Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass

Simis, Stefan; Ruiz‐Verdú, Antonio; Domínguez-Gómez, José Antonio; Peña-Martinez, R.; Peters, Steef; Gons, Herman J.

doi:10.1016/j.rse.2006.09.008

Cited by 185 publications

(164 citation statements)

References 31 publications

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“…In particular, monitoring water quality to detect turbid water and algal blooms is indispensable [2]. In this research, we focus on the waters of Japan's Lake Shinji and Lake Nakaumi (SJNU), which are well known as brackish water zones with abundant fishery and sightseeing resources such as birds and clams.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Unified Algorithms for Remote Sensing of Chlorophyll-a and Turbidity in Lake Shinji and Lake Nakaumi of Japan and the Vaal Dam Reservoir of South Africa under Eutrophic and Ultra-Turbid Conditions

Sakuno

Yajima

Yoshioka

et al. 2018

Water

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Abstract:We evaluated unified algorithms for remote sensing of chlorophyll-a (Chla) and turbidity in eutrophic and ultra-turbid waters such as Japan's Lake Shinji and Lake Nakaumi (SJNU) and the Vaal Dam Reservoir (VDR) in South Africa. To realize this objective, we used 38 remote sensing reflectance (R rs ), Chla and turbidity datasets collected in these waters between July 2016 and March 2017. As a result, we clarified the following items. As a unified Chla model, we obtained strong correlation (R 2 = 0.7, RMSE = 2 mg m −3 ) using a two-band model (2-BM) and three-band model (3-BM), with R rs (687)/R rs (672) and [R rs −1 (687) − R rs −1 (672)] × R rs (832). As a unified turbidity model, we obtained strong correlation (R 2 = 0.7, RMSE = 260 NTU) using 2-BM and 3-BM, with R rs (763)/R rs (821) and R rs (810) − [R rs (730) + R rs (770)]/2. When targeting the Sentinel-2 Multispectral Imager (MSI) frequency band, we focused on MSI Bands 4 and 5 (R rs (740) and R rs (775)) for the Chla algorithm. When optically separating SJNU and VDR data, it is effective to use the slopes of MSI Bands 3 and 4 (R rs (560) and R rs (665)) and the slopes of MSI Bands 7 and 9 (R rs (775) and R rs (865)).

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Section: Introductionmentioning

confidence: 99%

Evaluation of Unified Algorithms for Remote Sensing of Chlorophyll-a and Turbidity in Lake Shinji and Lake Nakaumi of Japan and the Vaal Dam Reservoir of South Africa under Eutrophic and Ultra-Turbid Conditions

Sakuno

Yajima

Yoshioka

et al. 2018

Water

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“…The measuring position had an azimuth angle of 130°-135° and a zenith angle of 35°-40°, which was used to decrease sun glint and shading interference [9,13]. The irradiance and radiance on the water surface were collected to evaluate and had the following ratio:…”

Section: Remote Sensing Reflectance Retrievalmentioning

confidence: 99%

“…In inland waters, several algorithms are applied to estimate the Chl-a concentration [5][6][7][8][9][10][11][12][13] and PC concentration [13][14][15]. However, these algorithms have limitations due to the variation of optical properties among water systems [16].…”

Section: Introductionmentioning

confidence: 99%

“…However, parameter optimization in the semi-analytical algorithms in inland waters relied on the algorithms performance to estimate the Chl-a and PC concentrations [5,6,13,14]. The absorption coefficient has been previously estimated [9,14] and used to compute pigment concentration without site-specific changes in the semi-analytical algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

et al. 2017

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Several semi-analytical algorithms have been developed to estimate the chlorophyll-a (Chl-a) and phycocyanin (PC) concentrations in inland waters. This study aimed at identifying the influence of algorithm parameters on the output variables and searching optimal parameter values. The optimal parameters of seven semi-analytical algorithms were applied to estimate the Chl-a and PC concentrations. The absorption coefficient measurements were coupled with pigment measurements to calibrate the algorithm parameters. For sensitivity analysis, the elementary effect test was conducted to analyze the influence of the algorithm parameters. The sensitivity analysis results showed that the parameters in the Y function and specific absorption coefficient were the most sensitive parameters. Then, the parameters were optimized via a single-objective optimization that involved one objective function being minimized and a multi-objective optimization that contained more than one objective function. The single-objective optimization led to substantial errors in absorption coefficients. In contrast, the multi-objective optimization improved the algorithm performance with respect to both the absorption coefficient estimates and pigment concentration estimates. The optimized parameters of the absorption coefficient reflected the high-particulate content in waters of the Baekje reservoir using an infrared backscattering wavelength and relatively high value of Y. Moreover, the results indicate the value of measuring the site-specific absorption if site-specific optimization of semi-analyical algorithm parameters was envisioned.

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“…The absorption of CDOM decreases exponentially with increasing wavelengths while it has negligible backscattering (Kirk, N o n -c o m m e r c i a l u s e o n l y 1994). The particulate constituents that attenuate incoming light include suspended sediments (both organic and inorganic) and phytoplankton (Morel and Prieur, 1977;Dall'Olmo and Gitelson, 2006), quantified by the main photosynthetic pigment, chl-a but also by accessory pigments as PC (Simis et al, 2007). Light scattering by suspended sediments strongly depends on the particles size, shape, and composition while absorption by mineral particulates is usually low (Wozńiak and Stramski, 2004).…”

Section: Optical Remote Sensingmentioning

confidence: 99%

Optical remote sensing of lakes: an overview on Lake Maggiore

Giardino

Bresciani²,

Stroppiana³

et al. 2013

J Limnol

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Influence of phytoplankton pigment composition on remote sensing of cyanobacterial biomass

Cited by 185 publications

References 31 publications

Evaluation of Unified Algorithms for Remote Sensing of Chlorophyll-a and Turbidity in Lake Shinji and Lake Nakaumi of Japan and the Vaal Dam Reservoir of South Africa under Eutrophic and Ultra-Turbid Conditions

Evaluation of Unified Algorithms for Remote Sensing of Chlorophyll-a and Turbidity in Lake Shinji and Lake Nakaumi of Japan and the Vaal Dam Reservoir of South Africa under Eutrophic and Ultra-Turbid Conditions

Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

Optical remote sensing of lakes: an overview on Lake Maggiore

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