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Remote Sens. 2017, 9(6), 542; doi:10.3390/rs9060542

Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

1
School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 689-798, Korea
2
Environmental Microbial and Food Safety Laboratory, USDA-ARS, Beltsville, MD 20705, USA
3
Water Quality Assessment Research Division, National Institute of Environmental Research, Environmental Research Complex, Incheon 22689, Korea
4
School of Environmental Engineering, University of Seoul, Dongdaemun-gu, Seoul 130-743, Korea
*
Authors to whom correspondence should be addressed.
Academic Editors: Deepak R. Mishra and Prasad S. Thenkabail
Received: 10 April 2017 / Revised: 24 May 2017 / Accepted: 26 May 2017 / Published: 30 May 2017
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
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Abstract

Several semi-analytical algorithms have been developed to estimate the chlorophyll-a (Chl-a) and phycocyanin (PC) concentrations in inland waters. This study aimed at identifying the influence of algorithm parameters on the output variables and searching optimal parameter values. The optimal parameters of seven semi-analytical algorithms were applied to estimate the Chl-a and PC concentrations. The absorption coefficient measurements were coupled with pigment measurements to calibrate the algorithm parameters. For sensitivity analysis, the elementary effect test was conducted to analyze the influence of the algorithm parameters. The sensitivity analysis results showed that the parameters in the Y function and specific absorption coefficient were the most sensitive parameters. Then, the parameters were optimized via a single-objective optimization that involved one objective function being minimized and a multi-objective optimization that contained more than one objective function. The single-objective optimization led to substantial errors in absorption coefficients. In contrast, the multi-objective optimization improved the algorithm performance with respect to both the absorption coefficient estimates and pigment concentration estimates. The optimized parameters of the absorption coefficient reflected the high-particulate content in waters of the Baekje reservoir using an infrared backscattering wavelength and relatively high value of Y. Moreover, the results indicate the value of measuring the site-specific absorption if site-specific optimization of semi-analyical algorithm parameters was envisioned. View Full-Text
Keywords: chlorophyll-a; phycocoyanin; semi-analytical algorithm; sensitivity analysis; multi-objective optimization chlorophyll-a; phycocoyanin; semi-analytical algorithm; sensitivity analysis; multi-objective optimization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pyo, J.; Pachepsky, Y.; Baek, S.-S.; Kwon, Y.; Kim, M.; Lee, H.; Park, S.; Cha, Y.; Ha, R.; Nam, G.; Park, Y.; Cho, K.H. Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea. Remote Sens. 2017, 9, 542.

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