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Light Penetration Ability Assessment of Satellite Band for Seagrass Detection Using Landsat 8 OLI Satellite Data

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Book cover Computational Science and Its Applications -- ICCSA 2016 (ICCSA 2016)

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Abstract

Seagrass distribution is controlled by light availability, especially at the deepest edge of the meadow. Light attenuation due to both natural and anthropogenically-driven processes leads to reduced photosynthesis. Reliability of satellite-based seagrass mapping under different water clarity that has different attenuation coefficient value is still not fully known. Understanding the minimum light requirements for growth is crucial when light conditions are insufficient to maintain a positive carbon balance, leading to a decline in seagrass growth and distribution. By comparing the seagrass-detected pixels at two different coastal locations with the corresponding depth from the nautical chart, the assessment of seagrass map derived from Landsat 8 OLI satellite data were performed. We presented the assessment of light penetration capability of Landsat 8 OLI bands in typical tropical coastal water of Malaysia, with special attention on the different water clarity that has different amount of light deprivation on the seagrass meadow.

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Acknowledgements

We gratefully acknowledge a Long-Term Research Grant Scheme (LRGS)-Seagrass Biomass From Satellite Remote Sensing-R.J130000.7309.4B094, 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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Correspondence to Mazlan Hashim .

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Misbari, S., Hashim, M. (2016). Light Penetration Ability Assessment of Satellite Band for Seagrass Detection Using Landsat 8 OLI Satellite Data. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9788. Springer, Cham. https://doi.org/10.1007/978-3-319-42111-7_21

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  • DOI: https://doi.org/10.1007/978-3-319-42111-7_21

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  • Publisher Name: Springer, Cham

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