scholarly journals Derivation of Red Tide Index and Density Using Geostationary Ocean Color Imager (GOCI) Data

2021 ◽  
Vol 13 (2) ◽  
pp. 298
Author(s):  
Min-Sun Lee ◽  
Kyung-Ae Park ◽  
Fiorenza Micheli
Keyword(s):  
Sea Water ◽  
Red Tide ◽  
Spatial Scales ◽  
Spectral Characteristics ◽  
Ocean Color ◽  
Coastal Region ◽  
Red Tides ◽  
Small Areas ◽  
Detection Algorithms ◽  
Actual Field

Red tide causes significant damage to marine resources such as aquaculture and fisheries in coastal regions. Such red tide events occur globally, across latitudes and ocean ecoregions. Satellite observations can be an effective tool for tracking and investigating red tides and have great potential for informing strategies to minimize their impacts on coastal fisheries. However, previous satellite-based red tide detection algorithms have been mostly conducted over short time scales and within relatively small areas, and have shown significant differences from actual field data, highlighting a need for new, more accurate algorithms to be developed. In this study, we present the newly developed normalized red tide index (NRTI). The NRTI uses Geostationary Ocean Color Imager (GOCI) data to detect red tides by observing in situ spectral characteristics of red tides and sea water using spectroradiometer in the coastal region of Korean Peninsula during severe red tide events. The bimodality of peaks in spectral reflectance with respect to wavelengths has become the basis for developing NRTI, by multiplying the heights of both spectral peaks. Based on the high correlation between the NRTI and the red tide density, we propose an estimation formulation to calculate the red tide density using GOCI data. The formulation and methodology of NRTI and density estimation in this study is anticipated to be applicable to other ocean color satellite data and other regions around the world, thereby increasing capacity to quantify and track red tides at large spatial scales and in real time.

scholarly journals Red tide of the Lingulodinium polyedrum (Dinophyceae) in Odessa Bay (Black Sea)

2021 ◽  
Vol 22 (4) ◽  
Author(s):  
Galyna Terenko ◽  
Alexander Krakhmalnyi
Keyword(s):  
Sea Water ◽  
Red Tide ◽  
Morphological Description ◽  
Red Tides ◽  
Toxic Dinoflagellate ◽  
Scrippsiella Trochoidea ◽  
Lingulodinium Polyedrum ◽  
Port Area ◽  
Ceratium Furca ◽  
History Of

One of the most massive red tides at the Odessa Bay was observed in September October 2020. It was caused by a toxic dinoflagellate Lingulodinium polyedrum (Stein) Dodge. The maximum abundance (56.1 x 106 cells L-1) of L. polyedrum was registered at the Odessa port area on October 6 when a water temperature and a salinity were 19.7°C and 14.3 ‰ respectively. The red tide was so huge and dense that the water glowed at night due to the bioluminescence characteristic of this species. The article briefly describes the history of the study of L. polyedrum in this area and provides a detailed morphological description with original photographs of this species sampled from bloom. We associate the appearance of the red tide with an increased temperature of sea water and air, a high content of nutrients, the presence of viable L. polyedrum cysts, and a slight decrease in salinity in the bay during the period of a mass development of the species in autumn of 2020. The red tide was accompanied by Protoperidinium steini, P. divergens, Prorocentrum cordatum, P. minimum, P. micans, Gonyaulas scrippsae, Diplopsalis lenticula, Azadinium spinosum, Dinophysis rotundata, D. acuminata, Oblea rotunda, Scrippsiella trochoidea, Ceratium furca.

scholarly journals Are Oil Spills Enhancing Outbreaks of Red Tides in the Chinese Coastal Waters from 1973-2017?

2021 ◽  
Author(s):  
xin LIU ◽  
chunchang zhang ◽  
ruiying geng ◽  
xin lv
Keyword(s):  
Oil Spill ◽  
Coastal Waters ◽  
Oil Spills ◽  
Red Tide ◽  
Contingency Management ◽  
Coastal Region ◽  
Red Tides ◽  
The Relationship ◽  
Spilled Oil ◽  
Shed Light

Abstract Between 1973–2017, evidences of red-tide outbreaks and oil spill accidents in the Chinese coastal waters were collected. Statistical analysis and multiple regression models were used to determine the relationship between the red tide and the oil spill. Major findings reveal that, (1) the frequency of red tides positively correlates to the number of oil spills and the volume of oil spilled as well; (2) The higher percentage of small spills (< 7 tonnes) are more likely to enhance the outbreaks of red tides; (3) More severe oil spill with penalty recorded implies a higher possibility to trigger the red tide afterwards. Therefore, oil spill contingency management aiming at preventing oil spills and mitigating spill effect could be of benefit to decrease the frequency of red tides as well. For example, it is suggested to carry out physical combat instead of chemical dispersants to remove the spilled oil in the shallow coastal areas for reducing the outbreak risk of red tides after the oil spill. The findings from this study shed light on the preventative management of red tides occurrence in the Chinese coastal waters and the similar coastal region elsewhere.

An Algorithm for Red Tides Species’ Identification Based on Spectral Characteristics and Wavelet Analysis

2015 ◽  
Vol 719-720 ◽  
pp. 1063-1067
Author(s):  
Juan Zhang ◽  
Bing Wang ◽  
He Meng Yang
Keyword(s):  
Wavelet Analysis ◽  
Spectral Reflectance ◽  
Wavelet Decomposition ◽  
Red Tide ◽  
Spectral Characteristics ◽  
Red Tides ◽  
Spectral Curves ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
False Recognitions

Hyperspectral remote sensing technology provides a new way to identify red tides types, but many existing methods can’t take full advantage of the spectral reflectance characteristics and often yield false recognitions. So, on the premise of perfect spectral curves library of red tides to be referred, this paper proposes an algorithm based on spectral reflectance characteristics and wavelet decomposition for red tides recognition. The algorithm identify the red tide species by applying wavelet analysis to a certain wavelength range limited by the spectral features. To compare and prove the effect of this algorithm, do simulate experiments with both the proposed method and the traditional SAM method. The results show that, compared with SAM method, the algorithm put forward in this paper can better indentify the species of red tides.

scholarly journals Red Tide Detection Method for HY−1D Coastal Zone Imager Based on U−Net Convolutional Neural Network

2021 ◽  
Vol 14 (1) ◽  
pp. 88
Author(s):  
Xin Zhao ◽  
Rongjie Liu ◽  
Yi Ma ◽  
Yanfang Xiao ◽  
Jing Ding ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Coastal Zone ◽  
Satellite Data ◽  
High Spatial Resolution ◽  
Detection Method ◽  
Red Tide ◽  
Ocean Color ◽  
Detection Methods ◽  
Red Tides ◽  
Spectral Difference

Existing red tide detection methods have mainly been developed for ocean color satellite data with low spatial resolution and high spectral resolution. Higher spatial resolution satellite images are required for red tides with fine scale and scattered distribution. However, red tide detection methods for ocean color satellite data cannot be directly applied to medium–high spatial resolution satellite data owing to the shortage of red tide responsive bands. Therefore, a new red tide detection method for medium–high spatial resolution satellite data is required. This study proposes the red tide detection U−Net (RDU−Net) model by considering the HY−1D Coastal Zone Imager (HY−1D CZI) as an example. RDU−Net employs the channel attention model to derive the inter−channel relationship of red tide information in order to reduce the influence of the marine environment on red tide detection. Moreover, the boundary and binary cross entropy (BBCE) loss function, which incorporates the boundary loss, is used to obtain clear and accurate red tide boundaries. In addition, a multi−feature dataset including the HY−1D CZI radiance and Normalized Difference Vegetation Index (NDVI) is employed to enhance the spectral difference between red tides and seawater and thus improve the accuracy of red tide detection. Experimental results show that RDU−Net can detect red tides accurately without a precedent threshold. Precision and Recall of 87.47% and 86.62%, respectively, are achieved, while the F1−score and Kappa are 0.87. Compared with the existing method, the F1−score is improved by 0.07–0.21. Furthermore, the proposed method can detect red tides accurately even under interference from clouds and fog, and it shows good performance in the case of red tide edges and scattered distribution areas. Moreover, it shows good applicability and can be successfully applied to other satellite data with high spatial resolution and large bandwidth, such as GF−1 Wide Field of View 2 (WFV2) images.

MEASURES FOR ENVIRONMENT CONSERVATION IN ENCLOSED COASTAL SEAS

2017 ◽  
Author(s):  
Keizo Negi ◽  
Keizo Negi ◽  
Takuya Ishikawa ◽  
Takuya Ishikawa ◽  
Kenichiro Iba ◽  
...  
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Water Mass ◽  
Sea Water ◽  
Red Tide ◽  
Water Environment ◽  
Quality Standard ◽  
Tokyo Bay ◽  
View Point ◽  
High Concentration

Japan experienced serious water pollution during the period of high economic growth in 1960s. It was also the period that we had such damages to human health, fishery and living conditions due to red tide as much of chemicals, organic materials and the like flowing into the seas along the growing population and industries in the coastal areas. Notable in those days was the issues of environment conservation in the enclosed coastal seas where pollutants were prone to accumulate inside due to low level of water circulation, resulting in the issues including red tide and oxygen-deficient water mass. In responding to these issues, we implemented countermeasures like effluent control with the Water Pollution Control Law and improvement/expansion of sewage facilities. In the extensive enclosed coastal seas of Tokyo Bay, Ise Bay and the Seto Inland Sea, the three areas of high concentration of population, we implemented water quality total reduction in seven terms from 1979, reducing the total quantities of pollutant load of COD, TN and TP. Sea water quality hence has been on an improvement trend as a whole along the steady reduction of pollutants from the land. We however recognize that there are differences in improvement by sea area such as red tide and oxygen-deficient water mass continue to occur in some areas. Meanwhile, it has been pointed out that bio-diversity and bio-productivity should be secured through conservation/creation of tidal flats and seaweed beds in the view point of “Bountiful Sea” To work at these challenges, through the studies depending on the circumstances of the water environment in the enclosed coastal seas, we composed “The Policy of Desirable State of 8th TPLCS” in 2015. We have also added the sediment DO into the water quality standard related to the life-environmental items in view of the preservation of aquatic creatures in the enclosed water areas. Important from now on, along the Policy, is to proceed with necessary measures to improve water quality with good considerations of differences by area in the view point of “Beautiful and bountiful Sea”.

scholarly journals Assessing Phytoplankton Bloom Phenology in Upwelling-Influenced Regions Using Ocean Color Remote Sensing

2021 ◽  
Vol 13 (4) ◽  
pp. 675
Author(s):  
Afonso Ferreira ◽  
Vanda Brotas ◽  
Carla Palma ◽  
Carlos Borges ◽  
Ana C. Brito
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Phytoplankton Bloom ◽  
Ocean Color ◽  
Coastal Region ◽  
Coastal Areas ◽  
Ocean Color Remote Sensing ◽  
Chl A ◽  
Peak Biomass ◽  
Phytoplankton Communities

Phytoplankton bloom phenology studies are fundamental for the understanding of marine ecosystems. Mismatches between fish spawning and plankton peak biomass will become more frequent with climate change, highlighting the need for thorough phenology studies in coastal areas. This study was the first to assess phytoplankton bloom phenology in the Western Iberian Coast (WIC), a complex coastal region in SW Europe, using a multisensor long-term ocean color remote sensing dataset with daily resolution. Using surface chlorophyll a (chl-a) and biogeophysical datasets, five phenoregions (i.e., areas with coherent phenology patterns) were defined. Oceanic phytoplankton communities were seen to form long, low-biomass spring blooms, mainly influenced by atmospheric phenomena and water column conditions. Blooms in northern waters are more akin to the classical spring bloom, while blooms in southern waters typically initiate in late autumn and terminate in late spring. Coastal phytoplankton are characterized by short, high-biomass, highly heterogeneous blooms, as nutrients, sea surface height, and horizontal water transport are essential in shaping phenology. Wind-driven upwelling and riverine input were major factors influencing bloom phenology in the coastal areas. This work is expected to contribute to the management of the WIC and other upwelling systems, particularly under the threat of climate change.

scholarly journals Feeding diverse prey as an excellent strategy of mixotrophic dinoflagellates for global dominance

2021 ◽  
Vol 7 (2) ◽  
pp. eabe4214
Author(s):  
Hae Jin Jeong ◽  
Hee Chang Kang ◽  
An Suk Lim ◽  
Se Hyeon Jang ◽  
Kitack Lee ◽  
...  
Keyword(s):  
Genetic Factor ◽  
Red Tide ◽  
Biogeochemical Cycles ◽  
Evolutionary Strategy ◽  
Distribution Data ◽  
Red Tides ◽  
Trade Off ◽  
Moderate Growth ◽  
Prey Diversity ◽  
Standing Question

Microalgae fuel food webs and biogeochemical cycles of key elements in the ocean. What determines microalgal dominance in the ocean is a long-standing question. Red tide distribution data (spanning 1990 to 2019) show that mixotrophic dinoflagellates, capable of photosynthesis and predation together, were responsible for ~40% of the species forming red tides globally. Counterintuitively, the species with low or moderate growth rates but diverse prey including diatoms caused red tides globally. The ability of these dinoflagellates to trade off growth for prey diversity is another genetic factor critical to formation of red tides across diverse ocean conditions. This finding has profound implications for explaining the global dominance of particular microalgae, their key eco-evolutionary strategy, and prediction of harmful red tide outbreaks.

scholarly journals High Spatial-Resolution Red Tide Detection in the Southern Coast of Korea Using U-Net from PlanetScope Imagery

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4447
Author(s):  
Jisun Shin ◽  
Young-Heon Jo ◽  
Joo-Hyung Ryu ◽  
Boo-Keun Khim ◽  
Soo Mee Kim
Keyword(s):  
Deep Learning ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Red Tide ◽  
Learning Approaches ◽  
Red Tides ◽  
Southern Coast ◽  
Color Sensors ◽  
Deep Learning Model ◽  
Bloom Water

Red tides caused by Margalefidinium polykrikoides occur continuously along the southern coast of Korea, where there are many aquaculture cages, and therefore, prompt monitoring of bloom water is required to prevent considerable damage. Satellite-based ocean-color sensors are widely used for detecting red tide blooms, but their low spatial resolution restricts coastal observations. Contrarily, terrestrial sensors with a high spatial resolution are good candidate sensors, despite the lack of spectral resolution and bands for red tide detection. In this study, we developed a U-Net deep learning model for detecting M. polykrikoides blooms along the southern coast of Korea from PlanetScope imagery with a high spatial resolution of 3 m. The U-Net model was trained with four different datasets that were constructed with randomly or non-randomly chosen patches consisting of different ratios of red tide and non-red tide pixels. The qualitative and quantitative assessments of the conventional red tide index (RTI) and four U-Net models suggest that the U-Net model, which was trained with a dataset of non-randomly chosen patches including non-red tide patches, outperformed RTI in terms of sensitivity, precision, and F-measure level, accounting for an increase of 19.84%, 44.84%, and 28.52%, respectively. The M. polykrikoides map derived from U-Net provides the most reasonable red tide patterns in all water areas. Combining high spatial resolution images and deep learning approaches represents a good solution for the monitoring of red tides over coastal regions.

scholarly journals Female reproductive biology and spawning periodicity of two species of king prawns, Penaeus longistylus Kubo and Penaeus latisulcatus Kishinouye, form Queensland's East Coast Fishery

1988 ◽  
Vol 39 (6) ◽  
pp. 729 ◽  
Author(s):  
AJ Courtney ◽  
MCL Dredge
Keyword(s):  
Egg Production ◽  
East Coast ◽  
Sea Water ◽  
Coastal Region ◽  
Ovary Development ◽  
Commercial Catch ◽  
Ovary Weight ◽  
Species Population ◽  
Spawning Periodicity ◽  
Catch Rates

In the coastal region of central Queensland female red-spot king prawns, P. longistylus, and the western or blue-leg king prawns, P. latisulcatus, had high mean ovary weights and high proportions of advanced ovary development during the winter months of July and August of 1985 and 1986. On the basis of insemination, both species began copulating at the size of 26-27 mm CL, but P. longistylus matured and spawned at a smaller size than P. latisulcatus. Abundance of P. longistylus was generally three to four times greater than that of P. latisulcatus but the latter was subject to greater variation in abundance. Low mean ovary weight and low proportions of females with advanced ovaries were associated with the maximum mean bottom sea-water temperature (28.5�C) for both species. Population fecundity indices indicated that peaks in yolk or egg production (a) displayed a similar pattern for both species, (b) varied in timing from year to year for both species and (c) were strongly influenced by abundance. Generally, sample estimates of abundance and commercial catch rates (CPUE) showed similar trends. Differences between the two may have been due to changes in targeted commercial effort in this multi-species fishery.

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