Red Tide Index Research Articles

Incidence of harmful algal blooms in pristine subtropical ocean: a satellite remote sensing approach (Jeju Island)

Despite the increasing numbers of red tide events in the pristine subtropical ocean, a paucity of previous observations has limited understanding of harmful algae in the seas around the Korean Peninsula. Therefore, using six years (2012–2017) of Geostationary Ocean Color Imager (GOCI) satellite data, we characterized the red tides around Jeju Island, a volcanic island located near the paths of the Jeju Warm Current and Tsushima Warm Current, using the Normalized Red Tide Index (NRTI) method. The seawater around Jeju Island has for a long time been considered to be very clear, with relatively low suspended particulate matter concentrations and few harmful algae. Nonetheless, the satellite-based NRTI detection method used in this study detected and supported the existence of red tides in the coastal region around Jeju Island. Analysis of the red tide distribution showed that red tide first began to appear near the western coast of Jeju Island, then developed in the northern and eastern coastal regions, and finally vanished in the eastern coastal region. The monthly averages of the NRTI demonstrated a bloom event from April to May in every year. Additional fall blooms were detected in August–September, particularly in 2013 and 2016. The NRTI revealed strong interannual variations. The longest blooms occurred in 2015, and the most comprehensive and strongest event occurred in the spring of 2016. The latter three years (2015–2017) had much higher NRTI than the former three years (2012–2014). The probability of red tide occurrence at a given point during the 6-year study period revealed spatial differences. Relatively high probability of 0.3–0.5 was determined along the northern coastal region, whereas low probability of less than 0.2 was found along the southern region. Ground truth data also showed more frequent observations and higher red tide cell densities along the northern coast. Changes in NRTI in spring are positively correlated with changes in ENSO indices in winter. This study is the first to use a satellite-based approach with a vast long-term satellite database to elucidate the existence and probability of red tides near Jeju Island. We anticipate that this study will provide a useful strategy for remote monitoring of harmful algal blooms over wide regions using optical data.

Assessment of GCOM-C Satellite Imagery in Bloom Detection: A Case Study in the East China Sea

The coast of the East China Sea (ECS) is one of the regions most frequently affected by harmful algal blooms in China. Remote sensing monitoring could assist in understanding the mechanism of blooms and their associated environmental changes. Based on imagery from the Second-Generation Global Imager (SGLI) conducted by Global Change Observation Mission-Climate (GCOM-C) (Japan), the accuracy of satellite measurements was initially validated using matched pairs of satellite and ground data relating to the ECS. Additionally, using SGLI data from the coast of the ECS, we compared the applicability of three bloom extraction methods: spectral shape, red tide index, and algal bloom ratio. With an RMSE of less than 25%, satellite data at 490 nm, 565 nm, and 670 nm showed good consistency with locally measured remote sensing reflectance data. However, there was unexpected overestimation at 443 nm of SGLI data. By using a linear correction method, the RMSE at 443 nm was decreased from 27% to 17%. Based on the linear corrected SGLI data, the spectral shape at 490 nm was found to provide the most satisfactory results in separating bloom and non-bloom waters among the three bloom detection methods. In addition, the capability in harmful algae distinguished using SGLI data was discussed. Both of the Bloom Index method and the green-red Spectral Slope method were found to be applicable for phytoplankton classification using SGLI data. Overall, the SGLI data provided by GCOM-C are consistent with local data and can be used to identify bloom water bodies in the ECS, thereby providing new satellite data to support monitoring of bloom changes in the ECS.

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

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.

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

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.

Monitoring HABs in the shallow Arabian Gulf using a qualitative satellite-based index

ABSTRACTIn this study, a harmful algal bloom (HAB) index, commonly known as a red tide index (RI), was developed and tested using in situ measurements in the shallow Arabian Gulf where periodical occurrence of red tide has been reported. The index is based on a combination of ratio and difference of bands centred at 443, 531, and 547 nm. The index was applied to Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua imagery and compared with other proxies of HABs such as chlorophyll-a (chl-a) concentrations and fluorescence line height (FLH). Validation of the proposed index produced a positive correlation between the index and chlorophyll-a concentration with a determination coefficient (R2) of 0.61. Seasonality analysis of RI indicated that HABs in the Gulf region occur mainly in fall and winter. The inter-annual variations of RI showed similar patterns with the conventional chl-a product. This new index can provide insights into the dynamics of red tides and guidance for mitigation efforts, and assist in establishing an effective and timely forecasting and warning system for red tide.

Assessing change of environmental dynamics by legislation in Japan, using red tide occurrence in Ise Bay as an indicator

Tokyo Bay, Ise Bay, and the Seto Inland Sea are the total pollutant load control target areas in Japan. A significant correlation between the incidence of red tides and water quality has been observed in the Seto Inland Sea (Honjo, 1991). However, while red tides also occur in Ise Bay and Tokyo Bay, similar correlations have not been observed. Hence, it is necessary to understand what factors cause red tides to effectively manage these semi-closed systems. This study aims to investigate the relationship between the dynamics of the Red Tide Index and nitrogen regulation as well as phosphorus regulation, even in Ise Bay where, unlike Tokyo Bay, there are few observation items, by selecting a suitable objective variable. The introduction of a new technique that uses the Red Tide Index has revealed a possibility that the total pollution load control has influenced the dynamics of red tide blooms in Ise Bay.

Diurnal changes of a harmful algal bloom in the East China Sea: Observations from GOCI

Harmful algal blooms (HABs) in the East China Sea (ECS) have been reported every year in the last decade, and satellite remote sensing has often been used to study the bloom size and duration. Yet satellite remote sensing suffered from lack of reliable algorithms to detect HABs in optically complex coastal waters and from frequent cloud cover. Thus, it has not been possible to document short-term changes of HABs in synoptic scales. Here, using measurements from the Geo-stationary Ocean Color Imager (GOCI), we studied diurnal changes of a HAB of the dinoflagellate Prorocentrum donghaiense in the ECS in May 2011. The standard remote sensing reflectance (Rrs) products from the GDPS processing algorithms showed promise in delineating HABs in turbid coastal waters, yet the cloud-masking is often too tight to reveal valid cloud-free data. An alternative approach was developed to circumvent this difficulty by using the Rayleigh-corrected reflectance (Rrc) and a normalization technique. A modified red tide index (RI) was developed from the normalized Rrc data at 443, 490 and 555nm, and proven effective in delineating the P. donghaiense bloom in sediment-rich waters. The hourly RI images on 29 and 30 May 2011 (8images per day from 8:30 to 15:30) showed consistent bloom evolution through the course of a day, with physical locations driven by tides while its surface expression increased significantly from early morning to early afternoon (maximum around 14:30 local time, a 124% and 163% increase from 9:30, respectively). The maximum coverage of the HAB at 14:30 on 29 May 2011, when no cloud was observed, reached 6620km2. While the short-term changes in the surface expression could be a result of the horizontal dilution due to tides, vertical migration of the dinoflagellate from early morning to afternoon, as reported elsewhere, may be a dominant reason. The case study here demonstrates the unique value of a geostationary satellite ocean color sensor in revealing short-term dynamics of HABs.

Detection of Cochlodinium polykrikoides red tide based on two-stage filtering using MODIS data

This study proposes a red tide detection algorithm based on two-stage filtering to provide positional information of red tide for design of desalination system. Based on MODIS Red tide Index (MRI), this algorithm conducts additional two-stage filtering processes, sea surface temperature, and 667 nm wavelength filtering, and finally detects red tide by applying the local Moran's I that is a spatial statistical method. We conducted visual interpretation and quantitative accuracy assessment using error matrix and introduced the F-measure, and Jaccard and Yule coefficients as measures of detection accuracy. The algorithm effectiveness was verified by the detection of a large Cochlodinium polykrikoides red tide event that appeared in Korean coastal waters. Therefore, it is expected that this algorithm could help plant designers and operators to choose an optimal place for a desalination system.

ADEOS-II/GLIの生物光学アルゴリズム

Empirical bio-optical algorithms developed for GLI are described. These algorithms can be used to retrieve in-water properties from GLI normalized water leaving radiances in temperate Case + waters. The OC. Chl-a algorithm uses the maximum band ratio switching procedure for bands that do not saturate over the ocean. GLI is the only ocean color sensor that has ultra-violet (UV) bands and we developed an experimental red tide UV index for the early detection of dinoflagellate blooms. The red tide index uses the increased absorption of UV light by mycosporine-like amino-acids (MAAs). A special version of the Chl-a algorithm was developed for the Southern Ocean Case + waters. The standard algorithms cannot be applied to turbid near-shore waters, e.g. o# Korea and Hong Kong where bio-optical characteristics deviate drastically from Case + characteristics. Developing new and improved algorithms for Case , waters is a major challenge in bio-optical oceanography.

Environment Change due to red tide indicates and the Chapter V of the Water Pollutant Control Law in Ise Bay

In general, red tide indicates a visual and customary name for the phenomenon that microalgae in seawater proliferate abnormally, causing a sudden change in sea surface color. However, this is not sufficient to quantitatively understand red tide, and the definition of red tide is not clear. On the other hand, the Ise Bay is considered to have eutrophication and red tide is regularly observed in the Bay. Although the load of nutrient salts has been decreasing, the Bay is one of the areas where determining the relation between red tide and water quality control is difficult. In this study, the author established the criteria to define red tide (red tide index), applied a stepwise method to a multiple regression model, and determined a stable model that has Chl-a (red tide index) as its explanatory variable. Environmental influence was captured by the change in the coefficient of determination of the red tide index model, which implicitly indicated the influence of the Fifth Regulation of Total Pollutant Load Control.

SeaWiFS sensing of hazardous algal blooms and their underlying mechanisms in shelf-slope waters of the Northwest Pacific during summer

RCA-chlorophyll (red tide index chlorophyll algorithm — RCA) estimates from the SeaWiFS, sea surface height (SSH) variations/geostrophic currents from the multi-satellite altimeters, sea surface temperature (SST) from the NOAA-AVHRR, and wind speed/direction from the QuikSCAT are used in conjugation with field observation data to first describe comprehensively the occurrences of various hazardous algal blooms (HABs) and their underlying mechanisms and link to nutrient enrichment during the summer (June–September) in shelf-slope waters off the Northwest Pacific (NWP) covering China, Korea, Japan and Russia (perhaps this is the first satellite-based study in Russia). These datasets provide a coherent view of the summertime evolution of HABs and related physical processes in the above regional segments with four common dynamic regions: coastal cold/estuary water zones, upwelling zones next to the coast, repeated meanders/eddies, and frontal regimes induced by the Kuroshio and its tributaries. Summer HABs numerically dominated by dinoflagellates and diatoms (only in few cases) were initiated in these hydrodynamically active coastal regions and subsequently transported throughout their coastal and oceanic ranges by major currents and eddy systems. As a consequence, dense and colossal blooms displayed mean RCA of > 7 mg m − 3 and TBCA (total bloom covered area) of > 20 × 10 3 km 2, which limits the research vessels to observe concomitantly their spatially explicit phases together with physical oceanographic features in such large regions. Less dense and spatially disbanded blooms were characterized by mean RCA of < 3 mg m − 3 and TBCA of < 8 × 10 3 km 2. Besides those of the nutrient-abundant zones, high blooms coincided with the coastal upwelling and cyclonic eddy regimes that followed SST minimum and large negative SSH along with favorable phase of winds. By contrast, relatively low mean RCA were consistent with the fronts and anticyclonic meanders revealing moderate-high SSH fields along with variable winds blown off the NWP coast. These anticyclonic meanders, on some occasions, when nutrient-containing coastal water setoff higher chlorophyll biomass and major currents gained force in August, straddled the continental margin, entraining high chlorophyll water from the coast and from the adjacent cyclonic eddies (and upwelling) located nearby into their outer rings that formed a conveyer-belt system of transport to inject coastal blooms into the deep-sea (e.g., East Sea) region of the NWP. The above findings based on satellite data combined with field hydrographic/bloom observation data evidently illustrated richness of the response of summer HABs to the surface circulation and nutrient enrichment processes in shelf-slope waters off the NWP coast.

Detecting the red tide algal blooms from satellite ocean color observations in optically complex Northeast-Asia Coastal waters

Over the last few decades, the coastal regions throughout the world have experienced incidences of algal blooms, which are harmful or otherwise toxic because of their potential threat to humans as well as marine organisms, owing to accelerated eutrophication from human activities and certain oceanic processes. Previous studies have found that correct identification of these blooms remains a great challenge with the standard bio-optical algorithms applied to satellite ocean color data in optically complex coastal waters containing high concentrations of the interfered dissolved organic and particulate inorganic materials. Here a new method called the red tide index (RI) is presented which is capable of identifying potential areas of harmful algal blooms (HABs) from SeaWiFS ocean color measurements representing the typical Case-2 water environments off the Korean and Chinese coasts. The RI method employs the water-leaving radiances ( L w), collected from in-situ radiometric measurements of three SeaWiFS bands centered at 443 nm, 510 nm and 555 nm, to achieve derivation of indices that are then related to absorbing characteristics of harmful algae (i.e., L w at 443 nm) from which a best fit with a cubic polynomial function with correlation coefficient of R 2 = 0.91 is obtained providing indices of higher ranges for HABs and lower and slightly reduced ranges for turbid and non-bloom waters. Similar indices derived from the use of remote sensing reflectance ( R rs), normalized water-leaving radiance ( nL w) and combination of both are found rather inadequate to characterize the variability of the encountered bloom. In order to quantify the HABs in terms of chlorophyll (Chl), an empirical relationship is established between the RI and in-situ Chl in surface waters from about 0.4–71 mg m − 3 , which yields a Red tide index Chlorophyll Algorithm (RCA) based on an exponential function with correlation coefficient R 2 = 0.92. The established methods were extensively tested and compared with the performances of standard Ocean Chlorophyll 4 (OC4) algorithm and Local Chlorophyll Algorithm (LCA) using SeaWiFS images collected from typical red tide waters of Korean South Sea (KSS), East China Sea (ECS), Yellow Sea (YS) and Bohai Sea (BS) during 1999–2002. The standard spectral ratio algorithms, the OC4 and LCA, yielded large errors in Chl retrievals for coastal areas, besides providing false information about the encountered HABs in KSS, ECS, YS and BS waters. On the contrary, the RI coupled with the standard spectral ratios yielded comprehensive information about various ranges of algal blooms, while RCA Chl showing a good agreement with in-situ data led to enhanced understanding of the spatial and temporal variability of the recent HAB occurrences in high scattering and absorbing waters off the Korean and Chinese coasts.