11th ICRS Abstract book - Nova Southeastern University

Oral Mini-Symposium 17: Emerging Techniques in Remote Sensing and Geospatial Analysis
17-9
Mapping The Habitats And Biodiversity Of Ningaloo Reef, Western Australia Using
Hyperspectral Imagery
Halina KOBRYN* 1 , Nicole PINNEL 1 , Thomas HEEGE 2 , Lynnath BECKLEY 1 , Matt
HARVEY 1 , Suzanne LONG 3
1 Environmental Science, Murdoch University, Murdoch, WA 6150, Australia, 2 EOMAP
GmbH&Co KG, D-82205 Gilching, Germany, 3 Department of Conservation and
Environment, Kensington, Australia
The largest hyperspectral survey of a coral reef (3400 km 2 ) was undertaken in April 2006
and forms the core data set for mapping habitat components and biodiversity of the
Ningaloo Marine Park, Western Australia. Optically deep waters of this region are ideally
suited for remote sensing techniques and airborne data were collected by HyVista. The
data are at 3.5 m spatial resolution for a 1km wide terrestrial coastal strip and out to 20m
depth over lagoon and reef areas and covers wavelengths from visible to near infrared at
15nm intervals. Hyperspectral data were corrected for atmospheric, air-water interface
and water column effects using the physics-based Modular Inversion & Processing
System. This approach allows for quantitative and automated steps as well as the removal
of subjectivity from the classification process, allowing improved transferability to
additional sampling locations, field spectral datasets and extension of the monitoring to
other seasons. Underwater field spectra were collected using an OceanOptics
spectrometer as well as underwater photographs, to allow for accurate interpretation and
validation. Results of this mapping can be compared to the transect data collected by
divers from other studies and also to earlier habitat maps prepared by expert
interpretation of aerial photography. Comparisons of classification results for Coral Bay
area show promising results in the discrimination of branching, tabulate and massive
corals as well as macro-algal assemblages. Remote sensing offers unique tools which are
non-invasive, quantitative and enable mapping of large areas into a seamless data set
which can be integrated with human use data, oceanographic circulation models and
other spatial data sets. The hyperspectral data are being used to develop a high-resolution
characterisation of the entire reef, shallow water habitats and terrestrial landforms of the
coastal strip in order to support sound conservation and management of the Ningaloo
Marine Park.
17-10
Development Of A Field Test Environment For The Validation Of Coastal Remote
Sensing Algorithms: Enrique Reef, Puerto Rico
James GOODMAN* 1 , Miguel VELEZ-REYES 2 , Samuel ROSARIO 2 , Shawn HUNT 2 ,
Fernando GILBES 2
1 University of Puerto Rico at Mayaguez, Miami, FL, 2 University of Puerto Rico at
Mayaguez, Mayaguez, Puerto Rico
Remote sensing is increasingly being used as a tool to quantitatively assess the location,
distribution and relative health of coral reefs and other shallow aquatic ecosystems. As
the use of this technology continues to grow and the analysis products become more
sophisticated, there is an increasing need for comprehensive ground truth data as a means
to assess the algorithms being developed. The University of Puerto Rico at Mayagüez,
one of the core partners in the NSF sponsored Bernard M. Gordon Center for Subsurface
Sensing and Imaging Systems, is addressing this need through the development of a
fully-characterized field test environment on Enrique Reef in southwestern Puerto Rico.
This reef area contains a mixture of benthic habitats, including areas of seagrass, sand,
algae and coral, and a range of water depths, from a shallow reef flat to a steeply sloping
forereef. The objective behind the test environment is to collect multiple levels of image
and field data with which to validate physical models, inversion algorithms, feature
extraction tools and classification methods for subsurface aquatic sensing. Data collected
from Enrique Reef currently includes airborne, satellite and field-level hyperspectral and
multispectral images, in situ spectral signatures, water bio-optical properties and
information on habitat composition and benthic cover. We present a summary of the
latest results from Enrique Reef, discuss our concept of an open testbed for the remote
sensing community and solicit other users to utilize the data and participate in ongoing
system development.
17-11
Remote Sensing Of Coral Reef Biogeochemistry Based On Optical Absorptance And
Light-Use Efficiency
Eric HOCHBERG* 1 , Marlin ATKINSON 1
1 Hawaii Institute of Marine Biology, University of Hawaii, Honolulu, HI
We have developed a remote sensing technique for measuring coral reef benthic primary
productivity based on light-use efficiency and optical absorptance. The model is GPP = EdAε,
where GPP is gross primary production, Ed is seafloor-incident irradiance, A is seafloor
absorptance, and ε is the benthic community’s light-use efficiency. Both Ed and A are derivable
from various remote sensing data sources. Given appropriate values for ε, it is therefore
possible to use remote sensing to determine GPP across spatial scales (meters to many
kilometers) and in different reef environments (e.g., fore reef, reef flat). We demonstrate the
utility of our approach for measuring the range and distribution of GPP across a reef system.
Because reef calcification is inherently linked to photosynthesis, it is possible to define a
separate light-use efficiency (εcalc) and thus remotely sense that rate, as well.
17-12
An Investigation Into The Effects Of Coral Cover, Colony Size-Frequency Distribution
And Clustering On The Classification Accuracy Of Simulated Reef Images.
Alan LIM* 1 , Peter MUMBY 2 , John HEDLEY 2 , Chris ROELFSEMA 3 , Ellsworth LEDREW 1
1 University of Waterloo, Waterloo, ON, Canada, 2 University of Exeter, Exeter, United
Kingdom, 3 University of Queensland, Brisbane, Australia
Numerous studies have been conducted to compare the classification accuracy of coral reefs
maps produced from satellite and aerial imagery at different spatial or spectral resolutions or
from images processed to different levels. So far no work has been done that specifically looks
at the differing spatial elements of the coral reef ecosystem and their effects on classification
accuracy. In this study, we will examine how accuracy is affected by spatial elements of the
reefscape by investigating the effects of colony size-frequency distribution, spatial aggregation
of the coral colonies and the proportion of live coral cover at different spatial resolutions.
One of the main difficulties of such a study would be the acquisition of images that could be
used to represent these different reef-scape scenarios. Additional difficulties in using actual
imagery would include ensuring that improved accuracy in one instance was not the result of
advantageous environmental conditions or on how well the accuracy assessment was carried
out. Thus, in order to investigate these issues, we created simulated spectral reef images which
could be manipulated to reflect the desired reefscapes. With simulated images, only those
characteristics of the reef that were of interest would be allowed to vary, allowing us complete
confidence in the results of the accuracy assessments.
The spatial elements determine the proportion of pixels in each class which are spectrally
‘purer’ due to lower amount of inter-class mixing. These factors will influence the number of
‘purer’ pixels such that images with higher coral cover, colony clustering and skew will have a
greater proportion of ‘purer’ pixels. However, an increase in this proportion is not always
related to increases in levels of accuracy. An analysis of the interactions between the various
spatial elements provides an insight into how these spatial elements influence classification
accuracy.
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