Paper
25 October 2010 Image processing for smarter browsing of ocean color data products: investigating algal blooms
Jer Hayes, Edel O'Connor, King-Tong Lau, Noel E. O'Connor, Alan F. Smeaton, Dermot Diamond
Author Affiliations +
Abstract
Remote sensing technology continues to play a significant role in the understanding of our environment and the investigation of the Earth. Ocean color is the water hue due to the presence of tiny plants containing the pigment chlorophyll, sediments, and colored dissolved organic material and so can provide valuable information on coastal ecosystems. We propose to make the browsing of Ocean Color data more efficient for users by using image processing techniques to extract useful information which can be accessible through browser searching. Image processing is applied to chlorophyll and sea surface temperature images. The automatic image processing of the visual level 1 and level 2 data allow us to investigate the occurrence of algal blooms. Images with colors in a certain range (red, orange etc.) are used to address possible algal blooms and allow us to examine the seasonal variation of algal blooms in Europe (around Ireland and in the Baltic Sea). Yearly seasonal variation of algal blooms in Europe based on image processing for smarter browsing of Ocean Color are presented.
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Jer Hayes, Edel O'Connor, King-Tong Lau, Noel E. O'Connor, Alan F. Smeaton, and Dermot Diamond "Image processing for smarter browsing of ocean color data products: investigating algal blooms", Proc. SPIE 7831, Earth Resources and Environmental Remote Sensing/GIS Applications, 78310P (25 October 2010); https://doi.org/10.1117/12.864949
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image processing

Image analysis

Clouds

Satellites

Sensors

Ecosystems

Environmental sensing

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