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An Empirical Algorithm using Derivative Difference for Estimating Chlorophyll-A in Case-II Water
Author(s) -
M. Pallikonda Rajasekaran,
R. Sivakumar,
Savithri Bhat
Publication year - 2019
Publication title -
international journal of advanced remote sensing and gis
Language(s) - English
Resource type - Journals
ISSN - 2320-0243
DOI - 10.23953/cloud.ijarsg.444
Subject(s) - derivative (finance) , wavelength , chlorophyll a , algorithm , phytoplankton , second derivative , water quality , mathematics , quality (philosophy) , linear regression , chlorophyll , remote sensing , environmental science , chemistry , statistics , physics , optics , mathematical analysis , nutrient , geography , biology , ecology , financial economics , economics , biochemistry , organic chemistry , quantum mechanics
Water quality management includes measurement of quantity and quality. The abundance of phytoplankton in water body represents the physical condition and chemical constituents. As Chlorophyll-a exists in all types of phytoplankton, naturally the choice for water quality measurement is estimation of Chl-a concentration. The Chl-a concentration is estimated using various spectral reflectance algorithms such as single band regression, band ratio, three-band ratio, four-band ratio etc have been developed and is being used. Subsequently, the first order derivative ratio and second order derivative ratio methods are also used in some studies. Though such algorithms provide water quality measures, new algorithms are being introduced to improve estimation accuracy. In this paper, a new algorithm ‘Derivative Difference’ is proposed. It is based on the Chlorophyll concentration variation with shape of reflectance spectrum. The derivative data represents the slope of the reflectance data at different wavelength. The difference in derivative values at selected two different wavelengths were correlated with measured values to estimate Chl-a concentration. Obtained results were compared with the values obtained from band ratio method and derivative ratio methods. The algorithm is found to be better in some conditions.

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