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Estimation of chlorophyll-a concentration in productive turbid waters using a Hyperspectral Imager for the Coastal Ocean—the Azov Sea case study
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 720 nm 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.
Estimation of chlorophyll-a concentration in productive turbid waters using a Hyperspectral Imager for the Coastal Ocean—the Azov Sea case study
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 720 nm 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.
Estimation of chlorophyll-a concentration in productive turbid waters using a Hyperspectral Imager for the Coastal Ocean—the Azov Sea case study
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 (author) / Bo-Cai Gao (author) / Rong-Rong Li (author) / Sergey Berdnikov (author) / Vladislav Saprygin (author)
Environmental Research Letters ; 6 ; 024023
2011-04-01
6 pages
Article (Journal)
Electronic Resource
English
Remote chlorophyll-a retrieval in turbid, productive estuaries: Chesapeake Bay case study
| Online Contents | 2007