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Proceedings Paper

Application of neural networks to AVHRR chlorophyll-a and turbidity estimation
Author(s): Yuanzhi Zhang; Jouni Pulliainen; Sampsa Koponen; Martti Hallikainen
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Paper Abstract

This paper presents the application of neural networks to chlorophyll-a and turbidity estimation using AVHRR data over the Gulf of Finland. Chlorophyll-a and turbidity are two major parameters in surface waters used for monitoring coastal water quality in the study. Since the Gulf of Finland is highly affected by the input from the rivers where have a high concentration of mineral suspended solids and nutrients, the coastal waters of the Gulf are optically dominated by absorption from both dissolved and particulate organic matters. Although AVHRR imagery can provide a synoptic view on surface water information of coastal areas, its quantitative use is still a difficult task in this study.

Paper Details

Date Published: 14 January 2002
PDF: 9 pages
Proc. SPIE 4488, Ocean Optics: Remote Sensing and Underwater Imaging, (14 January 2002); doi: 10.1117/12.452813
Show Author Affiliations
Yuanzhi Zhang, Helsinki Univ. of Technology (Finland)
Jouni Pulliainen, Helsinki Univ. of Technology (Finland)
Sampsa Koponen, Helsinki Univ. of Technology (Finland)
Martti Hallikainen, Helsinki Univ. of Technology (Finland)

Published in SPIE Proceedings Vol. 4488:
Ocean Optics: Remote Sensing and Underwater Imaging
Robert J. Frouin; Robert J. Frouin; Gary D. Gilbert, Editor(s)

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