Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments, chlorophyll a and phycocyanin

被引:187
作者
Randolph, Kaylan [1 ,3 ]
Wilson, Jeff [1 ]
Tedesco, Lenore [2 ,3 ]
Li, Lin [2 ]
Pascual, D. Lani [3 ]
Soyeux, Emmanuel
机构
[1] Indiana Univ Purdue Univ, Dept Geog, Indianapolis, IN 46202 USA
[2] Indiana Univ Purdue Univ, Dept Earth Sci, Indianapolis, IN 46202 USA
[3] Indiana Univ Purdue Univ, Ctr Earth & Environm Sci, Indianapolis, IN 46202 USA
关键词
Hyperspectral; Remote sensing; Cyanobacteria; Phycocyanin; Chlorophyll a; Blue-green algae;
D O I
10.1016/j.rse.2008.06.002
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Nuisance blue-green algal blooms contribute to aesthetic degradation of water resources by means of accelerated eutrophication, taste and odor problems, and the production of toxins that can have serious adverse human health effects. Current field-based methods for detecting blooms are costly and time consuming, delaying management decisions. Methods have been developed for estimating phycocyanin concentration, the accessory pigment unique to freshwater blue-green algae, in productive inland water. By employing the known optical properties of phycocyanin, researchers have evaluated the utility of field-collected spectral response patterns for determining concentrations of phycocyanin pigments and ultimately blue-green algal abundance. The purpose of this research was to evaluate field spectroscopy as a rapid cyanobacteria bloom assessment method. In-situ field reflectance spectra were collected at 54 sampling sites on two turbid reservoirs on September 6th and 7th in Indianapolis, Indiana using ASD Fieldspec (UV/VNIR) spectroradiometers. Surface water samples were analyzed for in-vitro pigment concentrations and other physical and chemical water quality parameters. Semi-empirical algorithms by Simis et al. [Simis, S., Peters, S., Gons, H. (2005). Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water. American Society of Limnology and Oceanography 50(11): 237-245] were applied to the field spectra to predict chlorophyll a and phycocyanin absorption at 665 nm and 620 nm, respectively. For estimation of phycocyanin concentration, a specific absorption coefficient of 0.0070 m(2) mg PC-1 for phycocyanin at 620 nm, a(PC)* (620), was employed, yielding an r(2) value of 0.85 (n=48, p<0.0001), mean relative residual value of 0.51 (sigma=1.41) and root mean square error (RMSE) of 19.54 ppb. Results suggest this algorithm could be a robust model for estimating phycocyanin. Error is highest in water with phycocyanin concentrations of less than 10 ppb and where phycocyanin abundance is low relative to chlorophyll a. A strong correlation between measured phycocyanin concentrations and biovolume measurements of cyanobacteria was also observed (r=0.89), while a weaker relationship (r=0.66) resulted between chlorophyll a concentration and cyanobacterial biovolume. (C) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码:4009 / 4019
页数:11
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