Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges

Shi, Kun; Zhang, Yunlin; Qin, Boqiang; Zhou, Botian

doi:10.1016/j.scib.2019.07.002

Cited by 117 publications

(63 citation statements)

References 184 publications

(434 reference statements)

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“…Several articles have evaluated bio-optical algorithms for the estimation of phycocyanin [19,[23][24][25][26][27]. The first two review articles were published in 2008 and 2013 by Ruiz-Verdu et al [23] and Ogashawara et al [19].…”

Section: Previous Reviews On Remote Sensing Of Phycocyaninmentioning

confidence: 99%

“…[19,[23][24][25][26][27]. 2 Reviewed Algorithms are cited from [5,17,18,23,[28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46] While these reviews compared performances of bio-optical algorithms based on in situ hyperspectral spectra and airborne and satellite images, two other reviews were published based on the description of algorithms and an evaluation of the challenges and future perspectives for the field [25,27]. Yan et [25] described several bio-optical algorithms for PC estimation (see Table 1) and highlighted the atmospheric correction and lack of orbital sensors as the main challenges of this research field.…”

Section: Previous Reviews On Remote Sensing Of Phycocyaninmentioning

confidence: 99%

“…The authors also suggested that more validation studies are needed for the use of OLCI for the monitoring of PC concentrations. Shi et al [27] also provided a comprehensive descriptive review of bio-optical algorithms for chl-a and PC concentration estimation (see Table 1). As well as Yan et al [25], this study also showed that OLCI is the main sensor for the monitoring of PC due its spectral band centered at 620 nm.…”

Section: Previous Reviews On Remote Sensing Of Phycocyaninmentioning

confidence: 99%

“…As well as Yan et al [25], this study also showed that OLCI is the main sensor for the monitoring of PC due its spectral band centered at 620 nm. The main challenges for this research field are the development of a universal algorithm for PC retrieval and the estimation of PC in oligotrophic waters [27].…”

Section: Previous Reviews On Remote Sensing Of Phycocyaninmentioning

confidence: 99%

“…Because of the growing relevance of the monitoring of cyanobacteria using remote sensing techniques, several articles compared bio-optical algorithms for the estimation of PC concentration [19,[23][24][25][26][27]. However, most of the previous reviews used limited numbers of bio-optical algorithms, expert-based judgments for algorithm comparison and suggested directions for future research.…”

Section: Introductionmentioning

confidence: 99%

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Determination of Phycocyanin from Space—A Bibliometric Analysis

Ogashawara

2020

Remote Sensing

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Over the past few decades, there has been an increase in the number of studies about the estimation of phycocyanin derived from remote sensing techniques. Since phycocyanin is a unique pigment of inland water cyanobacteria, the quantification of its concentration from earth observation data is important for water quality monitoring -once some species can produce toxins. Because of the growth of this field in the past decade, several reviews and studies comparing algorithms have been published. Thus, instead of focusing on algorithms comparison or description, the goal of the present study is to systematically analyze and visualize the evolution of publications. Using the Web of Science database this study analyzed the existing publications on remote sensing of phycocyanin decade-by-decade for the period 1991-2020. The bibliometric analysis showed how research topics evolved from measuring pigments to the quantification of optical properties and from laboratory experiments to measuring entire temperate and tropical aquatic systems. This study provides the status quo and development trend of the field and points out what could be the direction for future research.

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Section: Previous Reviews On Remote Sensing Of Phycocyaninmentioning

confidence: 99%

Section: Previous Reviews On Remote Sensing Of Phycocyaninmentioning

confidence: 99%

Section: Previous Reviews On Remote Sensing Of Phycocyaninmentioning

confidence: 99%

Section: Previous Reviews On Remote Sensing Of Phycocyaninmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Determination of Phycocyanin from Space—A Bibliometric Analysis

Ogashawara

2020

Remote Sensing

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Synechococcus and Other Bloom‐Forming Cyanobacteria Exhibit Unique Redox Signatures

et al. 2020

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Cyanobacteria form dense blooms that impair water quality. Although the impact of blooms on water quality largely differs depending on the species of cyanobacteria, it is challenging to distinguish cyanobacterial species with conventional sensors due to their similar physicochemical properties. Here, we conducted cyclic voltammetry to three major bloom‐forming cyanobacteria, Synechococcus sp., Microcystis aeruginosa, and Anabaena circinalis without addition of redox active compounds nor chemical modifications of the working electrode. These cyanobacteria exhibited redox peaks with distinct potentials from each other, in the range of +0.60 – +0.75 V vs SHE. Because these redox potentials hardly overlap with those of other environmental electroactive bacteria, those redox peaks may be used as indicators of the onset of a cyanobacterial bloom. Given that the photo‐responsive current correlated with the cell density of Synechococcus sp., electrochemical measurement would be a promising technique for a novel cyanobacterial quantification sensor, with in‐built ability to identify cyanobacterial species.

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Eutrophication trend analysis and forewarning model construction of water source reservoirs: Gaozhou Reservoir, China

Shi

Zhi-min

et al. 2021

Ecohydrology

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The eutrophication of water in reservoirs and lakes is worsening year after year and has become a prominent issue of environmental water protection. In order to understand the degree of eutrophication and the changing trend of important drinking water sources in the coastal areas of Western Guangdong, ensuring the safety of drinking water, this paper takes Gaozhou Reservoir as the research object. According to the long-term monitoring results of eutrophication index of reservoirs from 2012 to 2019, spatial and temporal analysis of each evaluation indicator and the comprehensive nutrient status of the reservoir was conducted using the integrated nutrient status index method. Based on the Weber-Fechner (W-F) law, an early warning model for reservoir eutrophication and grading evaluation was established. The results showed that Gaozhou Reservoir was in mesotrophic state, and the eutrophication was more serious in the high water period than in the low water period. TLI (TN) was the largest contributor to eutrophication of the reservoir, and all nutritional status indexes show mild eutrophication. Chl-a, phosphorus nutrients and organic matter had little effect on the degree of eutrophication. The fluctuation of the eutrophication status at each monitoring section of the reservoir was relatively stable. The TLI(Σ) of Liangde Dam was lower than that of the Shigu Reservoir, and the comprehensive nutritional status of the Shigu area in the decreasing order was tail > supply port > centre. According to the established early warning model, the eutrophication status in different seasons from 2012 to 2019 was evaluated. The results indicated that the comprehensive influence index value of the dry period was less than that of the flood period due to the influence of seasonal factors. In addition, the model has a good warning effect; it provides theoretical support and prevention and control methods for ecological environmental protection of reservoirs.

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Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges

Cited by 117 publications

References 184 publications

Determination of Phycocyanin from Space—A Bibliometric Analysis

Determination of Phycocyanin from Space—A Bibliometric Analysis

Synechococcus and Other Bloom‐Forming Cyanobacteria Exhibit Unique Redox Signatures

Eutrophication trend analysis and forewarning model construction of water source reservoirs: Gaozhou Reservoir, China

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