accuracies for fish and rubble. Still, even with such low 
producer/user’s accuracies, the overall accuracies obtained 
were still high, unlike in the pixel-based classification. 
Advantages of OBIA approach: The developed rule set is 
transferrable and applicable to similar aims of obtaining benthic 
cover maps. With a little tweaking of the rule sets, similar 
outputs may be obtained quickly. 
Potential improvements: Aside from improving the rule sets, 
use of more accurate bathymetric data and image ratioing 
(blue/red and green/blue rations) will further increase the 
accuracy of OBIA classification. 
4. CONCLUSIONS & RECOMENDATIONS 
Georeferencing and mosaicking: The generated uncontrolled 
mosaic was able to produce an acceptable replica of the actual 
transected area and registration to the bathymetric data was able 
to yield good results. Therefore, in such cases where limitations 
of the available data hinder the production of a useful photo- 
mosaic, Adobe Photoshop is a useful and capable alternative. 
Performance of OBIA against pixel-based image 
classification: Pixel-based classification methods are capable 
of classifying underwater photos to benthic cover maps with 
high accuracy as long as only a general classification is 
required of off them, such as living (coral) or non-living (sand) 
classes. Inclusion of other classes, such as rubble and fish, 
confuses the classification methods such as supervised and 
unsupervised classifications. Hybrid classification was the only 
pixel-based algorithm that was able to perform well even with 
orders of classifying more than 3 classes. As for the object- 
based classification, which was capable of automatically 
identifying 4 classes, it was able to perform significantly better 
than the individual classifications, which were supervised (p- 
value = 0.0152, a = 0.05), unsupervised (p-value = 0.0005, a = 
0.05) and hybrid classification (p-value = 0.0377, a = 0.05). 
Against all pixel-based classifications, OBIA was significantly 
able to generate more accurate results (p-value = 0.0001, a = 
0.05). Therefore, OBIA is a method capable of automatically 
and accurately classifying benthic cover other than living 
(coral) and non-living (sand). 
Recommendations: Geotagging by GPS coordinates collected 
by a snorkeler swimming directly on top of the diver doing the 
video capture can provide approximate coordinates to the 
video, which may be enough for some applications and will 
also facilitate the matching of photos with the MBES data. But 
more accurate georeferencing and mosaicking (or mosaicking 
and georeferencing) is needed for accurate monitoring of reef 
conditions. In order to obtain the full potential of OBIA, 
accurate bathymetric data and underwater videos would be 
required. To minimize errors in the recorded underwater videos 
and to be able to record at any depth, an AUV with a motion 
sensor may be a better alternative in recording transects. If 
motion sensors are not available for the underwater camera, a 
bubble level may be used instead to maintain the vertical 
orientation of the video to the seafloor. If this level is still not 
available, recording should just be done in such a way that the 
camera is always perpendicular to the seafloor so as to obtain 
images that are directly beneath the camera’s lens. This way, 
georeferencing and image to image registration will have 
minimal distortions and occlusions. Controlled lighting during 
image acquisition is also recommended to minimize variations 
in the spectral characteristics of the images. Stereo pairs, as 
done in photogrammetry, may also be attempted in order to 
fully model and recreate image acquisition geometry and to 
obtain relief information of the reef, which can also be used to 
identify elevation of benthic cover. With such information, 
height may be used in the rule sets in order to identify elevated 
and non-elevated features. For this case, however, ground 
controls are needed for absolute orientation but can be very 
difficult to provide. 
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6. ACKNOWLEDGEMENTS 
This research was supported by CECAM project, funded by 
ERDT-DOST and had full guidance from Dr. Ariel C. Blanco.