2018
DOI: 10.1590/0001-3765201720170125
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Abstract: In this present research, we assessed the performance of band algorithms in estimating chlorophyll-a (Chl-a) concentration based on bands of two new sensors: Operational Land Imager onboard Landsat-8 satellite (OLI/Landsat-8), and MultiSpectral Instrument onboard Sentinel-2A (MSI/Sentinel-2A). Band combinations designed for Thematic Mapper onboard Landsat-5 satellite (TM/Landsat-5) and MEdium Resolution Imaging Spectrometer onboard Envisat platform (MERIS/Envisat) were adapted for OLI/ Landsat-8 and MSI/Sentin… Show more

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Cited by 47 publications
(32 citation statements)
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References 28 publications
(24 reference statements)
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“…Analysis of the MSI/Sentinel-2 bands sensitivity to changes in water constituents allowed to determine optimal bands for assessing their concentration, as well as confirmed previous conclusions about the large potential of Sentinel-2 data for monitoring highly productive internal waters [5,[16][17][18][19][20][21][22]. Empirical models developed on the basis of 4087 in situ measurements reflect the regional characteristics of the optical characteristics in the Gorky Reservoir and can further be used for rapid estimation of Chl a and TSM concentration by radiometric measurements.…”
Section: Tsm Retrieval Modelssupporting
confidence: 66%
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“…Analysis of the MSI/Sentinel-2 bands sensitivity to changes in water constituents allowed to determine optimal bands for assessing their concentration, as well as confirmed previous conclusions about the large potential of Sentinel-2 data for monitoring highly productive internal waters [5,[16][17][18][19][20][21][22]. Empirical models developed on the basis of 4087 in situ measurements reflect the regional characteristics of the optical characteristics in the Gorky Reservoir and can further be used for rapid estimation of Chl a and TSM concentration by radiometric measurements.…”
Section: Tsm Retrieval Modelssupporting
confidence: 66%
“…Non-linear regression was also received for 3B index (Table 3, Figure 7b). These results mismatch [24,55], which showed that the 3B model with sufficient accuracy can be described by linear fit, and [18,25] showed that nonlinearity appears after 100 mg/m 3 .…”
Section: Chl a Retrieval Modelsmentioning
confidence: 76%
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“…The index is calculated from the green and near-infrared bands, which are highly sensitive to water contents. I2 is similar to the widely used Normalized Difference Chlorophyll Index (NDCI) [25], but instead of red, uses the red-edge band. I3, or Normalized Difference Turbidity Index NDTI [26,27], uses red and green reflectances for estimating the turbidity in water bodies.…”
Section: Methodsmentioning
confidence: 99%
“…I3, or Normalized Difference Turbidity Index NDTI [26,27], uses red and green reflectances for estimating the turbidity in water bodies. However, the same index has been used for chlorophyll-a estimation [25,28,29]. I4 was formed from the red and red-edge portion of the electromagnetic spectrum [29].…”
Section: Methodsmentioning
confidence: 99%