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

Charnsmorn Hwang, Chih-Hua Chang, Michael Burch, Milena Fernandes and Tim Kildea
Additional contact information
Charnsmorn Hwang: Department of Environmental Engineering, National Cheng Kung Chung University, Tainan 701, Taiwan
Chih-Hua Chang: Department of Environmental Engineering, National Cheng Kung Chung University, Tainan 701, Taiwan
Michael Burch: Department of Ecology and Evolutionary Biology, The University of Adelaide, Adelaide, South Australia 5005, Australia
Milena Fernandes: Australian Water Quality Centre, SA Water, Adelaide, South Australia 5000, Australia
Tim Kildea: Australian Water Quality Centre, SA Water, Adelaide, South Australia 5000, Australia

Sustainability, 2019, vol. 11, issue 13, 1-14

Abstract: 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.

Keywords: seagrass; spectroradiometry; reflectance; optically shallow coastal waters; remote sensing; benthic bottom type (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/13/3695/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/13/3695/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:13:p:3695-:d:245929

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().