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Improvements to the Phytodoas Method for Identification of Major Phytoplankton Groups Using Hyper-spectral Satellite Data : Volume 8, Issue 6 (23/11/2011)

By Sadeghi, A.

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Book Id: WPLBN0003972788
Format Type: PDF Article :
File Size: Pages 41
Reproduction Date: 2015

Title: Improvements to the Phytodoas Method for Identification of Major Phytoplankton Groups Using Hyper-spectral Satellite Data : Volume 8, Issue 6 (23/11/2011)  
Author: Sadeghi, A.
Volume: Vol. 8, Issue 6
Language: English
Subject: Science, Ocean, Science
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Dinter, T., Taylor, B., Bracher, A., Vountas, M., Peeken, I., & Sadeghi, A. (2011). Improvements to the Phytodoas Method for Identification of Major Phytoplankton Groups Using Hyper-spectral Satellite Data : Volume 8, Issue 6 (23/11/2011). Retrieved from

Description: Institute of Environmental Physics, University of Bremen, Bremen, Germany. The goal of this study was to improve PhytoDOAS, which is a new retrieval method for quantitative identification of major Phytoplankton Functional Types (PFTs) using hyper-spectral satellite data. PhytoDOAS is an extension of the Differential Optical Absorption Spectroscopy (DOAS, a method for detection of atmospheric trace gases), developed for remote identification of oceanic phytoplankton groups. Thus far, PhytoDOAS has been successfully exploited to identify cyanobacteria and diatoms over the global ocean from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) hyper-spectral data. The main challenge for retrieving more PFTs by PhytoDOAS is to overcome the correlation effects between different PFTs' absorption spectra. Different PFTs are composed of different types and amounts of pigments, but also have pigments in common, e.g., chl-a, causing correlation effects in the usual performance of the PhytoDOAS retrieval. Two ideas have been implemented to improve PhytoDOAS for the PFT retrieval of more phytoplankton groups. Firstly, using the fourth-derivative spectroscopy, the peak positions of the main pigment components in each absorption spectrum have been derived. After comparing the corresponding results of major PFTs, the optimized fit-window for the PhytoDOAS retrieval of each PFT was determined. Secondly, based on the results from derivative spectroscopy, simultaneous fit of PhytoDOAS has been proposed and tested for a selected set of PFTs (coccolithophores, diatoms and dinoflagllates) within an optimized fit-window. The method was then applied to the processing of SCIAMACHY data over the year 2005. Comparisons of the PhytoDOAS PFT retrievals in 2005 with the modeled PFT data from the NASA Ocean Biochemical Model (NOBM) showed similar patterns in their seasonal distributions for diatoms and coccolithophores, especially in the northern parts of the global ocean. The seasonal patterns of the PhytoDOAS coccolithophores indicated very good agreement with the global distributions of Particulate Inorganic Carbon (PIC) provided by MODIS (MODerate resolution Imaging Spectroradiometer)-Aqua level-3 products. Since PIC is known as a proxy for the abundance of coccolithophores (in open ocean), the latter agreement indicates the basic functionality of the method in retrieving coccolithophores. Moreover, as a case study, the simultaneous mode of PhytoDOAS has been applied to SCIAMACHY data for detecting a coccolithophore bloom around New Zealand (reported by NASA from MODIS imagery in December 2009); the result was quite consistent with the MODIS RGB image and the MODIS PIC map of the bloom, indicating the functionality of the method in short-term retrievals.

Improvements to the PhytoDOAS method for identification of major phytoplankton groups using hyper-spectral satellite data

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