Identifying four phytoplankton functional types from space: An ecological approach

Raitsos, DE; Lavender, SJ; Maravelias, CD; Haralabous, J; Richardson, AJ; Reid, PC. 2008 Identifying four phytoplankton functional types from space: An ecological approach. Limnology and Oceanography, 53 (2). 605-613.

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Abstract/Summary

Deriving maps of phytoplankton taxa based on remote sensing data using bio-optical properties of phytoplankton alone is challenging. A more holistic approach was developed using artificial neural networks, incorporating ecological and geographical knowledge together with ocean color, bio-optical characteristics, and remotely sensed physical parameters. Results show that the combined remote sensing approach could discriminate four major phytoplankton functional types (diatoms, dinoflagellates, coccolithophores, and silicoflagellates) with an accuracy of more than 70%. Models indicate that the most important information for phytoplankton functional type discrimination is spatio-temporal information and sea surface temperature. This approach can supply data for large-scale maps of predicted phytoplankton functional types, and an example is shown.

Item Type: Publication - Article
Depositing User: Miss Gemma Brice
Date made live: 26 Mar 2014 14:09
Last Modified: 06 Mar 2017 17:57
URI: http://plymsea.ac.uk/id/eprint/5902

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