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Estimation of Chlorophyll-a Concentration and the Trophic State of the Barra Bonita Hydroelectric Reservoir Using OLI/Landsat-8 Images

Author

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  • Fernanda Sayuri Yoshino Watanabe

    (Department of Cartography, Sao Paulo State University, Cep. 19060-900, Presidente Prudente, SP 19060-900, Brazil)

  • Enner Alcântara

    (Department of Cartography, Sao Paulo State University, Cep. 19060-900, Presidente Prudente, SP 19060-900, Brazil)

  • Thanan Walesza Pequeno Rodrigues

    (Department of Cartography, Sao Paulo State University, Cep. 19060-900, Presidente Prudente, SP 19060-900, Brazil)

  • Nilton Nobuhiro Imai

    (Department of Cartography, Sao Paulo State University, Cep. 19060-900, Presidente Prudente, SP 19060-900, Brazil)

  • Cláudio Clemente Faria Barbosa

    (Image Processing Division, National Institute for Space Research, São José dos Campos, SP 12227-010, Brazil)

  • Luiz Henrique da Silva Rotta

    (Department of Cartography, Sao Paulo State University, Cep. 19060-900, Presidente Prudente, SP 19060-900, Brazil)

Abstract

Reservoirs are artificial environments built by humans, and the impacts of these environments are not completely known. Retention time and high nutrient availability in the water increases the eutrophic level. Eutrophication is directly correlated to primary productivity by phytoplankton. These organisms have an important role in the environment. However, high concentrations of determined species can lead to public health problems. Species of cyanobacteria produce toxins that in determined concentrations can cause serious diseases in the liver and nervous system, which could lead to death. Phytoplankton has photoactive pigments that can be used to identify these toxins. Thus, remote sensing data is a viable alternative for mapping these pigments, and consequently, the trophic. Chlorophyll- a (Chl- a ) is present in all phytoplankton species. Therefore, the aim of this work was to evaluate the performance of images of the sensor Operational Land Imager (OLI) onboard the Landsat-8 satellite in determining Chl- a concentrations and estimating the trophic level in a tropical reservoir. Empirical models were fitted using data from two field surveys conducted in May and October 2014 (Austral Autumn and Austral Spring, respectively). Models were applied in a temporal series of OLI images from May 2013 to October 2014. The estimated Chl- a concentration was used to classify the trophic level from a trophic state index that adopted the concentration of this pigment-like parameter. The models of Chl- a concentration showed reasonable results, but their performance was likely impaired by the atmospheric correction. Consequently, the trophic level classification also did not obtain better results.

Suggested Citation

  • Fernanda Sayuri Yoshino Watanabe & Enner Alcântara & Thanan Walesza Pequeno Rodrigues & Nilton Nobuhiro Imai & Cláudio Clemente Faria Barbosa & Luiz Henrique da Silva Rotta, 2015. "Estimation of Chlorophyll-a Concentration and the Trophic State of the Barra Bonita Hydroelectric Reservoir Using OLI/Landsat-8 Images," IJERPH, MDPI, vol. 12(9), pages 1-27, August.
    • Handle: RePEc:gam:jijerp:v:12:y:2015:i:9:p:10391-10417:d:54778
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    References listed on IDEAS

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    1. Changchun Peng & Zhijun Xie & Xing Jin, 2024. "Using Ensemble Learning for Remote Sensing Inversion of Water Quality Parameters in Poyang Lake," Sustainability, MDPI, vol. 16(8), pages 1-19, April.
    2. Liang Zhang & Hugo A. Loáiciga & Meng Xu & Chao Du & Yun Du, 2015. "Kinetics and Mechanisms of Phosphorus Adsorption in Soils from Diverse Ecological Zones in the Source Area of a Drinking-Water Reservoir," IJERPH, MDPI, vol. 12(11), pages 1-15, November.
    3. Weidong Zhu & Fei Yang & Zhenge Qiu & Naiying He & Xiaolong Zhu & Yaqin Li & Yuelin Xu & Zhigang Lu, 2023. "Enhancing Forest Canopy Height Retrieval: Insights from Integrated GEDI and Landsat Data Analysis," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    4. Zihong Qin & Baozhen Ruan & Jian Yang & Zushuai Wei & Weiwei Song & Qiang Sun, 2022. "Long-Term Dynamics of Chlorophyll-a Concentration and Its Response to Human and Natural Factors in Lake Taihu Based on MODIS Data," Sustainability, MDPI, vol. 14(24), pages 1-15, December.
    5. Haobin Meng & Jing Zhang & Zhen Zheng, 2022. "Retrieving Inland Reservoir Water Quality Parameters Using Landsat 8-9 OLI and Sentinel-2 MSI Sensors with Empirical Multivariate Regression," IJERPH, MDPI, vol. 19(13), pages 1-26, June.

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