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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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 |
work_keys_str_mv |
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