1 January 2011 Improved monitoring of phytoplankton bloom dynamics in a Norwegian fjord by integrating satellite data, pigment analysis, and Ferrybox data with a coastal observation network
Zsolt Volent, Geir Johnsen, Erlend K. Hovland, Are Folkestad, Lasse M. Olsen, Karl Tangen, Kai Sorensen
Author Affiliations +
Abstract
Monitoring of the coastal environment is vitally important as these areas are of economic value and at the same time highly exposed to anthropogenic influence, in addition to variation of environmental variables. In this paper we show how the combination of bio-optical data from satellites, analysis of water samples, and a ship-mounted automatic flow-through sensor system (Ferrybox) can be used to detect and monitor phytoplankton blooms both spatially and temporally. Chlorophyll a (Chl a) data and turbidity from Ferrybox are combined with remotely sensed Chl a and total suspended matter from the MERIS instrument aboard the satellite ENVISAT (ENVIronmental SATellite) European Space Agency. Data from phytoplankton speciation and enumeration obtained by a national coastal observation network consisting of fish farms and the Norwegian Food Safety Authority are supplemented with data on phytoplankton pigments. All the data sets are then integrated in order to describe phytoplankton bloom dynamics in a Norwegian fjord over a growth season, with particular focus on Emiliania huxleyi. The approach represents a case example of how coastal environmental monitoring can be improved with existing instrument platforms. The objectives of the paper is to present the operative phytoplankton monitoring scheme in Norway, and to present an improved model of how such a scheme can be designed for a large part of the world's coastal areas.
©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Zsolt Volent, Geir Johnsen, Erlend K. Hovland, Are Folkestad, Lasse M. Olsen, Karl Tangen, and Kai Sorensen "Improved monitoring of phytoplankton bloom dynamics in a Norwegian fjord by integrating satellite data, pigment analysis, and Ferrybox data with a coastal observation network," Journal of Applied Remote Sensing 5(1), 053561 (1 January 2011). https://doi.org/10.1117/1.3658032
Published: 1 January 2011
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CITATIONS
Cited by 14 scholarly publications.
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KEYWORDS
Satellites

Remote sensing

RGB color model

Satellite imaging

Statistical analysis

Earth observing sensors

Environmental monitoring

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