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Proceedings Paper

An improved calculation normalized water-leaving radiance by in-water radiometric profile data
Author(s): Erhui Huang; Shujing Li; Xianqiang He; Delu Pan
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Paper Abstract

There are usually three calculation methods of normalized water-leaving radiance in use of in-water radiometric profile data the local linear regression method is the commonly used one for its simple principle and processing. However this method need manual selection of the regression depth interval the results are mostly affected by subjective factors of processors which can lead to 5%-45% errors with different depth intervals selected. In this paper a statistical method is introduced that calculates all the results of linear regression in the sub-interval of selected depth interval removing the exceptional values of them and the mean of remained values is best result. The other advantage of this method is that we can find the best regression depth intervals in use of the result. At last the author compares the results of processes of three measurements: in-water radiometric profile measurement above-water radiance measurement and the reversion produce of SeaWiFS data at the same time and site the results show that this statistical method is available and looking Es(O+.λ) on as the validation of extrapolation of Ed(O-,λ) is incorrect.

Paper Details

Date Published: 12 May 2005
PDF: 8 pages
Proc. SPIE 5832, Optical Technologies for Atmospheric, Ocean, and Environmental Studies, (12 May 2005); doi: 10.1117/12.619687
Show Author Affiliations
Erhui Huang, State Key Lab. of Ocean Dynamic Processes and Satellite Oceanography, SOA (China)
Remote Sensing Technology and Application Ctr., SOA (China)
Shujing Li, State Key Lab. of Ocean Dynamic Processes and Satellite Oceanography, SOA (China)
Xianqiang He, State Key Lab. of Ocean Dynamic Processes and Satellite Oceanography, SOA (China)
Delu Pan, State Key Lab. of Ocean Dynamic Processes and Satellite Oceanography, SOA (China)


Published in SPIE Proceedings Vol. 5832:
Optical Technologies for Atmospheric, Ocean, and Environmental Studies
Daren Lu; Gennadii G. Matvienko, Editor(s)

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