Change in Benthic Coral Communities in the Florida Keys (1996 and 2002):
A Comparison Between In Situ and Remote Sensing Assessments
David Palandro1, Matthew Lybolt2, Chuanmin Hu1, Serge Andréfouët1,
and Frank Muller-Karger1
(1) College of Marine Science, University of South Florida
140 7th Avenue South, Saint Petersburg, FL 33701, USA
Tel: 727-553-1186, Fax: 727-553-1103
E-mail: palandro@seas.marine.usf.edu
(2) Coral Group, Florida Marine Research Institute
Florida Fish and Wildlife Conservation Commission
100 8th Avenue Southeast, Saint Petersburg, FL 33701, USA
Submitted as a Note to:
Coral Reefs
Keywords: Landsat, CRMP, change detection, monitoring
Introduction
The primary operational method to assess percent coral cover in tropical coral reefs is to
conduct repeated intensive in situ observations in a restricted location or transect. The
Florida Marine Research Institute (FMRI) has examined over 40 sites in the Florida Keys
National Marine Sanctuary (FKNMS) for change since 1996 under the Coral Reef
Monitoring Project (CRMP). Three sites were added in the Dry Tortugas in 1999 (Porter
et al., 2002). This is the largest dataset of its kind. The CRMP uses permanently placed
stakes at each reef site to construct transects. These annual studies provide live coral
percent cover by species of octocorallia and of broader benthic categories (e.g., substrate,
sponges, and macroalgae).
The FKNMS coral communities experience various pressures, including bleaching and
several coral diseases (black band, white plague, white band and yellow blotch; Porter, et
al., 2001). The most severe coral decline seems to be the result of white pox, which
exclusively affects Acropora palmata, the major reef building coral of the Caribbean
(Patterson et al., 2002). The bleaching event of 1997-1998, algal overgrowth, and direct
anthropogenic stresses derived from fishing, nutrient input through sewage discharge,
direct destruction of the coral structure by swimmers of boats add significant stresses to
these communities (Dustan, 1999). Other sources of stress such as waters laden with
phytoplankton have been recently identified as another possible source of problems for
the reefs, such “dark water events” have been linked to decline of corals and sponges in
the Florida Keys (Hu et al., 2003).
1
Unfortunately, the in situ methods used in the CRMP and other similar programs, while
effective, only permit assessments of a small part of the coral reef system. Recent
advances in satellite remote sensing technology and methodology allow studies of change
in benthic habitats over time frames spanning years to decades (Andrefouet, et al., 2001;
Dustan et al., 2001; Palandro et al., 2003). In particular, the Landsat satellites carrying
the Thematic Mapper (TM, Landsats 4 and 5) and the Enhanced Thematic Mapper Plus
(ETM+, Landsat 7) sensors provide the longest continuous satellite data series useful for
coral reef benthic cover studies.
Landsat TM and ETM+ data provide repetitive coverage for sites at a 30 m spatial
resolution. Although this is too coarse to yield information on coral species coverage, the
data allow broad assessments of bottom types and useful inferences about spatial changes
in communities over time. The synoptic view of a reef system possible with these satellite
data provides information of entire reef areas, not just small parts.
In this study, we compare estimates of coral reef cover change obtained from in situ data
and Landsat data in the FKNMS.
Methods
CRMP and Landsat datasets for 1996, 1998, 2000 and 2002 for five sites in the FKNMS
are used in this study. The sites (Table 1; Figure 1) were chosen for their location (i.e. as
being representative of the upper, middle and lower Florida keys), their designation as a
Sanctuary Preservation Area (SPA), and their depth (less than 16m). All reefs are
2
classified by the CRMP as offshore (shallow or deep) and are typical of the spur and
groove reefs found throughout the Caribbean.
Table 1. Locations of the five CRM sites used in the study.
General area
Reef name
Latitude
Longitude
Upper Keys
Carysfort Reef
25º 13.33’
-80º 12.59’
Upper Keys
Grecian Rocks
25º 06.45’
80º 41.42’
Middle Keys
Alligator Reef
25º 50.77’
-80º 22.59’
Lower Keys
Looe Key Reef
24º 32.72’
-81º 24.48’
Lower Keys
Eastern Sambo Reef
24º 29.50’
-81º 39.81’
The process by which the CRMP data are gathered and analyzed are briefly described
here, but can be found in detail in Porter et al., 2002. Each CRMP site characterizes a
single reef zone and is comprised of four stations. Stations, demarcated by a pair of
permanently placed stakes, are comprised of three parallel video transects spaced 0.6m
apart. Each transect is 0.4m wide and approximately 22m long. Video transects were
analyzed with PointCount® software. The CRMP data for individual stony coral species
percent cover were pooled into total stony coral percent cover data. Station-level CRMP
percent coral cover data were pooled by combining shallow fore-reef (3-7m) and deep
fore-reef (12-16m) site data for Carysfort, Alligator, Looe Key and Eastern Sambo, so
that each of these sites has eight stations. Grecian Rocks had only four stations located at
a depth of 3m.
3
The in situ percent coral cover were compared to the number of Landsat Tm/ETM+
pixels classified as ‘coral’. The use of satellite data in multi-temporal (change detection)
studies requires a rigorous series of corrections including geo-rectification, atmospheric
correction and bathymetric correction (Palandro et al., 2003). The four Landsat scenes
(path-15, row-43) were acquired between March and May of each year (1996, 1998, 2000
and 2002) and all were geo-rectified using the 2002 image as reference. An atmospheric
correction was effected using a multi-sensor approach with bands seven and eight
(centered at 765 and 865nm) of the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS)
and the input of climatogical ancillary data (Hu et al, 2001) to derive the remote sensing
reflectance (Rrs), as follows:
Rrs = [Li – (LRayleigh + Laerosol)] / (F0 · cosθ0 · t · t0)
(1)
Here, Li is the radiance of an image pixel corrected for ozone absorption, θ0 is the solar
zenith angle, LRayleigh and Laerosol result from molecular and aerosol scattering,
respectively, F0 is the solar constant, and t and t0 are the diffuse transmittance from the
pixel to the sensor and the sun to the pixel, respectively. Under most circumstances (i.e.,
moderate solar and viewing angles) Rrs is assumed to be a property that depends
primarily on the color of the water (and the associated benthic surface), not on the
measurement configuration (solar and viewing angles, time of the year, etc.).
The bathymetric correction was accomplished by having detailed (30m spatial resolution)
NOAA depth soundings for the FKNMS. The data had a resolution of one meter for the
4
2-10m depth range, and five-meter intervals for the 10-20m depth range; the latter data
were interpolated horizontally to one-meter vertical intervals.
The attenuation coefficient (K, m-1) is an apparent optical property that describes the
transparency or clarity of the water column. This was estimated by obtaining Rrs for each
band at pixels where sand was easily identified at various depths from the Landsat image
(Palandro et al., in press). The derivation of K is based on the assumption that light
attenuates exponentially with depth (Kirk, 2003). Therefore, K can be estimated from the
natural log of Rrs versus depth where Rrs is dominated by the bottom signal. K was
assumed as being the regression slope of that line (Lyzenga, 1981 and Maritorena, 1996).
K = ln [Rrs (z1) / Rrs (z2)] / [2(z2-z1)]
(2)
[PLEASE CHECK FORMULA WITH CHUANMIN VERY CAREFULLY – NOTE
WHETHER Z2 is DEEPER THAN Z1, and DETERMINE IF FACTOR OF 2 is
CORRECT] [Hu: Yes they are correct whether or not z2 > z1 or z2<z1. The nominator
and denominator are both positive or negative. 2 should be there]
Where z1 and z2 are different depths at which sand pixels are located. With depth, K can
provide the necessary bathymetric correction value for each pixel.
Rrsº = Rrs · e (2Kz)
(3)
[PLEASE CHECK FORMULA WITH CHUANMIN VERY CAREFULLY – NOTE
WHETHER SIGN OF EXPONENT IS CORRECT, and DETERMINE IF FACTOR OF
2 is CORRECT; MAKE CLEAR WHERE RRS AND WHERE RRSo ARE
5
MEASURED – THIS IS NOT CLEAR HERE OR BELOW][Hu: yes 2 should be there,
and the sign is correct – this way Rrso is always larger than Rrs]
Where z is the depth of the target, Rrs is remote sensing reflectance from the satellite
pixel covering the target (by definition, Rrs is the ratio of water-leaving radiance (light
emerged from below the water surface as detected by a downward looking sensor just
above the water surface) and downwelling irradiance just above the water surface), and
Rrsº is the corrected remote sensing reflectance as if the target were just below the water
surface. The factor “2” in the exponential term (likewise, in the denominator term in Eq.
2) is to take account of the two-way attenuation (downward and upward) of light
(Maritorena et al., 1994). In other words, if the target is moved from depth z to 0 (just
below the water surface), neglecting the contribution from the water column itself, waterleaving radiance and remote sensing reflectance will increase by exp(2K*z).
[I am not sure what you did – you determined K from adjacent Rrs observations and the
NOAA bathymetry – then what is this Rrso? Did you recompute Rrs with equation 3?
Since K was not determined at each pixel but across adjacent pixels, how did you
interpolate/adopt a K and Rrs value for each pixel?] [Hu: Did you use an average of K
values for each site, then apply to all pixels for that site?]
Upon completion of the remote sensing corrections, five geographic areas of interest
(AOI) were produced, one for each reef site. The location and extent of the various AOIs
were defined to include the three major reef zonations; fore-reef, reef flat and back-reef,
6
this allowed for the entire reef system to be represented. The images were then classified
to derive six benthic classes (‘coral’, ‘sand’, ‘dense seagrass’, ‘sparse seagrass’, ‘bare
substrate’ and ‘covered substrate’), plus a deep water mask at 16m, using a Mahalanobis
Distance classifier (Fig. 2 [What is the purpose of including IKONOS here – discussed in
results??]). Training pixels for each class were obtained from field knowledge of the
different sites as well as high-resolution aerial photography or IKONOS satellite imagery
(4m resolution). The number of ‘coral’ pixels derived from the classifications was then
compared to the CRMP percent coral cover data to determine if the trends from both
datasets were similar.
The 1996 and 1998 Eastern Sambo and the 1996 and 2000 Looe Key images could not be
used because the Landsat scenes did not include the reef site or because of cloud cover.
Results and Discussion
The comparison between the percent coral cover from the in situ CRMP assessments and
the percent ‘coral’ pixels in the Landsat data show a good fit for all five reefs (Fig. 3). .
In general, the coral cover estimates based on Landsat were lower than CRMP
assessments. This difference is caused by including low-density habitat types, such as
the back-reef, in the Landsat classifications. These are not sampled by the CRMP.
An analysis was done to test whether the number of pixels classified as ‘coral’ varied
with AOI size. The result showed that the number of ‘coral’ pixels was only affected by
AOI size if an AOI was large enough to include coral areas from an adjacent reef site or
7
so small that it excluded sections of the reef flat or fore-reef. Changes in the number of
pixels classified as other than ‘coral’ were also seen. However, this would only change
the percent coral cover derived from Landsat linearly over time and would not alter the
total percent change over the entire time series of data. [NOT SURE WHAT YOU SAID
HERE – CLARIFY PLEASE]
The closest match between Landsat and CRMP assessments occurred at Grecian Rocks.
Unfortunately, the uncertainty associated with the CRMP assessments, which was based
on eight stations per reef, has probably increased as the number of stations has been
reduced for all of the sites studied here for the 2002 assessment with the exception of
Grecian Rocks, which maintained four stations throughout the series. The total number
of stations was reduced from 36 (1996-2000) to 24 (2002). The slight increase in coral
cover noted in the CRMP data for Carysfort may be an artifact of the removal of stations,
and may not be significant.
The 2000 Landsat image showed reflectance values greater than those of the other three
images. This may have confused the classification process and lead to overestimation of
the number of ‘coral’ pixels in that image for that site [THIS IS NOT APPARENT IN
FIGURE 3 – WHAT MAKES YOU SAY THIS???]. This is demonstrated by deriving
the R2 for Landsat versus CRMP for all of the sites: with the 2000 Landsat data (R2 =
0.8715) and without the 2000 Landsat data (R2 = 0.9476). The CRMP and Landsat
datasets both yielded high percentages of coral cover loss for four sites from 1996-2002,
42.45% and 43.51%, respectively (Table 1), the values for Eastern Sambo are for 2000-
8
2002 only and not included in this calculation. These values are representative of the
losses seen throughout the FKNMS (Causey et al., 2000). The similarity in change
values observed from the two independent datasets and acquisition methods may be
indicative of the wide-scale changes taking place in the Florida Keys. The changes being
observed on the CRMP sites caused by algal overgrowth (Dustan, 1999) and the coral’s
response to disease (Porter et al., 2001) seem to be reflected on the larger reef habitat
scale, as observed by Landsat. [THIS IS A POORLY WORDED PARAGRAPH AND
DOES NOT SEEM TO SAY MUCH – REWORD OR DELETE]
Current satellite have spatial and spectral resolution that is too coarse to provide species
information. However, Landsat data provide a synoptic view of a reef site and permits
time series assessments. The CRMP information provides an invaluable high-resolution
tool to ground-truth such remote sensing data and develop more robust area-wide
assessments. Long-term and sanctuary-wide coral reef monitoring are vital to maintaining
the coral reefs of the FKNMS (Causey et al., 2002). The techniques described here are
another step in the definition of methods that may be used to evaluate the state of the
entire FMKNMS coral reef tract, even in locations where no in situ data exist.
Acknowledgements
The authors would like to thank Damaris Torres-Pulliza and Selena Kupfner for their
assistance in the field. Ikonos data were obtained through the NASA Scientific Data
Purchase Program. This work was partially supported by NASA Headquarters under the
Earth System Science Fellowship Grant NGT5-30414 to David Palandro.
9
References
Andrefouet, S., Muller-Karger, F.E., Hochberg, E.J., Hu, C. and Carder, K.L. (2001)
Change detection in shallow coral reef environments using Landsat 7/ETM+ data.
Remote Sensing of Environment, 78: 150-162.
Causey, B. D., Dodge, R.E., Jaap, W.C., Banks, K., Delaney, J., Keller, B.D., Speiler, R.
(2002) Florida. In: The state of coral reef ecosystems of the United States and
Pacific Freely Associated States: 2002. NOAA, Silver Spring, MD, pp.101-118.
Causey, B.D., Delaney, J., Diaz, E., Dodge, R.E., Garcia, J.R., Higgins, J., Jaap, W.C.,
Matos, C.A., Schmal, G.P., Rogers, C., Miller, M.W. and Turgeon, D.D. (2000)
Status of coral reef in the US Caribbean and Gulf of Mexico: Florida, Texas,
Puerto Rico, U.S. Virgin Islands and Navassa. In: C. Wilkinson (ed) Status of
Coral Reefs of the World: 2000. AIMS, Cape Ferguson, Australia, pp. 239-259.
Dustan, P., Dobson, E. and Nelson, G. (2001) Landsat Thematic Mapper: detection of
shifts in community composition of coral reefs. Conservation Biology, 15: 892902.
Dustan, P. (1999) Coral reefs under stress: sources of mortality in the Florida Keys.
Natural Resource Forum, 23: 147-155.
Hu, C., Hackett, K.E., Callahan, M.K., Andrefouet, S., Wheaton, J.L., Porter, J.W. and
Muller-Karger, F.E. (2003) The 2002 ocean color anomaly in the Florida Bight:
A cause of local reef decline? Geophysical Research Letters, 30: 1151,
doi:10.1029/2002GL016479.
Hu, C., Muller-Karger, F.E., Andrefouet, S. and Carder, K.L. (2001) Atmospheric
10
correction and cross-calibration of Landsat-7/ETM+ imagery over aquatic
environments: a multi platform approach using SeaWiFS/MODIS. Remote
Sensing of Environment, 78: 99-107.
Kirk, J.T. (2003) The vertical attenuation of irradiance as a function of the optical
properties of the water. Limnology and Oceanography, 48: 9-17.
Lyzenga, D.R. (1981) Remote sensing of bottom reflectance and water attenuation
parameters in shallow water using aircraft and Landsat data. International Journal
of Remote Sensing, 1: 71-82.
Maritorena, S. (1996) Remote sensing of the water attenuation in coral reefs: a case
study in French Polynesia. International Journal of Remote Sensing, 17: 155-166.
Maritorena, S., Morel, A. and Gentili, B. (1994) Diffuse reflectance of oceanic shallow
waters; influence of the water depth and bottom albedo. Limnology and
Oceanography, 39: 1689-1703.
Palandro, D., Andréfouët, S., Muller-Karger, F.E., Dustan, P., Hu, C. and Hallock, P.
(2003) Detection of changes in coral reef communities using Landsat 5/TM and
Landsat 7/ETM+ data. Canadian Journal of Remote Sensing, 29: 201-209.
Palandro, D., Hu, C., Andréfouët, S. and Muller-Karger, F.E. (In press) Synoptic water
clarity assessment in the Florida Keys using diffuse attenuation coefficient
estimated from Landsat imagery. Hydrobiologia, in press.
Pattterson, K.L., Porter, J.W., Ritchie K.B., Polson, S.W., Mueller, E., Peters, E.C.,
Santavy, D.L. and Smith, G.W. (2002) The etiology of white pox, a lethal
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11
Porter, J.W., Kosmynin, V., Patterson, K.L., Porter, K.G., Jaap, W.C., Wheaton, J.L.,
Hackett, K.L., Lybolt, M., Tsokos, C.P., Yanev, G., Marcinek, D.M., Dotten, J.,
Eaken, D., Patterson, M., Meier, O.W., Brill, M. and Dustan, P. (2002) Detection
of coral reef change by the Florida Keys Coral Reef Monitoring Project. In: J.W.
and K.G. Porter (Eds.), The Everglades, Florida Bay, and Coral Reefs of the
Florida Keys. CRC Press, Boca Raton, pp. 749-769.
Porter, J.W., Dustan, P., Jaap, W.C., Patterson, K.L., Kosmynin, V., Meier, O.W.,
Patterson, M.E. and Parsons, M. (2001) Patterns of spread of coral disease in the
Florida Keys. In: J.W. Porter (Ed.), The ecology and etiology of newly emerging
marine diseases. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp.
1-24.
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Tables
[MOVE TABLE 1 HERE]
Table 2: Comparison of the percent change in coral cover (1996-2002) for the CRMP in
situ monitoring data and the Landsat ‘coral’ pixel data. Percent change data for Eastern
Sambo is from 2000-2002 only and not included in the total percent change value.
Site
Eastern Sambo
% CRMP
% Landsat
9.24
11.99
Looe Key
19.63
23.76
Alligator
47.50
37.30
Grecian Rocks
42.65
45.57
Carysfort
60.03
67.42
TOTAL
42.45
43.51
`
13
Figures
[LIST CAPTIONS SEPARATE FROM FIGURES – EACH FIGURE SHOULD BE
CONTAINED IN 1 PAGE]
14
81° 40’ W
81° 20’ W
81° W
82° 40’ W
82° 20’ W
N
25° N
24° 40’ N
0
20km
Figure 1. Landsat scene (path-15, row-43) of the Florida Keys showing the locations of
the five reef sites. From north to south the reef sites are: Carysfort, Grecian Rocks,
Alligator, Looe Key and Eastern Sambo.
15
16
N
250m
LEGEND
Sand
Coral
Sparse Seagrass
Covered Substrate
Dense Seagrass
Bare Substrate
Deep Water Mask (>16m)
[REWORD CAPTION TO SHOW ORDER OF FIGURES/PERHAPS LABEL
17
PANELS]Figure 2. IKONOS (displayed to show the detail of the reef), 2002 Landsat
and 2002 Mahalanobis Distance classified Landsat images (left to right) for Carysfort,
Alligator and Looe Key Reefs (top to bottom). Scale and geographic orientation are
constant.
250m
16
Carysfort
14
12
10
8
6
4
2
0
1996
16
1998
2000
2002
Looe Key
20
18
16
14
12
10
8
6
4
2
0
1996
2.5
Grecian Rocks
1998
2000
2002
2000
2002
Alligator
14
2
12
10
1.5
8
1
6
4
0.5
2
0
1996
16
1998
2000
2002
Eastern Sambo
0
1996
14
14
12
12
10
10
1998
All Sites
8
8
6
6
4
4
2
2
0
1996
0
1998
2000
2002
1996
18
1998
2000
2002
CRMP
Landsat
Figure 3. Percent coral cover from in situ CRMP data (with standard error bars) and
Landsat percent ‘coral-dominated’ pixels for 1996-2002 for all five reef sites and the
average of all sites.
19