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Chlorophyll-^{2} > 0.8) with the measured Chl-

The deterioration of the water quality of inland water bodies has been a serious ecological and social problem in China, since many lakes (both natural and artificial) and rivers are the main sources of drinking water, as well as water for agricultural use. With the increasing shortage of available water resources, the protection and maintenance of water quality have been a primary objective of watershed or water resources management. Eutrophication is a persistent water quality problem affecting the ecological health of many shallow lakes [

Phytoplankton primary production is regard as a reliable and accurate indicator for eutrophication assessment [

Chl-

Although Chl-

Numerous studies have focused on deriving Chl-^{3} in turbid estuaries [^{3} at these wavelengths [_{max}) and the reflectance at 670 nm (R_{670}), or the ratio R_{705}/R_{670} [

For all the limitations mentioned above, identification of the best indices for Chl-

In this study, Tangxun Lake was selected as the study area. Located between 30°22′N and 30°30′N and between 114°15′E and 114°35′E, in Wuhan, Central China, Tangxun Lake, as the second largest lake in Wuhan City, has a storage capacity of 32.85 million km^{3} and a catchment area of 240.38 km^{2}. Its current surface area is approximately 32.85 km^{2}, accounting for 28.7% of the total lake area in Wuhan. Tangxun Lake is a typical shallow lake with a mean water depth of 18.5 m. With the industrialization and urbanization of Wuhan, an enormous amount of untreated wastewater and sewage was discharged into the lake without treatment, resulting in an incessant increase of nutrient concentration in the lake. Consequently, water eutrophication has become a serious environmental problem, and the water quality of Tangxun Lake, as a result, can barely satisfy the ecological and living requirements and it is thus necessary to develop methods for monitoring the Chl-

Two datasets of hyperspectral reflectance data and Chl-

Hyperspectral reflectance was measured with a SVC HR-1024 spectroradiometer with a spectral resolution of less than 3.5 nm in the spectral range from 350 to 1,000 nm. The spectral resolution was resampled by the equipment’s software. In the measurement, the instrument was held manually over the deck of an anchored ship approximately one meter above the water surface. At each sampling location, three kinds of radiances were measured: radiances of water surface (_{sw}_{p}_{sky}_{v}_{v}_{sky}_{sw}_{w}_{d}^{+}) is the total incident radiance flux of water surface; _{sw}_{sky}_{p}_{p}

Surface water samples (2.5 L volume) were collected at a depth of 0.5 m below the surface immediately after the reflectance measurements. These samples were stored in a cooler with ice in the dark, and taken back to the laboratory for Chl-

We selected the spectroradiometer data with wavelengths between 380 and 900 nm for analysis according to previous research. The spectral reflectance curves of the samples are shown in

The reflectance spectra show a clear reflectance peak around 570 nm, which then decreases gradually. Another peak appears around 706 nm. The curves show less diversity when the wavelength is larger than 730 nm. According to previous studies, the reflectance peak near 570 nm may be caused by low absorption of algal pigments or the scattering of inorganic suspended materials and phytoplankton cells. The absorption valley from 670 nm to 686 nm may be caused by the maximum absorption of chlorophyll-a in the red-band. The other reflectance peak near 706 nm may be due to fluorescence of Chl-

Three types of hyperspectral indices, including single-band reflectance, first derivative of reflectance and reflectance ratio, were extracted from spectral profiles involving all bands of hyperspectral sensor. Correlation analysis was conducted to identify the most appropriate bands for those algorithms.

The correlation analysis was conducted between Chl-

It is shown in

All seven correlation coefficients between reflectance and Chl-

The first-derivative of reflectance can be calculated as [_{2})′_{2}_{2+1})_{2−1})_{2+1}_{2−1}_{2+1}_{2−1}

It is shown in

The reflectance ratio of characteristic bands is widely used to estimate Chl-_{705.2}/R_{682.1} and R_{705.2}/R_{572.4} were applied in linear modeling. The results of linear regression models with the two combinations are shown in

As shown in ^{2} of 0.0439 and 0.0037 respectively in Tangxun Lake. The fitting line will cause a huge error in Chl-_{861.1}/R_{865.7} ratio combination. Based on the correlation analysis, the optimal band combination is easy to obtain, and can be used for Chl-

According to the correlation analysis results, the R_{861.1}/R_{865.7} reflectance ratio with the maximum correlation coefficient of Chl-^{2} of the model reached 0.8605. The model based on correlation analysis was better than the one with empirical characteristic band combinations. The reflectance radio of different bands reduces the noise for Chl-

The objective of this study is to obtain the optimal model and its most suitable band combination for Chl-

The bands between 726.5 nm and 734.4 nm are selected for Chl-^{2} of the linear model is approximately 0.705. For the first-derivative algorithm, the optimal band for Chl-^{2} value of 0.863. And R_{861.1}/R_{865.7} ratio is the best band combination for the reflectance radio algorithm, whose accuracy is slightly lower than first-derivative one with a R^{2} value of 0.861. The mean relative error (MRE) is also calculated for three kinds of models. The MRE is expressed as:
_{i}_{i})

The MRE of first-derivative model is the lowest with a value of 11.2%, and the MRE of reflectance ratio model is slightly higher, with a value of 13.8%. Meanwhile, the largest error exists in the single-band model with an MRE of 26.3%. It can therefore be concluded that it is feasible to to estimate Chl-

In this study, the potential of hyperspectral data to derive Chl-

The correlation analysis has indentified the proper wavelengths or band ratios for the extraction of Chl-_{NIR}/R_{RED} radio was commonly used in previous research, and, for example, Mittenzwey shown a high coefficient of determination (R^{2}) of 0.98 between chlorophyll and the near-infrared (NIR)/red reflectance ratio [_{NIR}/R_{RED} were poor, with an R^{2} value of 0.043, which indicated the _{NIR}/R_{RED} is not suitable to estimate Chl-a concentrations in Tangxun Lake. This agrees with the conclusions of Han’s study in Branched Oak Lake [^{2} > 0.86). Derivative spectra indicate the rate of change of reflectance with wavelength, so derivative analysis allows one to correlate the shape of the reflectance pattern to Chl-a concentrations. The first-derivative algorithm can reduce pure-water effects on the water effect [^{2} and MRE of 0.863 and 11.2%, respectively. The difference of the most appropriate bands in our study means that it is of primary importance to choose optimal bands for estimating Chl-a concentrations in specific waters. The results suggest that assessment of Chl-

This research was supported and funded by Ministry of Science and Technology of China (grant 2008BAC34B06, 2008BAK50B01) and the State Key Laboratory of Resources and Environment Information System. The authors would also like to thank the two anonymous reviewers for their helpful comments and suggestions.

Study area and sampling locations.

Viewing geometry of spectra sampling.

Reflectance spectra at 10 sampling sites in Tangxun Lake.

The curve of correlation coefficients between reflectance and Chl-

The correlation coefficients between first-derivative of reflectance and Chl-

Linear models with reflectance ratios of characteristic bands.

The correlation coefficients between Chl-

Scatter plots of Chl-

Scatter plots of Chl-

Scatter plots of Chl-_{861.1}/R_{865.7}.

The correlation between spectral reflectance and Chl-

726.5 | 727.8 | 729.1 | 730.5 | 731.8 | 733.1 | 734.4 | |

−0.80652 | −0.82203 | −0.815 | −0.83498 | −0.83097 | −0.83998 | −0.82338 |

Regression models for Chl-

^{2} |
||||
---|---|---|---|---|

Single-band | 733.1 nm | Chla = −0.0227×R_{733.1} + 0.0568 |
0.705 | 26.3% |

First-derivative | 446.9nm | Chla = −0.3301R’_{446.9} + 0.023 |
0.863 | 11.2% |

Reflectance Ratio | R_{861.1}/R_{865.7} |
Chla = 0.2293 × (R_{861.1} / R_{865.7}) − 0.2146 |
0.861 | 13.8% |