Email the author 
Analysis of Seagrass Condition Using Spectral Reflection of Quickbird Imagery on Saronde Island North Gorontalo
Abstract
This study was encouraged by the importance of understanding the conditions of seagrass which becomes the source of food for many species of marine fish. Seagrass condition will indirectly affect the quantity and quality of fish obtained by fishermen who live in coastal areas. High-resolution imagery can simplify and accelerate data collection process of conditions of seagrass on the outer islands of Gorontalo Province. This study used digital remote sensing method using unsupervised classification and also assisted by the measurements of the transcule based on the pixel size that aims to detect and to match the information obtained from QuickBird imagery, to ultimately obtain information about seagrass condition. Seagrass with abundant/good condition can be found at station 1,3,4,5, and 6 with an average cover up to 67,70%, 63,54%, 68,75%, 62,5%, and 65,62% respectively. Meanwhile, seagrass with the less abundant/poor condition can be found at station 2 with an average cover up to 50% and at station 7 with an average cover up to 52,08%. Distribution of seagrass on Saronde Island covers up to 6. 9654 Ha. Seagrass with abundant/good condition covers 4,2025 Ha, and lowly abundant/poor seagrass covers 2,7629 Ha. Seagrass on Saronde Island is still in abundant/good condition with an average cover up to 61,45 % and form mixed vegetation.
Keywords
Full Text:
PDFReferences
Gray, C. A., McElligott, D. J., & Chick, R. C. (1996). Intra- and inter-estuary differences in assemblages of fishes associated with shallow seagrass and bare sand. Marine and Freshwater Research. https://doi.org/10.1071/MF9960723
Hochberg, E. J., & Atkinson, M. J. (2003). Capabilities of remote sensors to classify coral, algae, and sand as pure and mixed spectra. Remote Sensing of Environment. https://doi.org/10.1016/S0034-4257(02)00202-X
Hutomo, M., & Peristiwady, T. (1996). Diversity, abundance and diet of fish in the seagrass beds of Lombok Island, Indonesia. In Seagrass Biology: Proceedings of an International Workshop’.(Eds J. Kuo, RC Phillips, DI Walker and H. Kirkman.) pp (pp. 205–212).
Kuriandewa, T. E., & Supriyadi, I. H. (2006). Seagrass mapping in East Bintan coastal area, Riau archipelago, Indonesia. Coastal Marine Science, 30(1), 154–161.
Kutser, T., Dekker, A. G., & Skirving, W. (2003). Modeling spectral discrimination of Great Barrier Reef benthic communities by remote sensing instruments. Limnology and Oceanography. https://doi.org/10.4319/lo.2003.48.1_part_2.0497
Larkum, A. W. D., & West, R. J. (1990). Long-term changes of seagrass meadows in Botany Bay, Australia. Aquatic Botany. https://doi.org/10.1016/0304-3770(90)90064-R
Mumby, P. J., Edwards, A. J., Arias-González, J. E., Lindeman, K. C., Blackwell, P. G., Gall, A., … Llewenyn, G. (2004). Mangroves enhance the biomass of coral reef fish communities in the Caribbean. Nature. https://doi.org/10.1038/nature02286
Mumby, P. J., Green, E. P., Edwards, A. J., & Clark, C. D. (1999). The cost-effectiveness of remote sensing for tropical coastal resources assessment and management. Journal of Environmental Management. https://doi.org/10.1006/jema.1998.0255
Rahmawati, S., Hutomo, M., & Azkab, M. H. (2014). Panduan Monitoring Padang Lamun. (M. Hutomo & A. Nontji, Eds.). Bogor: COREMAP - CTI Lembaga Ilmu Pengetahuan Indonesia. Retrieved from coremap.or.id/downloads/Lamun-27022015.pdf
Supriyadi, I. H. (2008). Pemetaan kondisi lamun dan bahaya ancamannya dengan menggunakan citra satelit ALOS di pesisir selatan, Bitung Manado, Sulawesi Utara. Oseanologi Dan Limpnologi Di Indonesia, 34(3), 556–459.
Supriyadi, I. H. (2009). Pemetaan lamun dan biota asosiasi untuk identifikasi daerah perlindungan lamun di Teluk Kotania dan Pelitajaya. Oseanologi Dan Limnologi Di Indonesia, 45(2), 167–183.
Supriyadi, I. H., & Kuriandewa, T. E. (2008). Seagrass Distribution at Small Islands: Derawan Archipelago, East Kalimantan Province, Indonesia. Oseanologi Dan Limpnologi Di Indonesia, 34(1), 83–99.
Yamamuro, M., Nishimura, K., Kishimoto, K., Nozaki, K., Kato, K., Negishi, A., … Fukuoka, K. (2003). Mapping tropical seagrass beds with an underwater remotely operated vehicle (ROV). Japan International Marine Science and Technology Federation. Japan International Marine Science and Technology Federation.
DOI: https://doi.org/10.34312/jgeosrev.v1i1.2015
Copyright (c) 2019 Jambura Geoscience Review
This work is licensed under a Creative Commons Attribution 4.0 International License.
Jambura Geoscience Review (P-ISSN: 2623-0682, E-ISSN: 2656-0380) is licensed under a Creative Commons Attribution 4.0 International License.