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Proceedings Paper

Hyperspectral water quality retrieval model: taking Malaysia inshore sea area as an example
Author(s): Tingwei Cui; Jie Zhang; Yi Ma; Jing Li; Boonleong Lim; Samad Roslinah
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Paper Abstract

Remote sensing technique provides the possibility of rapid and synchronous monitoring in a large area of the water quality, which is an important element for the aquatic ecosystem quality assessment of islands and coastal zones, especially for the nearshore and tourism sea area. Tioman Island of Malaysia is regarded as one of ten of the best islands in the world and attracts tourists from all over the world for its clear sea, beautiful seashore and charming scenery. In this paper, on the basis of in situ dataset in the study area, distribution discipline of water quality parameters is analyzed to find that phytoplankton pigment, rather than suspended sediment is the main water quality parameter in the study area; seawater there is clean but not very oligotrophic; seawater spectra contains distinct features. Then water quality hyperspectral retrieval models are developed based on in situ data to calculate the chlorophyll a concentration ([chl-a]), transparency (SD) with satisfactory performance. It's suggested that model precision should be validated further using more in-situ data.

Paper Details

Date Published: 14 November 2007
PDF: 5 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679036 (14 November 2007); doi: 10.1117/12.750915
Show Author Affiliations
Tingwei Cui, State Oceanic Administration (China)
Jie Zhang, State Oceanic Administration (China)
Key Lab. of Marine Science and Numerical Modeling (China)
Yi Ma, State Oceanic Administration (China)
Key Lab. of Marine Science and Numerical Modeling (China)
Jing Li, Beijing Normal Univ. (China)
Boonleong Lim, Cilix Corp. Sdn Bhd (Malaysia)
Samad Roslinah, Malaysian Ctr. for Remote Sensing (Malaysia)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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