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Evaluation of Hyperspectral Indices for Chlorophyll- a Concentration Estimation in Tangxun Lake (Wuhan, China)

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  • Yaohuan Huang

    (Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Dong Jiang

    (Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Dafang Zhuang

    (Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Jingying Fu

    (Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

Chlorophyll- a (Chl- a ) concentration is a major indicator of water quality which is harmful to human health. A growing number of studies have focused on the derivation of Chl- a concentration information from hyperspectral sensor data and the identification of best indices for Chl- a monitoring. The objective of this study is to assess the potential of hyperspectral indices to detect Chl- a concentrations in Tangxun Lake, which is the second largest lake in Wuhan, Central China. Hyperspectral reflectance and Chl- a concentration were measured at ten sample sites in Tangxun Lake. Three types of hyperspectral methods, including single-band reflectance, first derivative of reflectance, and reflectance ratio, were extracted from the spectral profiles of all bands of the hyperspectral sensor. The most appropriate bands for algorithms mentioned above were selected based on the correlation analysis. Evaluation results indicated that two methods, the first derivative of reflectance and reflectance ratio, were highly correlated (R 2 > 0.8) with the measured Chl- a concentrations. Thus, the spatial and temporal variations of Chl- a concentration could be conveniently monitored with these hyperspectral methods.

Suggested Citation

  • Yaohuan Huang & Dong Jiang & Dafang Zhuang & Jingying Fu, 2010. "Evaluation of Hyperspectral Indices for Chlorophyll- a Concentration Estimation in Tangxun Lake (Wuhan, China)," IJERPH, MDPI, vol. 7(6), pages 1-15, May.
  • Handle: RePEc:gam:jijerp:v:7:y:2010:i:6:p:2437-2451:d:8473
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    References listed on IDEAS

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    1. Liu, Yong & Guo, Huaicheng & Yang, Pingjian, 2010. "Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis," Ecological Modelling, Elsevier, vol. 221(4), pages 681-688.
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    Cited by:

    1. Chunmei Cheng & Yuchun Wei & Xiaopeng Sun & Yu Zhou, 2013. "Estimation of Chlorophyll-a Concentration in Turbid Lake Using Spectral Smoothing and Derivative Analysis," IJERPH, MDPI, vol. 10(7), pages 1-16, July.
    2. Zhaoyi Shang & Yue Che & Kai Yang & Yu Jiang, 2012. "Assessing Local Communities’ Willingness to Pay for River Network Protection: A Contingent Valuation Study of Shanghai, China," IJERPH, MDPI, vol. 9(11), pages 1-17, October.

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