Phytoplankton Group Identification Using Simulated and In-situ Hyperspectral Remote Sensing Reflectance


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hongyan.xi [ at ] awi.de

Abstract

Given that the commonly used parameter obtained directly from hyperspectral earth observation sensors is the remote sensing reflectance (Rrs), we focused on identification of dominant phytoplankton groups by using Rrs spectra directly. Based on five standard absorption spectra representing five different phytoplankton spectral groups, a simulated database of Rrs (C2X database, compiled within the ESA SEOM C2X Project) that includes 105 different water optical conditions was built with HydroLight. In our previous study we have proposed an identification approach to determine phytoplankton groups with the use of simulated C2X data, and the skill of the identification were also tested by investigating how and to what extend water optical constituents (Chl, NAP, and CDOM) impact the accuracy of this identification (Xi et al. 2017). To furthermore test whether the approach is applicable in various natural waters, we have collected a large set of in situ data from waters with different optical types, including coastal waters such as the German Bight and British coastal waters, and inland waters such as Elbe River and several lakes in Germany. Both in situ Rrs and absorption spectra (ap) are used to identify the dominating phytoplankton group in these waters. Identification results from both approaches are compared, and the identification performance of the Rrs-based approach can therefore be evaluated for natural water applications.



Item Type
Conference (Poster)
Authors
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Primary Division
Programs
Primary Topic
Research Networks
Peer revision
Not peer-reviewed
Publication Status
Published
Event Details
HIGHROC Science Conference, 07 Nov 2017 - 09 Nov 2017, Brussels.
Eprint ID
48270
Cite as
Xi, H. , Hieronymi, M. , Krasemann, H. and Röttgers, R. (2017): Phytoplankton Group Identification Using Simulated and In-situ Hyperspectral Remote Sensing Reflectance , HIGHROC Science Conference, Brussels, 7 November 2017 - 9 November 2017 .


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