Kurekin, A, Miller, PI and Van der Woerd, HJ 2014 Satellite discrimination of Karenia mikimotoi and Phaeocystis harmful algal blooms in European coastal waters: Merged classification of ocean colour data. Harmful Algae, 31. 163-176. https://doi.org/10.1016/j.hal.2013.11.003
Full text not available from this repository.Abstract/Summary
The detection of dense harmful algal blooms (HABs) by satellite remote sensing is usually based on analysis of chlorophyll-a as a proxy. However, this approach does not provide information about the potential harm of bloom, nor can it identify the dominant species. The developed HAB risk classification method employs a fully automatic data-driven approach to identify key characteristics of water leaving radiances and derived quantities, and to classify pixels into “harmful”, “non-harmful” and “no bloom” categories using Linear Discriminant Analysis (LDA). Discrimination accuracy is increased through the use of spectral ratios of water leaving radiances, absorption and backscattering. To reduce the false alarm rate the data that cannot be reliably classified are automatically labelled as “unknown”. This method can be trained on different HAB species or extended to new sensors and then applied to generate independent HAB risk maps; these can be fused with other sensors to fill gaps or improve spatial or temporal resolution. The HAB discrimination technique has obtained accurate results on MODIS and MERIS data, correctly identifying 89% of Phaeocystis globosa HABs in the southern North Sea and 88% of Karenia mikimotoi blooms in the Western English Channel. A linear transformation of the ocean colour discriminants is used to estimate harmful cell counts, demonstrating greater accuracy than if based on chlorophyll-a; this will facilitate its integration into a HAB early warning system operating in the southern North Sea.
Item Type: | Publication - Article |
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Additional Keywords: | Harmful algal blooms; Karenia mikimotoi; MODIS; Ocean colour; Phaeocystis; Remote sensing |
Subjects: | Earth Observation - Remote Sensing Ecology and Environment Marine Sciences |
Divisions: | Plymouth Marine Laboratory > Science Areas > Sea from Space (expired) |
Depositing User: | Mrs Julia Crocker |
Date made live: | 05 Aug 2014 14:28 |
Last Modified: | 06 Jun 2017 16:12 |
URI: | https://plymsea.ac.uk/id/eprint/6161 |
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