Marine Science Faculty Publications
Finding Green River in Seawifs Satellite Images
Document Type
Article
Publication Date
2000
Abstract
Understanding oceanic primary production on a global scale can be enhanced by methods that are able to automatically track phytoplankton blooms from color satellite images. In this paper, unsupervised clustering and rule learning are combined to track green river, a plume of discolored water that forms every March-May offshore along the edge of the west Florida Shelf, from the Sea Viewing Wide Field of View Sensor which began flying in late 1997. Spatial information and sea surface temperature can be integrated into the approach to improve performance. Using cross-validation experiments over a series of 59 multi-spectral images, it is shown that the developed system is able to reliably discriminate between images with green river from those with no phytoplankton blooms or other kinds of blooms. It is also effective in identifying the region which the green river covers.
Citation / Publisher Attribution
Proceedings - International Conference on Pattern Recognition, v. 15, issue 2, p. 307-310
Scholar Commons Citation
Yao, W.; Hall, L. O.; Goldgof, Dmitry B.; and Muller-Karger, Frank E., "Finding Green River in Seawifs Satellite Images" (2000). Marine Science Faculty Publications. 1168.
https://digitalcommons.usf.edu/msc_facpub/1168
