A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China

Le, Chengfeng; Li, Yunmei; Zha, Yong; Sun, Deyong; Huang, Changchun; Lü, Heng

doi:10.1016/j.rse.2009.02.005

Cited by 256 publications

(163 citation statements)

References 35 publications

(44 reference statements)

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“…For example, a 3-band model (3-BM; hereinafter referred to as a C2 model) and 4-band model (hereinafter referred to as a C3 model) [20][21][22][23] have been proposed. Here, we briefly explain these models according to bio-optical theory.…”

Section: Chlorophyll-a and Turbidity Algorithmsmentioning

confidence: 99%

“…Conventional water quality remote sensing relies mainly on algorithms dealing with blue and green light, but in optically-complex inland waters, the red and near-infrared parts of the spectrum are often used [17]. For example, methods such as two-band algorithms [18,19], three-band algorithms [20,21] and four-band algorithms [22,23] have been proposed to measure chlorophyll-a (Chla). For measuring turbidity (Turb) or total suspended solids (TSS), which is an indicator of turbidity, methods such as one-band algorithms [24,25] and two-band algorithms [26,27] have been proposed.…”

Section: Introductionmentioning

confidence: 99%

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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: Chlorophyll-a and Turbidity Algorithmsmentioning

confidence: 99%

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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“…Satellite remote sensing provides rapid, synoptic, and regular information on important lake characteristics (physical and biogeochemical). Over the past two decades, advances in sensor technology and algorithm development have led to the use of remote sensing to monitor algal blooms in traditionally challenging ecosystems such as coastal seas and lakes, where variable optically conditions are present [18][19][20][21][22][23][24]. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), and the floating algae index (FAI) have been shown to provide good estimates of floating algal blooms coverage [25].…”

Section: Introductionmentioning

confidence: 99%

Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

Zhang

et al. 2015

Remote Sensing

104

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Abstract:As the fifth largest freshwater lake in China, Lake Chaohu has drawn increasing attention due to the decline in water quality and the occurrence of massive algal blooms. We applied an algae pixel-growing algorithm to MODIS Terra or Aqua data (2100 images) to characterize surface floating algae bloom dynamics from 2000 to 2013 with respect to meteorological and lake nutrient conditions. The results show an increase in surface algal bloom coverage, frequency, and duration with a trend toward earlier bloom formation. Importantly, spatial and temporal patterns in the historically less compromised eastern and middle lake areas show that water quality conditions are deteriorating. This has occurred at the same time as lake management has made a catchment scale effort to reduce impact. Our results show that nutrient concentrations were not the main driver of inter-annual bloom variations. Local meteorological conditions, in particular wind speed and temperature, played an important role in the dynamics of floating algal bloom. This highlights the important challenges for lake management.

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“…Reflectance in the red region (600-700 nm) had two minima around 620 nm and 675 nm, associated to phycocyanobilin and chlorophyll-a absorption [94,95]. A distinct peak around 700 nm shifted from 690 nm at low chlorophyll-a concentrations to 715 nm at high chlorophyll-a concentrations, which resulted from both high backscattering and minimum absorption by all optically active constituents, including pure water [96]. For low chlorophyll-a and high suspended sediments, this peak was reduced.…”

Section: Spectral Features Of Lake Water Cyanobacterial Scums and Amentioning

confidence: 99%

A MODIS-Based Novel Method to Distinguish Surface Cyanobacterial Scums and Aquatic Macrophytes in Lake Taihu

Liang

Zhang

et al. 2017

Remote Sensing

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Satellite remote sensing can be an effective alternative for mapping cyanobacterial scums and aquatic macrophyte distribution over large areas compared with traditional ship's site-specific samplings. However, similar optical spectra characteristics between aquatic macrophytes and cyanobacterial scums in red and near infrared (NIR) wavebands create a barrier to their discrimination when they co-occur. We developed a new cyanobacteria and macrophytes index (CMI) based on a blue, a green, and a shortwave infrared band to separate waters with cyanobacterial scums from those dominated by aquatic macrophytes, and a turbid water index (TWI) to avoid interference from high turbid waters typical of shallow lakes. Combining CMI, TWI, and the floating algae index (FAI), we used a novel classification approach to discriminate lake water, cyanobacteria blooms, submerged macrophytes, and emergent/floating macrophytes using MODIS imagery in the large shallow and eutrophic Lake Taihu (China). Thresholds for CMI, TWI, and FAI were determined by statistical analysis for a 2010-2016 MODIS Aqua time series. We validated the accuracy of our approach by in situ reflectance spectra, field investigations and high spatial resolution HJ-CCD data. The overall classification accuracy was 86% in total, and the user's accuracy was 88%, 79%, 85%, and 93% for submerged macrophytes, emergent/floating macrophytes, cyanobacterial scums and lake water, respectively. The estimated aquatic macrophyte distributions gave consistent results with that based on HJ-CCD data. This new approach allows for the coincident determination of the distributions of cyanobacteria blooms and aquatic macrophytes in eutrophic shallow lakes. We also discuss the utility of the approach with respect to masking clouds, black waters, and atmospheric effects, and its mixed-pixel effects.

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A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China

Cited by 256 publications

References 35 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

Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

A MODIS-Based Novel Method to Distinguish Surface Cyanobacterial Scums and Aquatic Macrophytes in Lake Taihu

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