
with most extracting Kdvalues for relevant bands directly from their imagery in
areas of uniform bottom type (e.g. sand) and known depth (e.g. Lyzenga 1981,
Bierwirth et al. 1993). Nearly all of these studies assume that Kdvalues extracted
for one area can be applied to other regions. However, it is likely that attenuation
in the tropical littoral zone spatially may be highly variable. Green et al. (2000)
acknowledge this fact with their recommendation to segment images into regions
with different water quality for separate water column correction. However, this
idea has not yet been tested. This paper reports the first attempt to investigate the
nature of the spatial variation in water column attenuation for a tropical littoral
region and infers its potential influence on calculated bottom reflectance.
2. Study site description
This study focuses on the littoral habitats of the Archipelago of San Andres,
Old Providence and Santa Catalina, Colombia, an expanse of 300 000 km2isolated
within the western waters of the Caribbean Sea, approximately 180 km east of the
Nicaraguan coast and 800 km north-east of the Colombian coast (figure 1). Its two
main islands are: San Andres (12‡34’N; 81‡43’W), and Old Providence (13‡22’N;
81‡23’W). The archipelago is surrounded by trenches and faults of very deep water
of the order of 2–3 km. Both islands are located on the tectonic fracture of the
Lower Nicaraguan Rise and have a similar volcanic history but San Andres does
not exhibit the later volcanic reactivation observable in Old Providence (Geister
and Diaz 1996).
Significant increases in the human population migrating to San Andres from the
1950s through to the 1980s saw a dramatic rise in population from 5675 inhabitants
in 1952 to around 80 000 by 1992, making it the most densely populated island in
the whole of the Caribbean (Vollmer 1997). Still today San Andres is by far the
E. Karpouzli et al.
2684
most developed island of the archipelago and a major Colombian national tourist
destination.
San Andres has a smooth topography and an area of approximately 27 km2.A
series of hills runs the length of the island not exceeding 90 m in elevation. The main
extent of its platform is to the east and north-east of the island bordered by a barrier
reef with depths ranging between 1m and 15 m before dropping rapidly to over 1000m
at the edge of the platform. The lagoonal area behind the reef receives some input of
diffuse organic pollution since most urban development is concentrated in the north
Figure 1. Map showing location of the islands of San Andres and Old Providence in the
south-western Caribbean Sea.
Remote Sensing of the Coastal Marine Environment 2685
end of the island in the town of San Andres, along with the main harbour, the airport
and a number of hotel resorts. Census data from 1990 indicate that over 70% of the
population lives in this northern sector of the island (Diaz et al. 1995). The lagoon
enclosed by the barrier reef to the north-east has a limited influence from the open sea
and relatively calm waters. The municipal sewage system currently only covers 8% of
the island, and is diverted to the west coast where the platform is much narrower and
plunges steeply to deep waters. The remainder is handled by septic tanks — most of
which do not meet technical specifications and leach effluent rapidly into the sea
through the porous limestone substrate, and direct discharge into the sea and gullies
(M. W. Howard, 2000, personal communication).
In contrast to San Andres the more recent volcanic history of Old Providence has
given rise to a slightly smaller island (18 km2) but with a mountainous landscape (peak
at 330 m) and a number of small and often ephemeral fresh-water streams that flow
down to the coastline. Flat land is scarce and is where the main settlements can be
found, its population today is still under 4500 inhabitants. The platform surrounding
Old Providence is more extensive at between 5m and 10 m depth. To the north, it
extends for 60 km with the second longest barrier reef in the Caribbean bordering its
eastern side. The substrate is finer darker silty sand comparing with the white coarse
sediment of coraline origin of the platform around San Andres.
The typical submerged habitats found around both islands are seagrass (mainly
Thalassia and Syringodium genera) and algal beds in different proportions, soft and
hard coral habitats, as well as sandy and rocky substrates. A number of mangrove
habitats of different sizes are also scattered around the coastlines of both islands, which
represent an extra source of natural eutrophic waters. The effects of increased tourism,
population growth and uncontrolled development to both islands in recent years but
mostly to San Andres have had a significant effect on the clarity of the surrounding
waters as they have been receiving increasing inputs of organic pollution and increased
boat traffic. Old Providence has also been subject to recent deforestation of the
hillsides, particularly from cattle raising which may have caused increased sedimenta-
tion through the stream outflows.
3. Methods
3.1. Broad-band irradiance measurements
Measurements of gross spatial variations in downwelling PAR attenuation at
stations around both San Andres and Old Providence islands were made using a
submersible PAR cosine quantum irradiance meter (Macam model Q203 PAR,
sensor 5638). In addition to broad-band PAR measurements, profiles of specific
attenuation were also made for red, green, and blue light using filters fitted to the
sensor closely matching the three visible bandwidths of the Landsat Thematic
Mapper2sensor. The sensor was fixed facing upwards on a weighted lowering
frame and lowered below the water surface. Measurements were made at 1 m, 0.5 m
or 0.25 m intervals to a maximum of 10 m depending on the depth and degree of
attenuation of the water column. In that way a vertical profile comprising typically
ten measurements was produced for each station. Measurements were referenced to
above-surface incident irradiance using an identical continuously logging PAR
cosine sensor on deck to correct for fluctuations in surface incident flux due to
drifting clouds. An electronic damping circuit, part of the submersible meter, was
also used to temporally average the readings, to smooth out rapid fluctuations in
E. Karpouzli et al.
2686
irradiance intensity produced by wave action. All measurements were made
between 10:00 and 15:00 hours local time each day, to minimise solar angle effects.
The measurements were made at selected sites chosen around San Andres, and
Old Providence after dividing up the coastal zone into arbitrary ‘optical zones’ and
ensuring that at least one sampling site was contained in each. The division was
made from estimates of the optical properties of the water column from Secchi disc
depths that are routinely carried out by the collaborating institution CORALINA,
the natural resource management agency that represents the Colombian national
environment system (SINA) in the Archipelago. Measuring site positions were
located to an accuracy of less than 4 m using a differential global positioning
satellite (GPS) system.
The first set of PAR measurements (AS1–AS25 and AP1–AP18) took place over a
one-month period (first collection period-A) from 16 April 1999 to 14 May 1999.
During that period (A) a total of 25 profiles (AS1–AS25) of downwelling PAR
irradiance were measured around San Andres and 18 around Old Providence (AP1–
AP18). A second set of 21 PAR measurements were carried out in San Andres a few
weeks later (BS1–BS24) during the period 6 June 1999 to 23 June 1999 (second
collection period – B). The second set of PAR measurements around San Andres (B)
included a number of sites that were also sampled during the first collection period (A)
which allowed for comparisons of temporal changes in attenuation. Pairs of stations
within 300 m distance from each other were considered to be the same site, and
subsequently 11 pairs of measurements were compared. These stations, in close
proximity, were used to test the hypothesis that temporal factors did not influence the
Kd(PAR) measurements, at least within the time frame that this study took place. To
test this a paired-sample t-test was carried out for the 11 paired stations around San
Andres.
A set of band-specific measurements using the red, green and blue filters were
made around San Andres during the second collection period (B) at most stations
at which PAR measurements were made. A set of band-specific downwelling
measurements was also made around Old Providence and Santa Catalina Islands
between 25 May 1999 and 2 June 1999.
For all downwelling measurements, the diffuse vertical attenuation coefficients
(Kd) were calculated as the linear slope coefficient of the logarithm of downwelling
irradiance (of PAR, red (R), green (G), or blue (B) bands) with respect to depth
(Kirk 1994). The majority of regressions between ln-irradiance and depth gave R2
values of 0.95 or above. Poor linear relationships were omitted.
3.2. Spectral measurements
In conjunction with the first set of PAR measurements, high spectral resolution
attenuation measurements were made at selected sites around San Andres and Old
Providence during the first collection period. All spectral measurements were made
using a GER 1500 spectroradiometer system comprising of two radiometers linked
to a notebook computer. The GER 1500 is a rapid scanning radiometer, using a linear
photodiode array to measure radiance over the visible to near-infrared wavelength
range (300–1100 nm) with a nominal dispersion of 1.5nm and resolution of 3 nm.
One radiometer sensor head was fitted with a 4 m fibre optic probe and cosine-
corrected sensor and used to make measurements of incident downwelling irradiance.
The cosine-corrected sensor was fixed on a lowering frame and, while kept horizontal,
Remote Sensing of the Coastal Marine Environment 2687
was lowered and triggered at 0.5m intervals down to 2.5m below the water surface.The
second sensor head was fitted with a 15‡field-of-view receptor and was used to
reference the downwelling measurements to above-surface incident irradiance reflec-
tance from a calibrated Spectralon2reflectance panel. Both instruments were triggered
simultaneously in dual field-of-view mode using the notebook computer, thus
obtaining pairs of target and reference measurements.
3.3. Laboratory analysis
Samples of 5 l of water from ten sites in San Andres and two of 4l from Old
Providence were collected and filtered though Whatman GF/C glass fibre filters under
low vacuum and stored until analysis for determination of absorption by aquatic
humus (dissolved colour). After transportation to the UK these samples were further
filtered through 0.2 mm membrane filters and the absorption of the filtrate determined
at 380 nm in a Perkin-Elmer Lambda 40 spectrometer using 10 cm pathlength cuvettes
and a reference of distilled water.
In addition to aquatic humus absorption measurements, the samples were also
analysed for chlorophyll concentration (performed on site). Particulate matter was
collected on Whatman GF/C filters, the pigments were extracted using boiling
ethanol and absorption of the extract measured in a spectrophotometer, following
the method of Moed and Hallegraeff (1978).
3.4. Predictive models for spatial estimation of attenuation
The construction of simple models to predict spatial variation in attenuation was
attempted for the separate San Andres and Old Providence attenuation datasets. A
number of predictor terms were considered and their significance to Kdtested using
stepwise multiple regression, performed using the Systat2software package. Terms
were validated by being added and removed from the analysis to lead to an optimal
subset of variables that gave the best possible regression equation. The predictor terms
that were considered are listed below.
.Water depth (Dor 1/D) – the depth of the water column at each sampling
station, measured during sampling using a hand-held echosounder.
.Influence of mangroves (MA/LMor MA/LM2) – a cumulative predictor
hypothesized to influence Kdas a factor of mangrove bed surface area (MA)
and their distance from the sampling stations (LM). In the absence of detailed
information on current directions around the islands it was assumed that all
mangroves on the coast facing the particular station would have some
influence on it. Thus, sampling stations were divided into east or west groups
and only the east coast mangroves were considered to have an effect on the
east-lying stations and the contrary for the west-lying stations.
.Influence of major towns (TA/LTor TA/LT2) – In the absence of detailed
population estimates for the different towns or of waste water volumes from
different sources, the area of the settlements (TA) and their distance from the
sampling stations (LT) was used to form this cumulative predictor. As for the
mangroves, only those coastal towns on the east or west coasts were considered,
depending on the particular location of the sampling station.
.Influence of river and sewage outlets (1/LRor 1/LR2) – a cumulative predictor
E. Karpouzli et al.
2688
estimated assuming that their influence on Kdis inversely related to their distance
(LR) from a particular sampling station. The predictor was then the sum of the
inverse distances from the outlets to the given sampling point or the sum of the
distances squared. Again, only east or west outlets were considered, depending on
sampling station location.
4. Results
4.1. Analysis of water samples
The water sample analysis revealed very low aquatic humus concentrations for both
islands (table 1). The highest measurement (0.1 m{1) was found to be Station AS8 at
the outflow of the largest mangrove bed of San Andres island (mangrove Bahia
Hooker), followed by station AS7 off the main port (figure2). Absorption by aquatic
humus in these islands is high compared to values for other Caribbean and tropical
regions reported by Kirk (1994), although most of those reported are for more open
oceanic waters.
Similarly, chlorophyll concentrations showed very low pigment concentrations
ranging from 0.13 mg m{3, at station AS5 north of the port of San Andres, to
0.98 mg m{3at station AP5 off Santa Catalina harbour on Providence (figures 2 and
3). In general, the highest values for San Andres were found at stations AS11, AS23,
AS24 and AS4 which were located near mangrove Bahia Hooker, off a sewage outlet
and by coastal tourist developments, respectively. Surprisingly, comparatively lower
concentrations of chlorophyll were found at station AS7 off the main port of San
Andres while the same station showed high absorption by aquatic humus (figure 2).
From a total of 11 samples taken in May and September 1992, Diaz et al. (1995) found
chlorophyll concentrationsaround San Andres ranging from 0.013–0.492 m2698g m{3.
Although the chlorophyll measurements of both Diaz et al. (1995) and this study
are limited in number, they may indicate a slight increase in chlorophyll
concentration around the island over the seven-year period.
Both Providence stations showed overall higher pigment concentrations but
lower concentrations of aquatic humus when compared to San Andres. Overall, the
Table 1. Concentrations of aquatic humus and chlorophyll from a number of sites around
San Andres and Old Providence islands.
Station Collection date
Total pigment
(mg m{3)
Aquatic humus absorption
at 380 nm (m{1)
San Andres
AS20 16 April 1999 0.21 0.069
AS21 16 April 1999 0.29 0.091
AS22 16 April 1999 0.30 0.075
AS23 16 April 1999 0.40 0.035
AS24 16 April 1999 0.36 0.043
AS1 19 April 1999 0.30 0.046
AS4 19 April 1999 0.36 0.063
AS5 19 April 1999 0.13 0.056
AS7 19 April 1999 0.18 0.100
AS8 19 April 1999 0.90 0.160
Old Providence
AP5 28 April 1999 0.98 0.080
AP11 28 April 1999 0.68 0.079
Remote Sensing of the Coastal Marine Environment 2689
Figure 2. Variation in measured PAR attenuation (Kd) in coastal waters around the island
of San Andres. Sampling stations marked A denote first sampling period, B second
sampling period.
E. Karpouzli et al.
2690
measurements for both islands suggest waters of high transparency but indicate
localised eutrophication effects.
4.2. Downwelling PAR measurements – temporal variations
Table 1 compares the Kdvalues for the first collection period stations (A) that
were re-visited during the second collection period (B). Their locations are shown in
figure 2.
Figure 3. Variation in measured PAR attenuation (Kd) in coastal waters around the island
of Old Providence during the first sampling period.
Remote Sensing of the Coastal Marine Environment 2691
No consistent pattern in variation in attenuation is evident, although differences
do exist at some stations. The results of a paired-sample t-test on the data indicated
no significant consistent differences due to sampling period (n~11, t~20.511,
pw0.05). The power of the test for detecting a true difference of at least 0.05 m{1in
Kdat the revisited stations was 0.98; thus 98% of the time such a difference would
be detectable using a sample of 11 stations at a significance level of 0.05. Therefore,
differences between stations were considered to be more due to spatial as opposed
to temporal variation in light attenuation. Subsequent analysis of the dataset
treated all the data combined, irrespective of sampling period.
4.3. Downwelling PAR measurements – spatial variations
Tables 3 and 4 present a comparison of the calculated downwelling diffused
attenuation coefficients for PAR (Kd) at the different sampling stations around the
two islands, along with the depth of the euphotic zone (Zeu) for each site, the latter
estimated as the depth of penetration of 1% of sub-surface irradiance light level.
Spatial variation in Kdaround the islands is also shown in diagrammatic form in
figures 2 and 3.
Attenuation around San Andres ranged from 0.05–0.57 m{1, corresponding to a
range of depth in the euphotic zone of 102m down to 8.1 m. The highest attenuation
was measured at locations closest to the port, the mangrove areas and nearest to the
developed coastline by the major towns. The lowest attenuation values were found off
the north-west coast and at the southernmost point of the island (figure 2).
Similarly, for Old Providence attenuation ranged from 0.06–0.38 m{1, correspond-
ing to variation in euphotic zone depths of 74.2 m down to 12.1 m. The greatest
attenuation was measured near the harbour by the town of Santa Isabel and along the
west coast of the island where most of the tourist development, made up of small inns
and cabins, is found (figure 3).
4.4. Downwelling waveband-specific measurements
Along with the PAR profiles for San Andres collected during the second data
collection period (B), 22 band-specific profiles (BSF1–BSF25) were obtained using
Table 2. Comparison of Kd(PAR) values for revisited stations around San Andres island
corresponding to those shown in figure 2.
Date Station Kd(m{1) Station Kd(m{1)
13 May 1999 AS2 0.139 BS4 0.110
16 April 1999 AS23 0.081 BS22 0.130
16 April 1999 AS22 0.193 BS21 0.139
16 April 1999 AS21 0.161 BS19 0.108
22 April 1999 AS19 0.088 BS18 0.113
22 April 1999 AS19 0.088 AS20 0.045
14 May 1999 AS17 0.299 BS12 0.287
15 June 1999 BS13 0.249 BS12 0.287
14 May 1999 AS14 0.262 BS9 0.304
7 June 1999 BS3 0.157 BS2 0.153
14 May 1999 AS9 0.272 AS8 0.292
E. Karpouzli et al.
2692
Table 3. Values of Kdand depth of euphotic zone for stations around San Andres island
during the first and second collection periods (A and B).
Station Kd(PAR) (m{1)Zeu (m)
East coast, north to south
BS4 0.11 41.82
AS2 0.14 33.20
AS1 0.11 41.40
AS3 0.13 36.60
BS5 0.30 15.59
AS4 0.25 18.10
BS6 0.29 16.03
AS5 0.17 27.80
AS6 0.17 26.80
AS7 0.12 39.70
AS8 0.29 15.70
AS9 0.27 16.90
AS10 0.25 18.20
AS11 0.57 8.10
AS12 0.21 21.90
AS13 0.30 15.20
AS14 0.26 17.60
BS9 0.30 15.13
BS10 0.17 26.90
AS15 0.10 48.40
AS16 0.22 20.90
BS11 0.13 35.94
BS12 0.29 16.03
BS13 0.25 18.47
AS17 0.30 15.40
AS18 0.26 17.40
BS14 0.18 26.29
BS15 0.12 39.66
BS16 0.11 41.07
West coast, south to north
BS18 0.11 40.71
AS19 0.09 52.00
AS20 0.05 102.2
BS19 0.11 42.59
AS21 0.16 28.60
BS20 0.27 16.85
BS21 0.14 33.09
AS22 0.19 23.80
BS22 0.13 35.38
AS23 0.08 56.80
BS23 0.08 56.79
AS24 0.12 38.90
BS24 0.07 66.67
BS1 0.16 28.75
AS25 0.07 70.00
BS2 0.15 30.07
BS3 0.16 29.30
Station locations correspond to those in figure 2.
Remote Sensing of the Coastal Marine Environment 2693
red, green and blue colour filters. A further 15 profiles were also obtained for Old
Providence (PF1–PF15). The calculated Kdvalues for red, green and blue light are
given in tables 5 and 6 and graphically illustrated for blue light in figures 4 and 5.
As can be seen from figures 4 and 5, the spatial variation of attenuation in an
individual band closely followed the pattern of the PAR measurements, being
highest at the same stations that PAR attenuation was highest. Lowest attenuation
was almost always observed at the blue region, suggesting that blue light is the most
penetrative (Tables 6 and 7). Red light was most attenuated, attributed to the
influence of the greater absorption of the light in this region by water itself. In the
few cases that green band attenuation approached or was less than that for blue
light, these were generally in the most turbid areas or where it might be expected
localised eutrophication effects were operating (e.g. near ports and mangroves).
4.5. Spectral measurements
Twelve attenuation spectra from San Andres and 14 from Old Providence were
calculated from measurements made using the spectroradiometer fitted with the
fibre optic probe (figure 6). Station numbers correspond to the PAR profiles from
figures 2 and 3. Little variation in spectral attenuation was observed between the
different stations, and between the islands, where the shape of attenuation was
largely influenced by the absorption properties of water itself across the visible
spectrum. This suggests that differences between stations were largely the result of
differences in scattering caused by varying concentrations of particulate matter.
Some stations (AS8, AP10, AP11) showed increased blue light attenuation in areas
E. Karpouzli et al.
Table 4. Values of Kdand depth of euphotic zone for stations around Old Providence island
during the first collection period (A).
Station Kd(PAR) (m{1)Zeu(m)
West coast, north to south
AP1 0.06 74.2
AP2 0.17 27.9
AP3 0.14 33.6
AP4 0.25 18.8
AP5 0.31 14.9
AP6 0.18 26.0
AP7 0.18 25.4
AP8 0.22 21.3
AP9 0.19 23.8
AP10 0.23 19.8
AP11 0.38 12.1
AP12 0.09 54.1
East coast, south to north
AP13 0.19 24.2
AP14 0.12 37.4
AP15 0.21 22.1
AP16 0.16 28.9
AP17 0.22 20.9
AP18 0.18 25.4
Station locations correspond to those in figure 3.
2694
where increased turbidity of water was encountered either as a result of proximity
to mangroves or probably due to effects of wind-induced mixing and resuspension
of particulate matter emanating from mangrove beds.
Table 6. Values of band-specific Kdmeasured using colour filters for stations around Old
Providence island.
Station KdBlue (m{1)KdGreen (m{1)KdRed (m{1)
PF1 0.05 0.18 0.44
PF2 0.13 0.17 0.49
PF3 0.21 0.21 0.98
PF4 0.05 0.28 0.36
PF4 0.41 0.38 0.59
PF5 0.28 0.34 0.53
PF6 0.11 0.19 0.52
PF7 0.34 0.38 0.66
PF8 0.16 0.13 0.49
PF9 0.13 0.21 0.42
PF11 0.13 0.25 0.44
PF12 0.16 0.18 0.56
PF13 0.20 0.27 0.50
PF14 0.32 0.40 0.50
PF15 0.20 0.16 0.50
Station numbers correspond to those in figure 5.
Table 5. Values of band-specific Kdmeasured using colour filters for stations around San
Andres island.
Station KdBlue (m{1)KdGreen (m{1)KdRed (m{1)
BSF1 0.13 0.12 0.43
BSF2 0.09 0.18 0.43
BSF3 0.10 0.14 0.42
BSF4 0.10 0.15 0.42
BSF5 0.22 0.21 0.43
BSF6 0.15 0.16 0.49
BSF7 0.20 0.23 0.47
BSF8 0.54 0.52 0.66
BSF9 0.31 0.29 0.58
BSF10 0.15 – –
BSF11 0.16 0.16 0.43
BSF13 0.33 – –
BSF14 0.10 0.16 0.54
BSF15 0.17 0.16 0.39
BSF16 0.12 0.12 –
BSF17 – – 0.39
BSF18 0.04 0.12 0.41
BSF19 0.10 0.12 0.41
BSF20 0.36 0.55 0.62
BSF21 0.05 0.15 0.45
BSF22 0.12 0.22 0.46
BSF23 0.07 0.13 0.41
BSF24 0.05 0.13 0.50
BSF25 0.08 – –
Station numbers correspond to those in figure 4.
Remote Sensing of the Coastal Marine Environment 2695
4.6. Predictive models results
To process a remotely sensed image to bottom reflectance in order to investigate
underwater habitats and to enable the accurate correction of the imagery for
varying bathymetry, an accurate measure of the water column attenuation at each
Figure 4. Variation in measured blue light attenuation (Kd, B) in coastal waters around the
island of San Andres.
E. Karpouzli et al.
2696
pixel is required. However, the results of the spatial survey indicate a high degree of
variation in light attenuation in the waters around both islands under study. Thus,
if a single measure of ‘average’ attenuation is used for water column correction of
imagery, the accuracy of the result may be questionable.
However, it is possible to generalise some factors about the behaviour of light
attenuation around the islands. First, Kdvalues generally decrease with greater
Figure 5. Variation in measured blue light attenuation (Kd, B) in coastal waters around the
island of Old Providence.
Remote Sensing of the Coastal Marine Environment 2697
E. Karpouzli et al.
Figure 6. Spectral attenuation at some San Andres and Old Providence sampling stations.
2698
distance from the shore of each island. Second, Kdvalues are generally lower over
deeper waters than shallower ones. These trends would suggest that it may be
possible to develop simple relationships which may be used to explain and map the
distribution in attenuation in such waters. Thus, to better understand the sources of
variation in water attenuation around the coastal zones of San Andres and Old
Providence, multiple regression analysis was employed to develop the simple models
to estimate PAR attenuation. A predictive model to estimate Kdin areas where
such measurements were not made would also give rise to better estimation of
attenuation as opposed to direct interpolation between the measured Kdpoints.
For San Andres the measurements of PAR attenuation for both the first and
second collection periods were used (table 2) whereas for Old Providence the values
in table 5 were used. Deep water sites were not included in the analysis since the
precise water depth for these sites was not known.
For San Andres the strongest correlation between attenuation and a single
variable was with water depth:
Kd~0:061z0:673:1=D,n~44, r2~0:752, pv0:001, ð1Þ
indicating the major influence of depth in determining relative water clarity around
the island. With the addition of further variables, it was found that the regression
was improved to
Kd~0:0778z0:4781:1=Dz0:0074MA=L2
Mz0:0028TA=L2
r,n~44, r2~0:890,
pv0:001, ð2Þ
With the elimination of Station AP11 (Southwest Bay) from the dataset for Old
Providence island, which was indicated as an outlier, depth was also a strongly
correlating variable with Kd:
Kd~0:069z0:646:1=D,n~16, r2~0:633, pv0:01, ð3Þ
The relationship between Kdand depth for Old Providence is very similar to that
obtained for San Andres above. With the addition of more variables into stepwise
regression analysis the model was improved to:
Kd~0:0757z0:4145:1=Dz0:0006TA=Lr,n~16, r2~0:78, pv0:05 ð4Þ
The addition of further variables did not improve the models of both islands.
Correlations between individual variable terms included in the regressions were all
non-significant (Pearson correlation coefficient rv0.5 in all cases) indicating their
relative independence.
5. Discussion
This investigation has shown that there was a three- to four-fold spatial
variation in the attenuation of tropical ‘clear’ littoral waters around the islands of
San Andres and Old Providence in the south-western Caribbean Sea, corresponding
to extremely wide variations in the depth of light penetration around both islands.
The general similarity in the shape of high spectral resolution attenuation spectra
made using a spectroradiometer suggested that this variation was largely the result
of attenuation due to scattering by particulate matter in the water column, rather
than varying concentrations of dissolved yellow substances. Broad-band spectral
measurements indicate that blue light was the most penetrating. Although there
is some evidence for slightly increasing chlorophyll concentrations around San
Remote Sensing of the Coastal Marine Environment 2699
Andres, light is still of sufficient quality to support a wide variety of plant and coral
habitats.
The limited sampling over time in this study (April to June) indicated that there
was little influence of a temporal component to variation in Kd(table 1). However,
this would need greater investigation in order to ascertain the degree of variation
over the different seasons.
These results therefore suggest that it may be highly inappropriate to use a single or
few measures of ‘typical’ attenuation obtained in deep water or shallow areas for water
column correction of remotely sensed images acquired over tropical regions where
reflectances are influenced by both variations in waterdepth and bottom type. It further
suggests that the results of such corrections should be interpreted with a high degree of
caution. Deep water attenuation values tend to be much lower than those over related
littoral zones and, as a result of scattering by varying concentrations of particulate
matter, attenuation values in shallower waters are highly variable. Clearly, field data
from deep water sites, as well as in the proximity of more turbid or organic-rich water
sources, are required to objectively correct remotely sensed images for water column
attenuation.
In this study, shallower waters generally showed greater attenuation compared to
more open and deeper sites. However, there was considerable variation in attenuation
in shallow regions alone, with up to three-fold variations encountered. It is thoughtthis
variation was a function of:
.depth of the water column;
.proximity of the sampling stations to the coastline;
.proximity to centres of population or mangrove and lagoon environments;
.local currents.
That attenuation was lowest further away from shore tends to indicate the
decreased influence of land processes and deeper waters which both encourages
settlement of sediments and discourages their re-suspension.
From the empirical modelling studies, water depth had the largest influence on
Kd. Deeper water would be expected to be both further away from the shoreline
and clearer, due to the larger volume of water over which turbid particles may
diffuse, and also due to lessened influence of sandy substrates where sediment may
become re-suspended. The results from the multivariate regression analysis gave
very similar models for both islands for the prediction of attenuation from water
depth alone, suggesting that a general model for both islands would be obtainable.
For both islands, predictions of Kdwere significantly improved by including
terms for the proximity and hence influence of, mangrove beds (known to be
significant sources of suspended sediments) and towns. The overall strength of the
equations developed for San Andres was high, with nearly 90% of the variation in
Kdexplained by variations in depth, distance to and size of mangroves and distance
to and size of towns. Relationships for Old Providence were less strong, with only
78% of the variation in Kdexplained by depth and distance to and size of towns.
This may be partially the result of the lower number of sampling stations measured
around this island but may also suggest that other factors that were not included in
the analysis may have been responsible in part for the variation encountered in Kd.
One such variable not included is the influence of current strengths and directions.
These may have had more influence around Old Providence island — where the
E. Karpouzli et al.
2700
platform is more exposed to the predominantly north-eastern wind-induced
currents as the barrier reef is discontinuous around where stations were located
(pinnacle belt) — than for San Andres (Diaz et al. 1996, 1997, Geister and Diaz
1996). Current hydrologies around both islands may thus be markedly different.
The results of this study suggest that, using the equations developed, Kdmay be
predicted spatially with a high degree of confidence for all locations on the platforms
around both these tropical islands. This would then enable remotely sensed images to
be more accurately corrected for water column effects than if based on ‘average’
attenuation values alone. It further suggests that similar relationships with driving
variables may be obtained for other littoral areas. The models reported here were
developed for broad PAR attenuation. For the correction of multi-spectral remotely
sensed images over littoral regions, estimates of band-specific Kdwould be required.
However, the similarities in behaviour between the broad-band blue, green and red
attenuation measurements made during this study and the broader PAR attenuation
values suggests that models specific for individual sensor bands should be easily
obtainable.
More accurate measurements of distance to sources of turbid water may lead to
improvements in the accuracy of the models. For example, populations of towns may
be a better variable to describe the influence of towns as opposed to their size as was
used in this study. Although rivers were ephemeral in this study region, the influence of
river flows and sewage outfalls may also be more quantitatively related to their
discharge volumes rather than simply distance from their locations. Furthermore, more
detailed information on hydrology may allow greater understanding of the diffusion of
pollutants in the water column and hence lead to better estimates of Kd. Nevertheless,
the results from this study are particularly encouraging, given the limited information
available for the study region.
Acknowledgments
The project was financially supported by the Darwin Initiative, the Onassis
Foundation, the Carnegie Trust, the Small Project grant scheme of Edinburgh
University, and the Moray Fund. It was conducted in collaboration with CORALINA
in San Andres. The assistance of a number of staff during data collection is gratefully
acknowledged. The GER 1500 spectroradiometer was obtained on loan from the
Natural Environment Research Council Equipment Pool for Field Spectroscopy, UK.
Special thanks are extended to Phil Lovell and Callan Duck for their valuable help
during fieldwork, and Phil Lovell and Lex Hibby for helpful discussions and for
comments which have greatly improved this paper.
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