Abstract
Sargassum species grow on rocks and dead coral, forming dense seaweed beds in their growth seasons. Sargassum beds play a range of ecological roles in coastal waters, but their sustainability is threatened by pollution and reclamation within ASEAN countries with rapid economic growth. Before conservation initiatives can be implemented, it is necessary to establish their present distribution. These beds can be mapped using the noncommercial satellite, ALOS, which can provide multiband images using high spatial resolution optical sensors (sensitive to 10 m-2 plots), AVNIR-2. These images are of sufficient quality for examining coastal ecosystems and, in this study, for mapping the Sargassum beds in the waters off the coast of Sattahip, Chon Buri Province, Thailand. This coastal zone is a natural marine park reserve and protected from human activities such as fishery and reclamation. Biomass data were obtained in January, February, March, and December 2009 from quadrat sampling. The biomass of Sargassum aquifolium (Turner) C.Agardh at a bottom depth of 1 m and 1.5–2 m was determined to be 7.73 and 92.75 g dw m-2, while that of Sargassum oligocystum Montagne was found to be 44.05 and 87.97 g dw m-2, respectively. Ground truth data were obtained in February and October 2012 from serial images taken by manta tow. Supervised classification is a procedure for identifying spectrally similar areas on an image by identifying “training” sites of known targets and then extrapolating those spectral signatures to other areas of unknown targets. By applying this methodology, the Sargassum beds off Sattahip can be detected with an accuracy of about 70%. It is estimated that the error is caused by mixel effects of the bottom substrates in individual pixels, each of which covers an area of 10×10 m. Our results indicate that the images captured by ALOS AVNIR-2 are informative and useful for mapping the Sargassum beds in Southeast Asia.
Acknowledgments
We would like to thank JAXA for providing ALOS AVNIR-2 data central to this study. This research study represents a component of the research conducted under the Environment Research and Technology Development Fund (S9) of the Ministry of the Environment in Japan, and from the Japan Science and Technology Agency (JST/CREST). We also gratefully acknowledge the sponsors of this study, which was conducted under the network of the Asian CORE Program of the Japan Society for the promotion of Science, “Establishment of research and education network on coastal marine science in Southeast Asia,” and the Ocean Remote Sensing Project for Coastal Habitat Mapping (WESTPAC-ORSP: PAMPEC III) of Intergovernmental Oceanographic Commission Sub-Commission for the Western Pacific supported by Japanese Funds-in-Trust provided by the Ministry of Education, Culture, Sports, Science and Technology in Japan.
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