Comparison of ocean color chlorophyll algorithms for IRS-P40CM sensor using in-situ data

Chauhan, Prakash ; Mohan, M. ; Nayak, S. R. ; Navalgund, R. R. (2002) Comparison of ocean color chlorophyll algorithms for IRS-P40CM sensor using in-situ data Journal of the Indian Society of Remote Sensing, 87 (1 & 2). pp. 87-94. ISSN 0255-660X

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In-situ chlorophyll concentration data and remote sensing reflectance (Rrs) measurements collected in -six different ship campaigns in the Arabian Sea were used to evaluate the accuracy, precision, and suitability of different ocean color chlorophyll algorithms for the Arabian Sea. The bio-optical data sets represent the typical range of biooptical conditions expected in this region and are composed of 47 stations encompassing chlorophyll concentration, between 0.072 and 5.90 mg m -3, with 43 observations in case I water and 4 observations in case I1 water. Six empirical chlorophyll algorithms [i.e. Aiken-C, POLDER-C, OCTS-C, Morel-3, Oceaa Chlorophyll-2 (OC2) and Ocean Chlorophyll-4 (OC4)] were selected for analysis on the Arabian Sea data set. Numerous statistical and graphical criterions were used to evaluate the performance of these algorithms. Among these six chlorophyll algorithms two chlorophyll algorithms (i.e. OC2 and OC4) performed well in the case I waters of the Arabian Sea. The OC2 algorithm, a modified cubic polynomial function which uses ratio of Rrs490 nm and Rrs555 nm (where, Rrs is remote sensing reflectance), performed well with r2=0.85; rms =0.15. The OC4 algorithm, a four-band (443, 490,510, 555 nm), maximum band ratio formulation was found best on the basis of statistical analysis results with r2=0.85 and rms=0.14. Both OC2 and OC4 algorithms failed to estimate chloróphyll in Trichodesmium dominated waters. The OC2 algorithm was preferred over OC4 algorithm for routine processing of the OCM data to generate chlorophyll-a images, as it uses a band ratio of 490/555 nm and atmospheric correction is more accurate in 490 nm compared to 443 nm band, which is used by OC4 algorithm.

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Source:Copyright of this article belongs to Indian Society of Remote Sensing.
ID Code:89357
Deposited On:26 Apr 2012 13:11
Last Modified:19 May 2016 03:55

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