Abstract
Chlorophyll a (chl-a) products calculated using medium resolution imaging spec- trometer (MERIS) data were tested. The satellite products were compared to chl-a concentra- tions measured in surface waters between 2003 and 2011 throughout the Baltic Sea. Image processing was performed with two neural-network-based MERIS data processors: the Case- 2 Water Properties processor developed at the Freie Universitat Berlin (FUB) and the Case- 2 Regional processor of the German Institute for Coastal Research (C2R). Additionally, two algorithms for deriving chl-a concentrations from atmospherically corrected reflectances origi- nally designed for Moderate Resolution Imaging Spectroradiometer and Sea-viewing Wide Field-of-view Sensor radiometers and adapted to Baltic Sea conditions were tested (algorithms denoted further as MD and SW respectively). The effectiveness of the Improved Contrast between Ocean and Land (ICOL) processor was also verified. Our results showed that the accu- racy of chl-a concentration retrieval from satellite data varies depending on the location of the area. The difference in the statistical error between results from optically different coastal and open sea waters was as high as 200%. The most accurate results for the coastal zone were noted for the standard chl-a FUB processor product, while in open sea waters the highest accuracy was noted for the MD and SW algorithms with reflectance derived from the FUB processor. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. (DOI: 10.1117/1.JRS.8.083605)
Highlights
Phytoplankton is an important component of all marine ecosystems
The aim of this work was to compare the performance of standard chl-a concentration products of two different neural-network-based (NN) processors developed for medium resolution imaging spectrometer (MERIS) data and two other band ratio algorithms for retrieving chl-a concentrations acquired for the Baltic Sea
It is proposed that both MD and SW can be used with similar error for MERIS and, in the future, Ocean and Land Colour Instrument (OLCI) data
Summary
Phytoplankton is an important component of all marine ecosystems. Chlorophyll a (chl-a) is the most common photosynthetically active pigment present in all phytoplankton species. Its concentration is a good indicator of phytoplankton biomass and it is frequently used for water quality assessment.[1] The concentration of this pigment is influenced by environmental factors such as water temperature, light intensity, and nutrient concentrations.2,3The presence of chlorophyll a influences the optical properties of sea water; concentrations of it can be retrieved from data acquired by satellite spectrometers operating in the solar reflective spectral range. These data can be used to monitor spatial and seasonal variations in the near-surface phytoplankton biomass. These algorithms work satisfactorily with Case-1 waters,[5,6] but with more complex Case-2 waters their accuracy is not as good because the radiance signal recorded by satellite sensors is influenced by high concentrations of colored dissolved organic matter (CDOM, called yellow substances) and suspended particulate matter (SPM) in which detritus and mineral particles can occur in varying proportions.[7,8,9]
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