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, Tim Kildea

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
Article number3695
JournalSustainability (Switzerland)
Volume11
Issue number13
DOIs
Publication statusPublished - 2019 Jul 1

Fingerprint

spectral reflectance
Deconvolution
deconvolution
reflectance
water column
water
sand
suspended particulate matter
shelter
detritus
habitat
Sand
invertebrate
alga
sustainability
monitoring
Derivatives
wavelength
remote sensing
substrate

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law

Cite this

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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.",
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Spectral deconvolution for dimension reduction and differentiation of seagrasses : Case study of Gulf St. Vincent, South Australia. / Hwang, Charnsmorn; Chang, Chih-Hua; Burch, Michael; Fernandes, Milena; Kildea, Tim.

In: Sustainability (Switzerland), Vol. 11, No. 13, 3695, 01.07.2019.

Research output: Contribution to journalArticle

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