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Open AccessArticle

Spectral Deconvolution for Dimension Reduction and Differentiation of Seagrasses: Case Study of Gulf St. Vincent, South Australia

1
Department of Environmental Engineering, National Cheng Kung Chung University, Tainan 701, Taiwan
2
Global Water Quality Research Center, National Cheng Kung University, Tainan 701, Taiwan
3
Department of Ecology and Evolutionary Biology, The University of Adelaide, Adelaide, South Australia 5005, Australia
4
Australian Water Quality Centre, SA Water, Adelaide, South Australia 5000, Australia
5
College of Science and Engineering, Flinders University, Adelaide, South Australia 5001, Australia
*
Authors to whom correspondence should be addressed.
Sustainability 2019, 11(13), 3695; https://doi.org/10.3390/su11133695
Received: 30 May 2019 / Revised: 1 July 2019 / Accepted: 1 July 2019 / Published: 5 July 2019
Seagrasses are a vulnerable and declining coastal habitat, which provide shelter and substrate for aquatic microbiota, invertebrates, and fishes. More accurate mapping of seagrasses is imperative for their sustainability but is hindered by the lack of data on reflectance spectra representing the optical signatures of individual species. Objectives of this study are: (1) To determine distinct characteristics of spectral profiles for sand versus three temperate seagrasses (Posidonia, Amphibolis, and Heterozostera); (2) to evaluate the most efficient derivative analysis method of spectral reflectance profiles for determining benthic types; and to assess the influences of (3) site location and (4) the water column on spectral responses. Results show that 566:689 and 566:600 bandwidth ratios are useful in separating seagrasses from sand and from detritus and algae, respectively; first-derivative reflectance spectra generally is the most efficient method, especially with deconvolution analyses further helping to reveal and isolate 11 key wavelength dimensions; and differences between sites and water column composition, which can include suspended particulate matter, both have no effect on endmembers. These findings helped develop a spectral reflectance library that can be used as an endmember reference for remote sensing, thereby providing continued monitoring, assessment, and management of seagrasses. View Full-Text
Keywords: seagrass; spectroradiometry; reflectance; optically shallow coastal waters; remote sensing; benthic bottom type seagrass; spectroradiometry; reflectance; optically shallow coastal waters; remote sensing; benthic bottom type
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Hwang, C.; Chang, C.-H.; Burch, M.; Fernandes, M.; Kildea, T. Spectral Deconvolution for Dimension Reduction and Differentiation of Seagrasses: Case Study of Gulf St. Vincent, South Australia. Sustainability 2019, 11, 3695.

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