Estimation of chlorophyll-a concentration in productive turbid waters using a Hyperspectral Imager for the Coastal Ocean - The Azov Sea case study

Anatoly A. Gitelson, Bo Cai Gao, Rong Rong Li, Sergey Berdnikov, Vladislav Saprygin

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66 Scopus citations


We present here the results of chlorophyll-a (chl-a) concentration estimation using the red and near infrared (NIR) spectral bands of a Hyperspectral Imager for the Coastal Ocean (HICO) in productive turbid waters of the Azov Sea, Russia. During the data collection campaign in the summer of 2010 in Taganrog Bay and the Azov Sea, water samples were collected and concentrations of chl-a were measured analytically. The NIR-red models were tuned to optimize the spectral band selections and chl-a concentrations were retrieved from HICO data. The NIR-red three-band model with HICO-retrieved reflectances at wavelengths 684, 700, and 720nm explained more than 85% of chl-a concentration variation in the range from 19.67 to 93.14 mg m-3 and was able to estimate chl-a with root mean square error below 10 mg m -3. The results indicate the high potential of HICO data to estimate chl-a concentration in turbid productive (Case II) waters in real-time, which will be of immense value to scientists, natural resource managers, and decision makers involved in managing the inland and coastal aquatic ecosystems.

Original languageEnglish (US)
Article number024023
JournalEnvironmental Research Letters
Issue number2
StatePublished - Jan 1 2011



  • HICO
  • NIR-red algorithm
  • chlorophyll-a
  • remote sensing
  • turbid productive waters

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Public Health, Environmental and Occupational Health

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