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Proceedings Paper

Image processing for smarter browsing of ocean color data products: investigating algal blooms
Author(s): Jer Hayes; Edel O'Connor; King-Tong Lau; Noel E. O'Connor; Alan F. Smeaton; Dermot Diamond
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Paper 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.

Paper Details

Date Published: 25 October 2010
PDF: 7 pages
Proc. SPIE 7831, Earth Resources and Environmental Remote Sensing/GIS Applications, 78310P (25 October 2010); doi: 10.1117/12.864949
Show Author Affiliations
Jer Hayes, Dublin City Univ. (Ireland)
IBM Ireland (Ireland)
Edel O'Connor, Dublin City Univ. (Ireland)
King-Tong Lau, Dublin City Univ. (Ireland)
Noel E. O'Connor, Dublin City Univ. (Ireland)
Alan F. Smeaton, Dublin City Univ. (Ireland)
Dermot Diamond, Dublin City Univ. (Ireland)


Published in SPIE Proceedings Vol. 7831:
Earth Resources and Environmental Remote Sensing/GIS Applications
Ulrich Michel; Daniel L. Civco, Editor(s)

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