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A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans

Blondeau-Patissier, David, Gower, James F. R., Dekker, Arnold G., Phinn, Stuart R. and Brando, Vittorio E. (2014). A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans. Progress in Oceanography,123:123-144.

Document type: Journal Article
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IRMA ID 84376995xPUB52
Title A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans
Author Blondeau-Patissier, David
Gower, James F. R.
Dekker, Arnold G.
Phinn, Stuart R.
Brando, Vittorio E.
Journal Name Progress in Oceanography
Publication Date 2014
Volume Number 123
ISSN 0079-6611   (check CDU catalogue  open catalogue search in new window)
Scopus ID 2-s2.0-84899059319
Start Page 123
End Page 144
Total Pages 22
Place of Publication United Kingdom
Publisher Pergamon Press
HERDC Category C1 - Journal Article (DIISR)
Abstract The need for more effective environmental monitoring of the open and coastal ocean has recently led to notable advances in satellite ocean color technology and algorithm research. Satellite ocean color sensors’ data are widely used for the detection, mapping and monitoring of phytoplankton blooms because earth observation provides a synoptic view of the ocean, both spatially and temporally. Algal blooms are indicators of marine ecosystem health; thus, their monitoring is a key component of effective management of coastal and oceanic resources. Since the late 1970s, a wide variety of operational ocean color satellite sensors and algorithms have been developed. The comprehensive review presented in this article captures the details of the progress and discusses the advantages and limitations of the algorithms used with the multi-spectral ocean color sensors CZCS, SeaWiFS, MODIS and MERIS. Present challenges include overcoming the severe limitation of these algorithms in coastal waters and refining detection limits in various oceanic and coastal environments. To understand the spatio-temporal patterns of algal blooms and their triggering factors, it is essential to consider the possible effects of environmental parameters, such as water temperature, turbidity, solar radiation and bathymetry. Hence, this review will also discuss the use of statistical techniques and additional datasets derived from ecosystem models or other satellite sensors to characterize further the factors triggering or limiting the development of algal blooms in coastal and open ocean waters.
DOI http://dx.doi.org/10.1016/j.pocean.2013.12.008   (check subscription with CDU E-Gateway service for CDU Staff and Students  check subscription with CDU E-Gateway in new window)
 
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