• Spatial Information Research
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• v.12 no.3
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• pp.263-274
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• 2004

The purpose of this study is to develop of red tide information system for spatial and temporal analysis of red tide including the outbreak season of red tide and biological-oceanography parameters using GIS techniques. The outbreaks of red tide were sporadic in the South Sea until 1994, but became frequent and widespread in whole coastal waters of the South Sea and East Sea since 1995. Therefore, the research fields of red tide has undergone a major changes. For monitoring of red tide, many kinds of techniques were carried out such as remote sensing, GIS and fuzzy model system. In this research, the development methods of red tide information system were suggested. For construction of the CIS based Red Tide database, spatial distribution area, species of red tide plankton and physical environment were analyzed.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.41 no.2
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• pp.140-146
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• 2005

The aim of our study understands the influence of meteorological factors relating to the formation of the red tide, and monitors the red tide by satellite remote sensing. The meteorological factors have directly influenced on red tide formation. Thus, it was possible to predict and apply to red tide formation from statistical analyses on the realtionships between red tide formation and meteorological factors, and also to realize the near real time monitoring for red tide by satellite remote sensing.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.39-45
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• 2011

There have been many studies on red tide because of increasing of damage to sea farming by a red tide blooms of harmful algae. The studies of red tide have mostly focused chemical properties and investigation of biological cause. If we can predict the occurrence of red tide, we will be able to minimize the damage of red tide. However, internal study of prediction of red tide blooms is only classification method that is still insufficient for red tide blooms forecast. In this paper, we proposed the red tide blooms prediction method using neural network and SVM.

• Korean Journal of Microbiology
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• v.29 no.6
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• pp.361-370
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• 1991

Physical and chemical environmental factors influencing on the outbreak of freshwater red tide by Peridinium bipes (dinoflagellate) in Soyang Reservoir were studied. Red tide occured in the site of inflowing of tributary streams annually, but the extent and severity of red tide varied from year to year. Several environmental factors such as water level, nutrient releasing from sediment, cyst resuspension, and concentrations of $Ca^{2+}$ and $Mg^{2+}$were studiedin relation to development, extent, and duration of red tide. In June of 1989 and 1991, the red tides of Peridinium bipes were very severe, and these red tides coincided with notable and rapid drawdown of lake water in late spring. Nutrient releasing and cyst resuspension by turbulence during drawdown were suggested as main causes of red tide. The quanity of nutrient releasing from sediment and hydrometeorological factors such as run-off and wind may determine the extent and duration of red tide.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.2 s.40
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• pp.51-57
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• 2007

Few researches related to the spatial determination of areas where red tide occurs have been performed, so accurately determining the area where red tide occurs and disappears poses difficulties. Therefore, a more objective and scientific method is necessary to analyze the occurrence and movement of red tide based on a geo-spatial information system. In this study, the coastline was extracted using a digital topographic map in order to examine areas where red tide occurs each year. An analysis of red tide occurrence areas, which were determined based on red tide data for the last several years, showed that only Yeoja bay had almost a zero case of red tide of the areas studied, whereas Dolsando in the South Sea and NamHaedo Aenggang bay areas exhibited the highest frequency of red tide occurrences. Based on these results, by using a system that determines the geo-spatial distribution status of areas repeatedly hit by red tide every year, it would be possible to predict the course of red tide and prevent consequent damages.

• Journal of Environmental Science International
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• v.18 no.10
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• pp.1155-1162
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• 2009

To investigate the influence of water area calmness on the red tide development, runoff phenomena due to antecedent precipitation of red tide development day were analyzed. There were examined the water quality variation properties at about the same time of the red tide develop. The red tide was developed when the stage and discharge nearly had not changed. It was estimated that the stability of particle behavior in the mouth of river effected on the red tide develop. Also, the concentrations of $COD_{Mn}$ were increased about 241~629% when the red tide developed.

• Smart Media Journal
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• v.7 no.2
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• pp.34-39
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• 2018

There are many studies on red tide due to the continuous increase in damage to domestic fish and shell farms by the harmful red tide. However, there is insufficient domestic research of identifying harmful red tide algae that automatically recognizes red tide images. In this paper, we propose a red tide image classification method using deep learning based open source. To solve the problem of recognition of various images of red tide algae, the proposed method is implemented by using tensorflow framework and Google image classification model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.41-48
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• 2012

Red tide is a natural phenomenon temporary blooming harmful algal with changing sea color from normal to red, which fish and shellfish die en masse. It also give a bad influence to coastal environment and sea ecosystem. The damage of sea farming by a red tide has been occurred each year which it cost much to prevent disasters of red tide blooms. Red tide damage and prevention cost of red tide disasters can be minimized by means of prediction of red tide blooms. In this paper, we proposed the red tide blooms prediction method using ensemble train. The proposed method use the bagging and boosting ensemble train methods for enhancing red tide prediction and forecast. The experimental results demonstrate that the proposed method achieves a better red tide prediction performance than other single classifiers.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.445-449
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• 2005

Various methods to detect the phytoplankton/red tide blooms in the oceanic waters have been developed and tested on satellite ocean color imagery since the last two and half decades, but accurate detection of blooms with these methods remains challenging in optically complex turbid waters, mainly because of the eventual interference of absorbing and scattering properties of dissolved organic and particulate inorganic matters with these methods. The present study introduces a new method called Red tide Index (Rl), providing indices which behave as a good measure of detecting red tide algal blooms in high scattering and absorbing waters of the Korean South Sea and Yellow Sea. The effectiveness of this method in identifying and locating red tides is compared with the standard Ocean Chlorophyll 4 (OC4) bio-optical algorithm applied to SeaWiFS ocean imagery, acquired during two bloom episodes on 27 March 2002 and 28 September 2003. The result revealed that OC4 bio-optical algorithm falsely identifies red tide blooms in areas abundance in colored dissolved organic and particulate inorganic matter constituents associated with coastal areas, estuaries and river mouths, whereas red tide index provides improved capability of detecting, predicting and monitoring of these blooms in both clear and turbid waters.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.253-260
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• 2005

The aim of this study is to analyze the temporal and spatial distribution aspects of red tide using GIS techniques. The damage caused by red tide appears various aspects according to the species, concentration and spatial distribution of red tide plankton. Therefore, in order to prevent the damage of red tide it is important to understand the distribution characteristics of red tide by each species according to time and space. In this perspective, we analyzed the beginning outbreak area, spatial occurrence frequency and spatial migration of red tide. The spatial data used by this study was constructed by digitizing the red tide quick report and coupled with various attributes such as species, concentration and water temperature for construction of red tide database. We used various spatial analysis methods such as union, intersect, tracking, buffer and spatial interpolation for analyzing temporal and spatial characteristics of red tide. From the result of these spatial analyses, we could get the spatial information on the temporal and spatial distribution characteristics of red tide at the Southern Sea.