a semianalytical model using modis data to estimate cell density of red tide algae (aureococcus anophagefferens)

a semianalytical model using modis data to estimate cell density of red tide algae (aureococcus anophagefferens)

;Lingling Jiang;Lin Wang;Xinyu Zhang;Yanlong Chen;Deqi Xiong
The Journal of biological chemistry 2016 Vol. 2016 pp. -
203
jiang2016advancesa1

Abstract

A multiband and a single-band semianalytical model were developed to predict algae cell density distribution. The models were based on cell density (N) dependent parameterizations of the spectral backscattering coefficients, bb(λ), obtained from in situ measurements. There was a strong relationship between bb(λ) and N, with a minimum regression coefficient of 0.97 at 488 nm and a maximum value of 0.98 at other bands. The cell density calculated by the multiband inversion model was similar to the field measurements of the coastal waters (the average relative error was only 8.9%), but it could not accurately discern the red tide from mixed pixels, and this led to overestimation of the area affected by the red tide. While the single-band inversion model is less precise than the former model in the high chlorophyll water, it could eliminate the impact of the suspended sediments and make more accurate estimates of the red tide area. We concluded that the two models both have advantages and disadvantages; these methods lay the foundation for developing a remote sensing forecasting system for red tides.

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ID: 157460
Ref Key: jiang2016advancesa1
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0x95644003c57E6F55A65596E3D9Eac6813e3566dA
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157460
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10.1155/2016/1780986
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Scimatic Chain (ID: 481)
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