Remote sensing of underwater vegetation using single-beam acoustics

A single-beam, acoustic, ground-discrimination system (QTC VIEW, Series V) was used to study the distribution of underwater macrophytes in a shallow-water coastal system, employing frequencies of 50 and 200 kHz. The study was conducted in Mar Menor, SE Spain, where the expansion of Caulerpa prolifera has contributed to the silting up of the superficial sediments. A direct relationship was identified between algal biomass and sediment-fines content. Acoustic information on sediment grain size and data on algal biomass were obtained in muddy and sandy sediments, including vegetated and non-vegetated seabed. Non-vegetated muddy areas were created by diving and handpicking the algae. The multivariate acoustic data were analysed under the null hypotheses that there were no acoustic differences between bare seabeds with contrasting superficial sediment types or among low, medium, and high algal-biomass areas, having in mind that grain size can act as a confounding factor. Both null hypotheses were rejected, and the results showed that 200 kHz was better than 50 kHz in distinguishing cover levels of algal biomass. The relationship between the 200-kHz acoustic data and algal biomass suggests utility in modelling the latter using the former.

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Quintino V. Freitas R. Mamede R. Ricardo F. Rodrigues A.M. Mota J. Perez-Ruzafa A. y Marcos C. Remote sensing of underwater vegetation using single-beam acoustics. Oxford University Press, 2009. https://doi.org/10.1093/icesjms/fsp251

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Resource type Article
Date of creation 2024-11-05
Date of last revision 2024-11-05
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Metadata identifier 20c1fe6f-c0e9-5e5e-a1f2-bc66ca52435c
Metadata language Spanish
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High-value dataset category Earth observation and environment
ISO 19115 topic category biota
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Name of the dataset creator Quintino, V., Freitas, R., Mamede, R., Ricardo, F., Rodrigues, A.M., Mota, J., Perez-Ruzafa, A. y Marcos, C.
Name of the dataset editor Oxford University Press
Other identifier DOI: 10.1093/icesjms/fsp251
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Email of the dataset creator victor.quintino@ua.pt
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