Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra

The emergence of hyperspectral optical satellite sensors for ocean observation provides potential for more detailed information from aquatic ecosystems. The German hyperspectral satellite mission EnMAP (enmap.org) currently in the production phase is supported by a project to explore the capability...

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Main Authors: Hongyan Xi, Martin Hieronymi, Rüdiger Röttgers, Hajo Krasemann, Zhongfeng Qiu
Format: Article
Language:English
Published: MDPI AG 2015-11-01
Series:Remote Sensing
Subjects:
QAA
Online Access:http://www.mdpi.com/2072-4292/7/11/14781
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spelling doaj-9e8198e2a76642ed854016e7c2fd3e5d2020-11-24T22:09:18ZengMDPI AGRemote Sensing2072-42922015-11-01711147811480510.3390/rs71114781rs71114781Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption SpectraHongyan Xi0Martin Hieronymi1Rüdiger Röttgers2Hajo Krasemann3Zhongfeng Qiu4Institute for Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, Geesthacht 21502, GermanyInstitute for Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, Geesthacht 21502, GermanyInstitute for Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, Geesthacht 21502, GermanyInstitute for Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, Geesthacht 21502, GermanySchool of Marine Sciences, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, ChinaThe emergence of hyperspectral optical satellite sensors for ocean observation provides potential for more detailed information from aquatic ecosystems. The German hyperspectral satellite mission EnMAP (enmap.org) currently in the production phase is supported by a project to explore the capability of using EnMAP data and other future hyperspectral data from space. One task is to identify phytoplankton taxonomic groups. To fulfill this objective, on the basis of laboratory-measured absorption coefficients of phytoplankton cultures (aph(λ)) and corresponding simulated remote sensing reflectance spectra (Rrs(λ)), we examined the performance of spectral fourth-derivative analysis and clustering techniques to differentiate six taxonomic groups. We compared different sources of input data, namely aph(λ), Rrs(λ), and the absorption of water compounds obtained from inversion of the Rrs(λ)) spectra using a quasi-analytical algorithm (QAA). Rrs(λ) was tested as it can be directly obtained from hyperspectral sensors. The last one was tested as expected influences of the spectral features of pure water absorption on Rrs(λ) could be avoided after subtracting it from the inverted total absorption. Results showed that derivative analysis of measured aph(λ) spectra performed best with only a few misclassified cultures. Based on Rrs(λ) spectra, the accuracy of this differentiation decreased but the performance was partly restored if wavelengths of strong water absorption were excluded and chlorophyll concentrations were higher than 1 mg∙m−3. When based on QAA-inverted absorption spectra, the differentiation was less precise due to loss of information at longer wavelengths. This analysis showed that, compared to inverted absorption spectra from restricted inversion models, hyperspectral Rrs(λ) is potentially suitable input data for the differentiation of phytoplankton taxonomic groups in prospective EnMAP applications, though still a challenge at low algal concentrations.http://www.mdpi.com/2072-4292/7/11/14781phytoplankton taxonomic groupsEnMAPremote sensing reflectanceabsorptionderivative analysisQAA
collection DOAJ
language English
format Article
sources DOAJ
author Hongyan Xi
Martin Hieronymi
Rüdiger Röttgers
Hajo Krasemann
Zhongfeng Qiu
spellingShingle Hongyan Xi
Martin Hieronymi
Rüdiger Röttgers
Hajo Krasemann
Zhongfeng Qiu
Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra
Remote Sensing
phytoplankton taxonomic groups
EnMAP
remote sensing reflectance
absorption
derivative analysis
QAA
author_facet Hongyan Xi
Martin Hieronymi
Rüdiger Röttgers
Hajo Krasemann
Zhongfeng Qiu
author_sort Hongyan Xi
title Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra
title_short Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra
title_full Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra
title_fullStr Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra
title_full_unstemmed Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra
title_sort hyperspectral differentiation of phytoplankton taxonomic groups: a comparison between using remote sensing reflectance and absorption spectra
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2015-11-01
description The emergence of hyperspectral optical satellite sensors for ocean observation provides potential for more detailed information from aquatic ecosystems. The German hyperspectral satellite mission EnMAP (enmap.org) currently in the production phase is supported by a project to explore the capability of using EnMAP data and other future hyperspectral data from space. One task is to identify phytoplankton taxonomic groups. To fulfill this objective, on the basis of laboratory-measured absorption coefficients of phytoplankton cultures (aph(λ)) and corresponding simulated remote sensing reflectance spectra (Rrs(λ)), we examined the performance of spectral fourth-derivative analysis and clustering techniques to differentiate six taxonomic groups. We compared different sources of input data, namely aph(λ), Rrs(λ), and the absorption of water compounds obtained from inversion of the Rrs(λ)) spectra using a quasi-analytical algorithm (QAA). Rrs(λ) was tested as it can be directly obtained from hyperspectral sensors. The last one was tested as expected influences of the spectral features of pure water absorption on Rrs(λ) could be avoided after subtracting it from the inverted total absorption. Results showed that derivative analysis of measured aph(λ) spectra performed best with only a few misclassified cultures. Based on Rrs(λ) spectra, the accuracy of this differentiation decreased but the performance was partly restored if wavelengths of strong water absorption were excluded and chlorophyll concentrations were higher than 1 mg∙m−3. When based on QAA-inverted absorption spectra, the differentiation was less precise due to loss of information at longer wavelengths. This analysis showed that, compared to inverted absorption spectra from restricted inversion models, hyperspectral Rrs(λ) is potentially suitable input data for the differentiation of phytoplankton taxonomic groups in prospective EnMAP applications, though still a challenge at low algal concentrations.
topic phytoplankton taxonomic groups
EnMAP
remote sensing reflectance
absorption
derivative analysis
QAA
url http://www.mdpi.com/2072-4292/7/11/14781
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