%0 Journal Article %1 oliver_bioinformatic_2004 %A Oliver, Matthew J. %A Glenn, Scott %A Kohut, Josh T. %A Irwin, Andrew J. %A Schofield, Oscar M. %A Moline, Mark A. %A Bissett, W. Paul %D 2004 %J Journal of Geophysical Research %K imported %N C7 %P C07S04 %R 10.1029/2003JC002072 %T Bioinformatic approaches for objective detection of water masses on continental shelves %U http://www.agu.org.proxy.lib.uiowa.edu/pubs/crossref/2004/2003JC002072.shtml %V 109 %X As part of the 2001 Hyper Spectral Coupled Ocean Dynamics Experiment, sea surface temperature and ocean color satellite imagery were collected for the continental shelf of the Mid-Atlantic Bight. These images were used to develop a water mass analysis and classification scheme that objectively describes the locations of water masses and their boundary locations. This technique combines multivariate cluster analysis with a newly developed genetic expression algorithm to objectively determine the number of water types in the region on the basis of ocean color and sea surface temperature measurements. Then, through boundary analysis of the water types identified, the boundaries of the major water types were mapped and the differences between them were quantified using predictor space distances. Results suggest that this approach can track the development and transport of water masses. Because the analysis combines the information of multiple predictors to describe water masses, it is an effective tool in detecting water masses not readily recognizable with temperature or chlorophyll alone.

@article{oliver_bioinformatic_2004, abstract = {As part of the 2001 Hyper Spectral Coupled Ocean Dynamics Experiment, sea surface temperature and ocean color satellite imagery were collected for the continental shelf of the Mid-Atlantic Bight. These images were used to develop a water mass analysis and classification scheme that objectively describes the locations of water masses and their boundary locations. This technique combines multivariate cluster analysis with a newly developed genetic expression algorithm to objectively determine the number of water types in the region on the basis of ocean color and sea surface temperature measurements. Then, through boundary analysis of the water types identified, the boundaries of the major water types were mapped and the differences between them were quantified using predictor space distances. Results suggest that this approach can track the development and transport of water masses. Because the analysis combines the information of multiple predictors to describe water masses, it is an effective tool in detecting water masses not readily recognizable with temperature or chlorophyll alone.}, added-at = {2017-01-09T13:57:26.000+0100}, author = {Oliver, Matthew J. and Glenn, Scott and Kohut, Josh T. and Irwin, Andrew J. and Schofield, Oscar M. and Moline, Mark A. and Bissett, W. Paul}, biburl = {https://www.bibsonomy.org/bibtex/2f4511840bc13a5684664098199507f2d/yourwelcome}, copyright = {© 2008 American Geophysical Union}, doi = {10.1029/2003JC002072}, interhash = {dbe22d11609a9a9f767464fa2ab86634}, intrahash = {f4511840bc13a5684664098199507f2d}, issn = {0148-0227}, journal = {Journal of Geophysical Research}, keywords = {imported}, language = {English}, month = jul, number = {C7}, pages = {C07S04}, timestamp = {2017-01-09T14:01:11.000+0100}, title = {Bioinformatic approaches for objective detection of water masses on continental shelves}, url = {http://www.agu.org.proxy.lib.uiowa.edu/pubs/crossref/2004/2003JC002072.shtml}, urldate = {2012-11-10}, volume = 109, year = 2004 }