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Collaborative Environmental Project in Indonesia ENVIRONMENTAL INTELLIGENCE FOR SUSTAINABLE DEVELOPMENT |
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An
Analysis of In Situ Observations of Spectral Reflectance Characteristics
of Coral Reef Features in Fiji and Indonesia by:
Heather M. Holden (e-mail
address:
) Dissertation
for Ph.D. in Philosophy University of Waterloo, 1999 Increased
awareness of the vulnerability of coral reef ecosystems to the synergistic
effects of natural and anthropogenic environmental changes has lead to
subjective reporting of observed changes, but there has been a significant
lack of objective monitoring of coral reef ecosystems on a repetitive
basis. Only consistent,
repetitive monitoring over time will increase understanding of the dynamic
and complex nature of coral reef ecosystems and the ways in which changes
in the ecosystem are related to environmental changes.
One limiting factor to remote detection of coral reef well-being is
the lack of a quantitative means of identifying optically similar features
such as healthy coral and macro algae. In
this study, a field program was designed to explore the differences in
spectral reflectance characteristics of various coral reef features.
High spectral resolution in situ data were collected with a
hand-held hyperspectral radiometer. In
1996, in situ spectral reflectance data of submerged coral reefs
were collected in Beqa Lagoon, Fiji: in 1997, in situ spectral
reflectance measurements of exposed coral reef features were collected in
Manado, Indonesia. Finally, in
situ data of submerged coral reefs were collected in 1998 in Savusavu
Bay, Fiji. The
spectra collected were divided into populations of healthy coral,
unhealthy coral, algae-covered surfaces and rubble surfaces based on
feature type according to field notes and photographic records.
These data sets were compared and analyzed to test the following
hypotheses. First, the
within-population variability is low such that spectra of similar coral
reef features display similar spectral reflectance characteristics, and
conversely, there are discernable spectral reflectance differences between
populations. Secondly, the
geographic location of measurement does not affect the spectral
reflectance characteristics. The
final hypothesis tested is that the slopes and changes in slopes of the
spectral reflectance curves will allow differentiation of populations and
subsequent classification. Cluster
and correlation analyses indicate that both the within and
between-population variability is low.
Therefore, while spectra of similar features are comparable, there
are predictable inaccuracies in classification due to spectral
similarities between populations. Nevertheless,
principal components analysis was used successfully as a data reduction
tool to reduce the large data set of 334 spectra to 6 spectra
representative of the pre-defined populations.
A classification scheme was devised based on these representative
spectra such that the slope, change in slope and magnitude of reflectance
of the spectral curves enabled identification.
This classification procedure was applied to the remainder of the
data set and an error analysis was performed to investigate accuracy of
identification. The overall
accuracy was 80.1% and an investigation of the errors of omission and
commission indicate that the majority of the errors are a result of an
inability to characterize bleached coral correctly.
The results of this study indicate that hyperspectral remote
sensing may be a feasible means of accurate identification and subsequent
monitoring of changes in coral health and overall well-being. |
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