Satellite detection of harmful algal bloom occurrences in Korean waters

Harmful Algae 5 (2006) 213–231 www.elsevier.com/locate/hal

Satellite detection of harmful algal bloom occurrences in Korean waters Yu-Hwan Ahn a,*, Palanisamy Shanmugam a, Joo-Hyung Ryu a, Jong-Chul Jeong b a

Satellite Ocean Research Laboratory, Korea Ocean Research and Development Institute, Ansan P.O. Box 29, Seoul 425-600, Republic of Korea b Department of Geoinformatics Engineering, Namseoul University, 21 Maeju-ri, Choongnam 330-800, Republic of Korea

Received 1 February 2005; received in revised form 18 June 2005; accepted 21 July 2005

Abstract Cochlodinium polykrikoides ( p) is a planktonic dinoflagellate known to produce red tides responsible for massive fish kills and thereby serious economic loss in Korean coastal waters, particularly during summer and fall seasons. The present study involved analyzing chlorophyll-a (Chl-a) from SeaWiFS ocean color imagery collected over the period 1998–2002 to understand the spatial and temporal aspects of C. polykrikoides blooms that occurred in the enclosed and semi-enclosed bays of the Korean Southeast Sea. NOAA-AVHRR data were used to derive Sea Surface Temperature (SST) to elucidate physical factors affecting the spatial distribution and abundance of C. polykrikoides blooms. The time series of SeaWiFS-derived Chl-a gave an impression that recent red tide events with higher concentrations appeared to span more than 8 weeks during summer and fall seasons and were widespread in most of the Korean Southeast Sea coastal bays and neighboring oceanic waters. Coupled eutrophication and certain oceanic processes were thought to give rise to the formation of massive C. polykrikoides blooms with cell abundances ranging from 1000 to 30,000 cells ml
1, causing heavy mortalities of aquaculture fish and other marine organisms in these areas. Our analysis indicated that Chl-a estimates from SeaWiFS ocean color imagery appeared to be useful in demarcating the locality, spatial extent and distribution of these blooms, but unique identification of C. polykrikoides from non-bloom and sediment dominated waters remains unsuccessful with this data alone. Thus, the classical spectral enhancement and classification techniques such as Forward Principal Component Analysis (FPCA) and Minimum Spectral Distance (MSD) to uniquely identify and better understand C. polykrikoides blooms characteristics from other optical water types were attempted on both low spatial resolution SeaWiFS ocean color imagery and high spatial resolution Landsat-7 ETM+ imagery. Application of these techniques could capture intricate and striking patterns of C. polykrikoides blooms from surrounding non-bloom and sediment dominated waters, providing improved capability of detecting, predicting and monitoring C. polykrikoides bloom in such optically complex waters. The result obtained from MSD classification showed that retrieval of C. polykrikoides bloom from the mixed phase of this bloom with turbid waters was not feasible with the SeaWiFS ocean color imagery, but feasible with

* Corresponding author. Tel.: +82 31 400 6129; fax: +82 31 400 6139. E-mail addresses: [email protected], [email protected] (Y.-H. Ahn). 1568-9883/$ – see front matter # 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.hal.2005.07.007

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Landsat-7 ETM+ imagery that provided more accurate and comparable spatial C. polykrikoides patterns consistent with in situ observations. The dense phase of the bloom estimated from these imageries occupied an area of more than 25 km2 around the coastal bays and the mixed phase extended over several hundreds kilometers towards the Southeast Sea offshore due to exchange of water masses caused by coastal and oceanic processes. Sea surface temperature analyzed from AVHRR infrared data captured the northeastward flow of Tsushima Warm Current (TWC) waters that provided favorable environmental conditions for the rapid growth and subsequent southward initiation of C. polykrikoides blooms in hydrodynamically active regions in the Korean Southeast Sea offshore. # 2005 Elsevier B.V. All rights reserved. Keywords: C. polykrikoides blooms; Ocean color; SeaWiFS; Landsat-7 ETM+; FPCA; MSD; Korea

1. Introduction Phytoplankton blooms appear to be an increasingly common phenomena on a worldwide scale and are sometimes considered to be harmful either because of their potential threat to human health through the consumption of contaminated seafood, as in the case of many toxic phytoplankton blooms or through the changes in species abundance and distributions (often including species of commercial value), as in the case of recent brown or red tide blooms (Buskey et al., 1996; Franks, 1997; Tester and Steidinger, 1997; Cho et al., 2000; Matsuyama et al., 2001; Sierra-Beltran et al., 2004; Cheng et al., 2005). The bloom formation occurs, when the rate of phytoplankton growth exceeds the rate of cell dispersion, due to enhanced anthropogenic nitrification, which is one of the most pervasive changes altering coastal environments worldwide (Shumway, 1990; Burkholder, 1998) or some times steepening of nutricline by intervenes of physical phenomena (Falkowski et al., 1991; Olaizola et al., 1993). The semi-enclosed nature of Korean Southeast Sea coastal bays often reaches extremity in eutrophic state by receiving terrestrial wastewater and pollutants related to heavy rainfall and surface runoff, resulting in occurrence and outbreaks of series of harmful Cochlodinium polykrikoides ( p) blooms, which appear to have significantly increased in frequency, intensity and geographic distribution and caused massive mortalities of aquaculture fish off the southern and eastern coasts of Korea (Kim et al., 1999). Among several dinoflagellate species, C. polykrikoides has been identified as causative organism of red tides responsible for massive fish kills in warm temperate and tropical waters (Steidinger and Tangen, 1997). Its monospecific nature with a unique set of conditions results in high rates of respiration that can cause

dissolved oxygen concentrations to fall to a level low enough to endanger marine life (Buskey et al., 1996). Besides coastal eutrophication, other changing environmental conditions such as warming, resuspension of spores and advection are also principal factors for the increased occurrence of monospecific C. polykrikoides blooms in Korean coastal waters (Kim et al., 1990). Although there are historical records of this red tide forming algae since the sixth century, the first scientific report on red tides was published by Park and Kim (1967), and later, many red tide events have been documented along with an extensive red tide phytoplankton bloom in summer 1995, which caused heavy mortalities of aquaculture fish and amounted to a loss of US$ 95.5 million (Kim et al., 1997). A similar event of C. polykrikoides in the southern China Sea during March and April 1998 has been reported to cause tremendous damage to the coastal aquaculture industry, wiping out 1500 tonnes of farmed fish, which was equivalent to half of the entire Hong Kong aquacultural production of 1997 (Anderson, 1998; Tang et al., 2003). Perhaps, this species was first reported from the Caribbean Sea along the southern coast of Puerto Rico (Margalef, 1961) and northern Atlantic waters along the American east coast, Barnegat bay, New Jersey (Silva, 1967). Although C. polykrikoides is a known red tide species associated with extensive fish kills and great economic loss in Korean and Japanese coastal waters (Kim et al., 1999; Yuki and Yoshimatsu, 1989; Fukuyo et al., 1990), the mechanism of toxicity and toxin production associated with extensive aquaculture fish and mollusk damage have yet to be elucidated (Taylor et al., 1995). However, secretion of some ichthyologic substances by C. polykrikoides species has been reported as a possible cause for fish kills (Onoue et al., 1985; Hallegraeff, 1992).

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It is very important to mitigate the impacts of such harmful algal blooms and therefore there is a need to monitor the blooms and to forecast their development and movement (Stumpf, 2001). Because of the high temporal and spatial heterogeneity of coastal oceanic ecosystem and processes as well as the expense of research vessels, monitoring of the development and movement of these blooms with traditional field sampling at discrete locations remains critical. Thus, the only effective way of monitoring such blooms on a regular basis is through remote sensing. Utilization of remote sensing technology because of its synoptic and repeat coverage has been explored for detecting harmful algal blooms, delineating their spatial extent and addressing their impacts as well as describing the associated hydrographic conditions (Haddad, 1982; Cullen et al., 1997; Tester and Stumpf, 1998; Schofield et al., 1999). Steidinger and Haddad (1981) were among the first to demonstrate the potential of satellite ocean color sensor with Coastal Zone Color Scanner (CZCS) for the detection of a major Karenia brevis bloom in the western Florida waters. With the availability of daily imagery from the current SeaWiFS operational ocean color sensor, routine monitoring has been initiated by Stumpf (2001), who indicates that the use of chlorophyll data might provide a means for the detection of algal blooms in coastal waters. Similarly, Chang et al. (2001) exploited the usefulness of SeaWiFS ocean color imagery for detecting and monitoring G. catenatum bloom in New Zealand waters. On the other hand, satellite-derived sea surface temperature using Advanced Very High Resolution Radiometer (AVHRR) data, which provides real-time capability with two thermal infrared channels, has been widely used for the derivation of circulation patterns, structure of oceanic fronts, behavior of eddies/meanders and the location of upwelling zones and associated chemical and biological features (Pearce and Pattiaratchi, 1997; Cipollini et al., 1998; Chang et al., 2002; Tang et al., 2003). During several research cruises conducted in the Southeast Sea coastal waters of Korea during August/ September 1998–2002, we observed elevated chlorophyll concentrations as the result of massive C. polykrikoides blooms triggered by enhanced levels of nutrients, resulting from heavy rainfall and surface runoff as well certain oceanic processes. In this study,

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we first examine chlorophyll-a (Chl-a) concentrations analyzed from SeaWiFS ocean color image data of August/September of the period 1998–2002 in relation to identifying potential areas of C. polykrikoides bloom occurrences in these waters. We then attempt to implement certain image enhancement/classification techniques such as Forward Principal Component Analysis (FPCA) and Minimum Spectra Distance (MSD) classification on SeaWiFS image data to distinguish C. polykrikoides blooms from non-bloom and sediment dominated waters. As a part of this study, a potential use of high resolution Landsat-ETM+ image data to identify these blooms is also explored with these techniques. Finally, the retrieved bloom patterns are corroborated with the in situ observations made as a part of this study and by National Fisheries Research and Development Institute (NFRDI).

2. Materials and methods 2.1. Study area and cruise measurements The study area includes enclosed and semienclosed bays of the Korean Southeast Sea, encompassing complex interactions between physical, chemical, biological and geological processes in the shallow waters with depth less than 60 m, connecting to the East China Sea (ECS) in the southwest and East Sea (ES) in the northeast (Fig. 1). The Tsushima Warm Current (TWC) is known to be a major oceanic current feature of this region transporting nutrient-abundant Kuroshio water into the East Sea through the Tsushima Strait. It splits into two distinct branches, a northward flow of the East Korean Warm Current (EKWC) along the east Korean coast and an eastward flow of the Offshore Branch (OB) along the Japanese coast (Chang et al., 2002). This warm current appears to not only provide favorable conditions for the rapid growth of C. polykrikoides but also controls the spatial distribution of this bloom in the offshore waters. The C. polykrikoides blooms since 1981 appear to have occurred all along these coasts, including Chonsu and Mokpo in the east and Yoja, Kamak, Chinju, Kosong and Jin-hae in the south, and Onsan, Ulsan and Yongil in the east, which seriously undergo eutrophication, therefore, dinoflagellate C. polykrikoides blooms spread frequently every year. Fig. 1 shows important

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Fig. 1. Study area map shows potential areas of harmful C. polykrikoides bloom occurrences (color shaded circles) along the Korean southern and eastern coasts. The arrow mark indicates areas of in situ measurements carried out over the Jin-hae bay and surrounding waters during August/September of the period 1998–2003. In addition, regional surface current patterns observed from the satellite-tracked drifter trajectories in the Korean and neighboring waters (Lie et al., 1998) are illustrated showing Tsushima Warm Current (TWC) and its branches the East Korean Warm Current and Offshore Branch.

locations (color shaded circles) of C. polykrikoides bloom occurrences with high frequency, intensity and spatial distribution between summer and fall seasons, with a peak in August and September. Fig. 2a and b show red tide waters dominated by C. polykrikoides bloom in August 1999. The R/V Olympic cruises were conducted over the Jin-hae bay and neighboring waters coinciding with the occurrences of C. polykrikoides blooms during August/September of the period 1998–2003 (see Fig. 1). The ship surveys consisted of over 200 stations inside and outside the blooms. Seawater samples collected simultaneously with the radiometric measurements were analyzed for Chl-a concentrations using Perkin-Elmer Lambda 19 dual-beam spectrophotometer. The chlorophyll concentrations varied from 3 to 65 mg m
3 around the Jin-hae bay (Fig. 2c and d), except for a few locations close to the coast where it reached 207 mg m
3 in August 1999 (not

shown here). Fig. 2e shows absorption spectra of phytoplankton aph(l) measured in the red tide waters around the Jin-hae bay, which exhibit two dominant absorption peaks around 444 and 670 nm and the magnitude of these peaks increases with the increase in Chl-a concentration. On the other hand, remote sensing reflectance Rrs(l) spectra corresponding to chlorophyll concentrations 18–34 mg m
3 show absorption maxima at 445 nm and reflectance maxima at 567 nm and sun-induced chlorophyll fluorescence peak maxima at 688 nm (Fig. 2f). When Chl-a concentration increases, the magnitude of the fluorescence peak also increases with a notable decrease towards the blue part of the spectrum. Note that the position of the peak remains constant, offering a way to estimate chlorophyll-a concentrations and detect these blooms using the relationship between this signal and Chl-a concentrations (Ahn and Shanmugam, submitted for publication).

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Fig. 2. (a and b) Red tide waters dominated by C. polykrikoides species in the Jin-hae bay during August 1998. C. polykrikoides is found in single cells (ellipsoidal shape) and chain form. (c and d) Surface Chl-a concentration measured in August 1998 and 1999. (e) Absorption spectra aph(l) determined in the red tide waters of the Jin-hae bay exhibiting two absorption features around 444 and 670 nm. (f) Example of remote sensing reflectance Rrs(l) spectra, corresponding to chlorophyll concentrations 18–34 mg m
3, showing absorption maxima at 445 nm and reflectance maxima at 567 nm and chlorophyll fluorescence maxima around 688 nm.

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2.2. Satellite imagery and processing Level 1A SeaWiFS products were collected from our KORDI satellite data receiving station during August/September of the period 1998–2002. These data were coincident with the rapid growth and outbreaks of C. polykrikoides blooms in the Jin-hae bay and neighboring waters. The ocean color radiances were atmospherically corrected and processed to level 2 using NASA SeaDAS version 4.4 (Tomlinson et al., 2004), which has an updated atmospheric correction algorithm that compensates for near-infrared water-leaving radiance and for absorbing aerosols (Stumpf et al., 2003). The surface Chl-a concentrations were then derived by using NASA OC4v4 bio-optical algorithm within SeaDAS software (Yoder et al., 2002). The SeaWiFS-derived Chl-a was nearly consistent with the in situ Chl-a data collected outside the coastal bays. Similarly, NOAAAVHRR imageries were geo-referenced to a common grid and projection system at a spatial resolution of 1.1 km and the land pixels were subject to masking to a single value. Sea surface temperature was then computed by combining the radiance temperatures derived from the two individual thermal bands to account for the varying amounts of water vapor in the atmosphere (Barton, 1995). This was accomplished with the split window Multi Channel Sea Surface Temperature (MCSST) dual channel algorithm (available with TerraScan software) because it was found to be more efficient for the accurate SST computation, with the root mean square differences of about 0.6 8C (Li et al., 2001). In order to map accurately the initiation and movements of C. polykrikoides blooms, SeaWiFS and Landsat-7 ETM+ image data were processed separately with the classical spectral enhancement and classification techniques such as Forward Principal Component Analysis and Minimum Spectral Distance (MSD) classifier. These techniques are, in principle, the most widely used techniques for extracting land cover information on the surface from remotely sensed data (Smara et al., 1998; Oetter et al., 2000), aquaculture form information from Landsat-5 TM data in the Korean coastal waters (Shanmugam et al., 2004) and also detecting algal blooms from SeaWiFS image data in the North Sea (Pasterkamp et al., 2002). The essence of FPCA is that it uses a linear

transformation of multi-band data to translate and rotate data set from the actual measurement space, such as radiance in spectral bands, to a new measurement space that maximizes the variance of the original data set. The method considers all the available measured initial differences at once and provides, in prioritized order, sets of coefficients to rotate the input bands to new dimensions of maximum variation. In contrast, the MSD classifier is a wellknown mathematical decision rule used for hard classification of remotely sensed image data. It operates by calculating the spectral distance between the measurement vector for the pixel to be classified and the mean vector for each signature (Jensen, 1995; Schowengerdt, 1997). Before application of these methods to SeaWiFS and Landsat-7 ETM+ image data, two steps were followed: (1) both SeaWiFS and Landsat-7 ETM+ image data were georeferenced to a standard datum and projection and georeferencing accuracy was less than 0.5 pixel, and (2) pixel digital counts were converted to radiance at the top of the atmosphere (TOA) using SeaWiFS calibration coefficients (Hooker et al., 1994) and Landsat-7 ETM+ calibration coefficients (http://ltpwww.gsfc.nasa.gov/IAS/handbook/handbook_toc.html), respectively. It was followed by atmospheric correction of these images with the Spectral Shape Matching Method (SSMM) developed by Ahn and Shanmugam (2004). In order to produce a single map of likeliest class, the MSD required a number of data points (also referred to as training samples) for each class. Therefore, a training data set was constructed from the image consisting of a group of prototypical data points that represent the data characteristics of each class, spanning the observed variability in feature values while maintaining class separability in feature space. These data points from SeaWiFS image consisted of all eight bands and Landsat-7 ETM+ image of four bands (three visible and one near infrared red bands). In order to evaluate the signature separability between the selected training data points, two statistical measures of distance were reported, namely Transformed Divergence (TD) and Jeffries– Matusita (JM) (Swain and Davis, 1978). These values have lower and upper bounds, i.e., 0 and 2000 for TD and 0 and 1414 for JM distance. Here we considered these values ranging from 0 and 2. If the calculated

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distance is equal to the upper bound then the signatures can be said to be totally separable in the bands being analyzed. A calculated distance of zero means that the signatures are inseparable (Swain and Davis, 1978). 2.3. Harmful algal bloom (red tide) events in Korean coastal waters Since 1970, the geographical distribution of red tide algal blooms was limited to the enclosed bays such as the Jin-hae and Kosong bays, but they turned out to be widespread to Kangnung waters in the East Sea, Inchon and Mokpo bordering the Yellow Sea and Yoja bay in the western part of the South Sea (Kim et al., 1990). A series of red tide algal bloom outbreaks was recorded in Korean coastal waters as a part of red tide monitoring program implemented by National Fisheries Research and Development Institute (NFRDI) under the support of Ministry of Maritime Affairs and Fisheries (MOMAF) (Fig. 3). The annual total number of red tide outbreaks reveals that 8 events occurred in 1981, encompassing 3 harmful dionoflagellate C. polykrikoides blooms with cell concentrations 1500 cells ml
1, and 21 in 1982, and followed by 28 harmful events (with cell concentrations over 27,000 cells ml
1) out of 65 in 1995, the year of C. polykrikoides blooms. Recently, the C. polykrikoides blooms have affected most of coastal areas, with some cases caused by more than one toxic algal species such as Prorocentrum micans, Gymnodinium mikimotoi, Gymnodinium sanguineum, Prorocentrum minimum and Heterosigma akashiwo. The toxins of these species have been reported to cause extensive

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mortality in fish and invertebrate populations (Buskey et al., 1996; Kim et al., 1994). Table 1 characterizes red tide blooms into four stages based on species toxicity, bloom density, area and duration. It gives an impression that recent red tide events with higher density appear to have persisted for more than 8 weeks and are widespread in most of the enclosed bays and neighboring ocean waters.

3. Results 3.1. Distribution of chlorophyll during August/ September The variability of SeaWiFS-derived Chl-a and AVHRR-derived SST throughout the Jin-hae bay and neighboring waters is displayed in Fig. 4a–f, where elevated Chl-a concentrations are observed with striking patterns at several places around coastal and offshore waters of the Southeast Sea during August/September of the period 1998–2000. With the exception of river mouths and estuaries where artifact occurs due to presence of other water constituents, the observed patterns in other areas may be caused by C. polykrikoides bloom, which tends to spread eastwardly and dominate euphotic waters off the Ulsan coast in August 1998 (see attached figure on the top corner of Fig. 4a). SeaWiFS-derived Chl-a concentration during this period appears to have varied from 3 to 54 mg m
3 inside the Jin-hae bay and 0.6–14 mg m
3 outside the bay. The accumulation of C. polykrikoides within the euphotic layer off the Ulsan coast is thought to result mainly from vertical mixing and enhanced

Fig. 3. Number of observations of harmful algal bloom outbreaks off the Korean coast since 1980. Note that the frequency of the flagellates bloom outbreaks appears to have increased over time to that of diatoms bloom outbreaks (Kim, 1998).

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Table 1 Characterization of red tide algal blooms in Korean coastal waters since 1980 Terms

Before 1980

1981–1988

1989–1992

1993–1997

Species toxicity Affected area Bloom density (cells/ml) The longest duration

Harmless Partial area 1000 1 week

Harmless/harmful Partial/wide area 1000–5000 1–2 weeks

Harmful Widespread/South Sea 2000–10000 3 weeks (81)

Harmful Widespread overall coast 3000–30000 8 weeks (1995)

levels of essential nutrients pumped upward from the bottom layer, which subsequently leads to the formation of quick eutrophic situations off the Ulsan coast. A time series of SeaWiFS-derived Chl-a suggests that the bloom event lasted several weeks (2 months) inside the Jin-hae bay while spanning 1–2 weeks (a short-term variability) in the nutrient-rich upwelled waters. The upwelled waters closely linked

with EKWC (Byun, 1989) are characteristic with temperature typical of 2–10 8C surrounded by warm current waters of 7–23 8C and renowned for their high fisheries production in these areas. Blooms of high intensity were previously reported in such coastal upwelling areas at the mid and high latitudes (Glover and Brewer, 1988; Morel and Berthon, 1989). Though nutrient-rich upwelled waters were characterized by

Fig. 4. (a–f) Spatial and temporal aspects of surface chlorophyll concentrations analyzed from the SeaWiFS ocean color imagery showing recurrent patterns of C. polykrikoides blooms (a–d) caused by the intervenes of several physical processes, which are manifest in the sea surface temperature images from AVHRR infrared data (e and f). (g) In situ data show the spatial distribution of C. polykrikoides bloom in the southeastern coastal areas during August 1998–2000.

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the surface salinity and potential temperature obtained from CTD sensors, there was no data available for corroborating the accumulation of C. polykrikoides species off the Ulsan coast, because most of our in situ data were confined to the Jin-hae bay and its surrounding waters during August. However, SeaWiFS-derived Chl-a was consistent with in situ data between Kosong and western coast of Geoje island (see Fig. 4g (top)). In contrast, the SeaWiFS-derived Chl-a on 25 September 1999 demonstrates the southward extension of C. polykrikoides blooms, favored by the flow of TWC waters along the Tsushima Strait in the South Sea offshore (Fig. 4a and e). The Chl-a elevation during the southward penetration of this bloom is due to the fact that the growth rate of C. polykrikoides is maximum 0.41 day
1 at 25 8C and salinity 34 (Kim et al., 2004), who support the hypothesis that C. polykrikoides species blooms extensively with a peak when water temperature increases from 22 to 25 8C due to northeastward intrusion of TWC along the Tsushima Strait. This warm current not only provides favorable environmental conditions for this bloom, but also derives oceanic nutrients from the Kuroshio, conveying for the seed of the offshore bloom. The NFRDI data indicate that the cell abundance in the coastal areas between Geoje island and Kosong ranged from 500 to 26,000 cells ml
1, these levels are enough to produce stress and weakness in aquaculture fish and increased susceptibility to other infections. For the bloom, SeaWiFS-derived Chl-a concentration ranged from 3 to 56 mg m
3 inside the Jin-hae bay and 2– 23 mg m
3 outside the bay, closely resembling in situ Chl-a at several stations except some locations close to the coast where it reached very high levels (comparison made for August 1999 images because of having in situ match-up). According to the CTD survey results, the southward extension of C. polykrikoides bloom was associated with low saline and cold water (u < 14 and S < 34.3) around the Jin-hae bay, with pronounced hydrographic variability at both surface and subsurface which was indicative of the thermohaline water flow along the Tsushima Strait in the South Sea offshore. It is conspicuous in AVHRR-derived SST image (Fig. 4e), which elucidates temperature variability between TWC and surrounding waters. A close inspection on SeaWiFS-derived Chl-a on 27 September 1999 reveals that, in a matter of 2 days, the

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southward extension pattern of C. polykrikoides bloom transformed eastwardly by the intensification of the northward intrusion of TWC (see Fig. 4e where TWC appears to flow along the northern periphery of the island in the South Sea offshore), resulting in a mushroom-like structure in the SeaWiFS-derived Chla with 1.5–17 mg m
3 (Fig. 4b). The early stage of this bloom captured from SeaWiFS-derived Chl-a compared well with in situ data from Suh et al. (2004) (Fig. 4g (middle)). On 27 September 1999, the appearance of C. polykrikoides bloom can also be evident around Pohang coastal waters (Fig. 4b). This bloom spanning few weeks was apparently triggered by anthropogenic nutrients driven by the Yongil river, while a massive phytoplankton bloom observed in waters north off Pohang coast appears to be associated with the eddylike feature indicated by a circle in Fig. 4b and e. This eddy was typically episodic and energetic enough to cause an injection of essential nutrients into the euphotic layer, resulting in the enhanced levels of algal biomass which produced Chl-a concentrations from 0.9 to 2.7 mg m
3. Falkowski et al. (1991) reported such increased biomass concentration associated with the cyclonic eddy features. The eddy-like feature, that did not trap algal matter-like rings, produced upwelling over a time scale sufficiently long to produce a transient bloom at this location and resulted in a trail-like Chl-a pattern that extended over a few hundreds kilometers from waters north off Pohang coast to waters north off Ulleungdo in the East Sea. Trajectory of a satellite-tracked surface drifter (Agros buoy) and hydrographic measurements demonstrated that this pattern was induced as a consequence of EKWC along the east Korean coast that produced anticyclonic circulation of water mass around Ulleungdo with high speed of about 50– 60 cm s
1 (Chang et al., 2002). In September 2000, C. polykrikoides bloomed extensively with higher cell concentrations and discolored waters all along the southeastern coast, posing potential threat to aquaculture fisheries and other marine organisms (Fig. 4c and d). The coastal blooms initiated in cold and low saline waters resulting from monsoonal rains, while the rapid growth and offshore extension of C. polykrikoides bloom was sustained by the physical warm currents. The TWC characterized by S > 32.2 and u > 21 8C at

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surface and S > 34.4 and u > 15 8C at 75 dbar was very intensive during this period directing the spatial patterns of these blooms (over hundreds of kilometer) on the Offshore Branch along the Japanese coast (Fig. 4c, d and f). In fact, this was the first time such massive blooms directed on the Offshore Branch were detected over an expanse stretching hundreds of kilometer along the Japanese coast. The absence of sea truth data did not allow confirming this bloom event. CTD observations showed that the southward penetration of NKCC waters along the Korean coast induced hampering the escalation of EKWC, giving rise to the strong eastward flow of the Offshore Branch, which directed the spatial structure of this bloom to the southern East Sea during September 2000 (Fig. 4d and f). As a result of NKCC waters, a previously formed anticyclonic eddy feature in May 2000 appeared to be dominated by waters of lower salinity and temperature S < 33 and u < 15 8C, and consequently SeaWiFS-derived Chl-a around the eddy feature south off Ulleungdo became very low 0.5– 2.1 mg m
3 (as seen in Fig. 4d), indicative of the deformation of this eddy feature in the East Sea during September 2000. 3.2. Detection of red tide blooms with the spectral enhancement and classification techniques The SeaWiFS-derived Chl-a combined with physical oceanographic information provided a means of detecting, delineating and monitoring of coastal and offshore extent of the C. polykrikoides blooms in the Korean Southeast Sea. However, analysis of Chl-a alone does not seem to be effective for the delineation of C. polykrikoides blooms, because it helps only in identifying areas with high chlorophyll concentration rather than distinguishing C. polykrikoides blooms from surrounding non-bloom and sediment dominated turbid waters. Tang et al. (2003) observed that such high-chlorophyll concentrations often result from artifacts owing to abundance of dissolved organic and particulate inorganic sediments around river mouths and estuaries. Therefore, it is very essential to correctly identify C. polykrikoides blooms from other optically dominant water types, which requires additional capability rather than simply identifying chlorophyll patterns (Stumpf et al., 2003). Optical methods have been previously developed for detecting

Coccolithophores and Trichodesmium spp. (Brown and Yoder, 1994; Subramaniam and Carpenter, 1994), but these methods require water lacking particulate matter and other dissolved pigments. With the intension of correctly identifying potential areas of C. polykrikoides blooms and enhanced understanding of bloom patterns, the Forward Principal Component Analysis and Minimum Spectral Distance (MSD) classification techniques were attempted on both low spatial resolution SeaWiFS ocean color imagery (acquired on 14 August 1998 and 19 September 2000) and high spatial resolution Landsat-7 ETM+ imagery (acquired on 24 August 2001). During the process of FPCA, a covariance matrix of the input bands was computed, and this covariance matrix was used in the subsequent stage to compute the principal components or eigenvectors. Table 2 shows the eigenvalues and variance (%) explained by each component computed from SeaWiFS images acquired on 14 August 1998 and 19 September 2000, respectively. The total variance in percentage was calculated for each component using the following formula: % variance explained = (eigenvalues of component  100)/sum P of all eigenvalues, i.e., % variancei ¼ li  100= ni¼1 li . It appears that the first five components contain nearly 100% of the critical data contained in the eight bands. Similarly for components 1–8, the % variance explained decreased rapidly and the cumulative percentage that is a check for all eight components was equal 100%. The last three components containing mostly noise were disregarded here. For the convenience, multiple components (containing least to most information) Table 2 The eigenvalues and % variance explained by each component computed from SeaWiFS images acquired on 14 August 1998 and 19 September 2000 Component

1 2 3 4 5 6 7 8

SeaWiFS image (14 August 1998)

SeaWiFS image (19 September 2000)

Eigenvalue

% Variance

Eigenvalue

% Variance

56.46536 1.1767 0.118244 0.022436 0.019221 0.006051 0.000833 0.000301

97.67547 2.035491 0.204543 0.03881 0.03325 0.010468 0.001441 0.000521

54.68769 0.493074 0.172289 0.028757 0.016871 0.004643 0.000233 0.000103

98.70771 0.889967 0.31097 0.051905 0.030452 0.00838 0.00042 0.000186

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were displayed simultaneously to facilitate interpretation of C. polykrikoides bloom from other dominant optical water types. Fig. 5a and b compare SeaWiFS-derived Chl-a and spectrally transformed FPCA image obtained from multiplied components 1 and 5 (containing most and least information). Comparison reveals that SeaWiFSderived Chl-a simply shows chlorophyll pattern that was thought to result from C. polykrikoides blooms, but FPCA image supports improved detection and discrimination of C. polykrikoides blooms (in pink tone) from non-bloom (in blue to green) and turbid waters (brown). Because of optical complexity of these waters and problem associated with the standard SeaWiFS atmospheric correction algorithm, a white mask was created on the SeaWiFS-derived Chl-a in the Jin-hae bay and neighboring coastal bays (Fig. 5a). In contrast, the FPCA image processed after application of Spectral Shape Matching Method (SSMM) (Ahn and Shanmugam, 2004) for correcting the

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atmospheric effects in the SeaWiFS image exhibit apparent patterns of C. polykrikoides bloom in these coastal bays (Fig. 5b). This means that SSMM enabled retrieval of water-leaving radiance in high scattering and absorbing waters in proximity to the coast. From the FPCA image, it is evident that C. polykrikoides bloom around the Jin-hae bay and a small pocket of turbid water around Pusan river mouth appear to move eastward to influence optical properties of water masses off the Ulsan coast. The large accumulation of C. polykrikoides in the upwelling area off the Ulsan coast might have caused damage to the aquaculture farms and associated marine ecosystem. However, our data set restricted to the Jin-hae bay did not confirm this bloom event in the Ulsan coastal waters and offshore waters. Similarly, Fig. 5c and d show the SeaWiFS-derived Chl-a and a color composite FPCA image from three components 5, 2 and 1 that demonstrated majority of spatial variability among C. polykrikoides bloom and

Fig. 5. (a–f) Detection of C. polykrikoides blooms with the spectral enhancement techniques applied to SeaWiFS and Landsat-7 ETM+ data. (a– d) Comparison between SeaWiFS-derived Chl-a and FPCA images and (e and f) original and enhanced images (contrast stretching) of Landsat-7 ETM+ data acquired over the Southeast Sea on 24 August 2001.

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other water constituents. It appears that C. polykrikoides bloom patterns inferred from the SeaWiFSderived Chl-a compare well with those (orange and red patches) displayed in the FPCA image, excluding areas of turbid plume associated with the Pusan river mouth and its adjacent coastal waters and coastal waters west off Kosong coast, where SeaWiFSderived Chl-a falsely identifies C. polykrikoides blooms. Interpretation of Chl-a suggests that C. polykrikoides bloom indications in areas of such highly colored waters should generally be ignored (Stumpf et al., 2003). In FPCA image, five categories can be distinguished, namely dense red tides (in yellow and orange), less dense red tides (in pink and red), highly turbid water (in blue), less turbid water (in dark blue) and non-bloom waters (in green) (Fig. 5d). The movement and future location of the dense phase of C. polykrikoides bloom can also be captured from an enhanced color composite zoomed image (using original image of B841) shown on the right side of Fig. 5e (denoted by a cross mark). The dense phase moved southwardly occupies large areas of Kosong waters, posing potential threat to the entire Kosong coastal ecosystem during 19 September 2000. On the contrary, the C. polykrikoides bloom appeared to be highly persistent around the Jin-hae bay and expanded significantly to encompass areas in the Southeast Sea offshore and southern East Sea. The highly dynamic C. polykrikoides bloom patterns outside the bay coexisted with turbid waters from the Pusan river, and the intrusion of Tsushima Warm Current remained the main cause governing the geographical distribution of the C. polykrikoides blooms in these waters. The high resolution Landsat-7 ETM+ imagery (only visible and near infrared bands) acquired on 24 August 2001 over the Southeast Sea was also processed to provide what information can be gained from such high resolution data regarding C. polykrikoides bloom dynamics, its direction of movement and areas of high persistence and distribution. This was the period of highly intense C. polykrikoides blooms coinciding with our field measurement and field and aerial survey (by helicopter) conducted by NFRDI. The field measurement revealed that C. polykrikoides blooms appeared to be darker with several striking patterns observed around the Kosong waters, Jin-hae bay and off the southern and eastern coasts of Geoje island. These dark patches of C.

polykrikoides bloom were difficult to be detected with the geometrically and atmospherically corrected False Color Composite (FCC) image (generated using ETM+ bands 432) (Fig. 5e), but were conspicuous when the spectral enhancement was done by manipulating the range of digital radiance values in the color composite images (Fig. 5f is displayed with B321 and a small subset shown on the top right corner of this image is displayed with B123), graphically represented by their histograms. The multiple color display consisted of considerable spatial variability characterized by three different color ranges corresponding to different levels of red tide algal species and associated water constituents. The subset image shown on the top right corner of Fig. 5f demonstrates linear and filament-like dark patches (originating from the coastal areas of Kosong) consistent with NFRDI observations (see Fig. 7c). These dark patches were also tracked from SeaWiFS-derived Chl-a (4–53 and 1–7 mg m
3 for less dense phase) image of this period. The development of most part of this bloom might have been caused by coupled eutrophication and oceanic processes. In order to map potential areas of C. polykrikoides blooms, the use of Minimum Spectral Distance classification was explored using atmospherically corrected SeaWiFS and Landsat-7 ETM+ imagery. Pasterkamp et al. (2002) established algal bloom classes with the application of supervised classification techniques using SeaWiFS imagery, while Danaher and Omongain (1992) developed a similar classification algorithm based on the singular value decomposition (SVD) technique for the detection and classification of algal bloom types from reflectance data. The success of these classifications largely depends on the knowledge of the study area and optical significance of various water types. In this study, several training data points (samples) were identified for each of four dominant water class types in case of SeaWiFS image (Fig. 6a–d) and three dominant water class types in case of Landsat-7 ETM+ image in order to perform MSD classification of both these image data. Attention was paid in selecting these training data points so as to reduce possible errors associated with classification. The mean spectral values (water-leaving radiance in units of mW cm
2 mm
1 s
1) of these classes in each of SeaWiFS and Landsat-7 ETM+ bands are given in

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Fig. 6. (a–d) Training data points (samples) collected from the atmospherically corrected SeaWiFS image data (19 September 2000) in order to perform MSD classification, showing major optical water types such as red tide, mixed type (red tide and suspended sediments), turbid water and clear water. The mean spectral values in each SeaWiFS bands and for each class are given in Table 3. X-axis—SeaWiFS band number and Yaxis—water-leaving radiance.

Table 3. Prior to the classification, these training signatures were evaluated using two separability measures—Jeffries–Matusita (JM), Transformed Divergence (TD) and the results are shown in Table 4. It is confirmed that the selected training data

points are good separable from each other having high values in both JM and TD measures. The result of classification of SeaWiFS image indicates that good discrimination was possible between the dense phase of C. polykrikoides bloom

Table 3 Mean spectral values in each SeaWiFS and Landsat-7 ETM+ bands for different training data points representing major optical water types in the study area Band no.

1 2 3 4 5 6 7 8

SeaWiFS image (19 September 2000) (mean spectrum)

Landsat-7 ETM+ image (24 August 2001) (mean spectrum)

Red tide

Mixed type

Turbid water

Clear water

Red tide

Turbid water

Clear water

0.3344 0.3517 0.3495 0.3787 0.6055 0.2163 0.0764 0.0524

0.6080 0.9176 1.2711 1.3715 1.6205 0.5548 0.0786 0.0463

1.1987 1.8321 2.5105 2.4713 2.3824 0.7244 0.2147 0.1531

0.8803 0.9350 0.7302 0.5726 0.3558 0.1411 0.0696 0.0509

0.2468 0.3711 0.2039 0.0686

0.7138 1.1691 1.0439 0.1229

0.7151 0.4780 0.1268 0.0394

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Table 4 Results of spectral separability analysis performed on different training data points from SeaWiFS and Landsat-7ETM+ image dataa SeaWiFS radiance image (19 September 2000)

Landsat-7 ETM+ image (24 August 2001)

Red tide Mixed: (2.0, 2.0) Turbid water: (2.0, 2.0) Clear water: (2.0, 2.0)

Turbid water: (2.0, 2.0) Clear water: (1.9, 1.9)

Mixed Red tide: (2.0, 2.0) Turbid water: (2.0, 2.0) Clear water: (2.0, 2.0) Turbid water Red tide: (2.0, 2.0) Mixed: (2.0, 2.0) Clear water: (2.0, 2.0)

Red tide: (2.0, 2.0) Clear water: (2.0, 2.0)

Clear water Red tide: (2.0, 2.0) Mixed: (2.0, 2.0) Turbid water: (2.0, 2.0)

Red tide: (1.9, 1.9) Turbid water (2.0, 2.0)

Pair separation (least to most) Red tide and mixed: (2.0) Mixed and turbid water: (2.0) Red tide and clear water: (2.0) Red tide and turbid water: (2.0) Mixed and clear water: (2.0) Turbid and clear water: (2.0)

Red tide and turbid water: (2.0) Red tide and clear water: (1.9) Turbid water and clear water: (2.0)

a

Separability measures: Jeffries–Matusita (JM), Transformed Divergence (TD).

and non-bloom and sediment dominated waters, but mixed phase of this bloom coupled with turbid plume (propagating from Pusan coastal area to its offshore) could not be fully captured from non-bloom waters. The possible reason is that the MSD decision rule calculates the spectral distance between the measurement vector for the pixel to be classified and the mean vector for each signature, therefore, a class with less variance, like blue waters, may tend to become overestimated, since the pixels that belong to the class are usually spectrally closer to their mean (Jensen, 1995). The inadequate spatial resolution of the SeaWiFS image results in the large errors with the mixed water type class (Fig. 7a). In the classified image, red color indicates C. polykrikoides bloom, thistle color represents highly turbid waters, green color stands for mixed type and blue color denotes clear water. The predominantly high-suspended

sediments resulted from the river and process of sediment resuspension due to tidal currents and bottom circulations. The estimated area for the dense phase of the C. polykrikoides bloom was about 26 km2 covering the Jin-hae bay and Kosong waters, while it was over 30 km2 for the mixed phase of the bloom extending to include offshore waters in the Southeast Sea. In contrast, classification of Landsat-7 ETM+ image data with MSD mapping technique could bring out detailed information about the location, direction of movement, distribution and intricate patterns of C. polykrikoides bloom off the Korean southeastern coast (Fig. 7b). Three distinct categories as red tide, suspended sediments and seawater were mapped from Landsat-7 ETM+ image, because intension with the derivation of more number of classes produced unrealistic results and led to the underestimation of the spatial extent of C. polykrikoides bloom in these waters. Comparison between classification of low and high spatial resolution data demonstrated that classification accuracy was higher in Landsat-7 ETM+ image than in SeaWiFS image data, however, both images clearly showed strong persistence of C. polykrikoides bloom between Geoje island and Kosong coastal areas and inside the Jin-hae bay. For validation of the classification, we used data collected on 21 August 2001 through field and aerial survey (by helicopter) by NFRDI (Fig. 7c) (Suh et al., 2004). The C. polykrikoides bloom density was observed to exceed 3000 cells ml
1 (in red color) in the western and southern parts off Geoje island, while relatively less dense bloom with concentrations less than 3000 cells ml
1 (in stripped polygons) dominated Kosong coastal waters and all along the southeastern coastal areas (Fig. 7c). It should be recalled that bloom of higher density (exceeding 1000 cells ml
1) would have a potential impact on the aquaculture fish and other marine organisms (see Table 1) (Kim, 1998). Validation of classification revealed that the inferred patterns and distribution of C. polykrikoides bloom by MSD classification on Landsat-7 ETM+ image data closely resembled to that observed in situ and through aerial reconnaissance survey by NFRDI, indicating the reliability of the MSD classification. A similar classification can also be achieved through direct spectral discrimination using feature

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Fig. 7. (a and b) Detection of red tide algal blooms with the MSD mapping technique applied to SeaWiFS (19 September 2000) and Landsat-7 ETM+ images (24 August 2001). These images give an idea that C. polykrikoides bloom recurs in the Jin-hae bay and Kosong coastal areas west of Geoje island during the fall season. We observed that the high spatial resolution Landsat-7 ETM+ image brings out detailed information about the C. polykrikoides bloom patterns consistent with in situ data (c) collected on 21 August 2001 by NFRDI (Suh et al., 2004). No data are available for corroborating massive blooms occurred in the Jin-hae bay during this period.

space shown in Fig. 8. The ratio Lw (510/555) against Lw (443) (from SeaWiFS) allows one to extract patterns of red tides from other dominant optical water types such as turbid waters and non-bloom (clear waters) waters. However, the success of this method largely depends on verification data to confirm the bloom event, because non-red tide bloom may also show similar patterns in the feature space.

4. Discussion and conclusion The increased terrestrial and water-born pollutants in the closed and semi-enclosed bays of the Korean Southeast Sea result in the occurrence of potentially toxic red tide blooms, seasonal anoxia and shellfish intoxication (Kim, 1998). C. polykrikoides which is a species with a very adoptable physiology, frequently occurring, widespread and persistent and

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Fig. 8. Discrimination of red tide algal blooms from turbid and nonbloom waters. Red tides are identified at the lower left vertex, while clear and turbid waters can be captured from the lower right vertex and left upper vertex in the scatter plot of Lw (510/555) and Lw (443). Mixing region may occur in the centre of the feature space. If this method is intended to be used for this application, one needs to confirm the type of algal bloom and its location in the feature space.

accompanying mass fish mortalities forms these red tide blooms. Until now it has been found to be very hard to accurately locate, identify, monitor and forecast the future locations of C. polykrikoides blooms and there are ineffective countermeasures to mitigate the subsequent damages. What causes initiation of such colossal blooms in these waters? Apparently, the nutrient enrichment is the main cause of these blooms, which occur in the following ways: monsoonal rainfalls and typhoons that produce anomalous floods and heavy surface runoff in the Korean southern peninsula, flushing nutrients which provide unusual inputs of inorganic and organic nutrients beyond the intolerable level, aquaculture/ shrimp forming which is carried under intensive and semi-intensive schemes producing enrichment of the waters mainly with organic nutrients in all along the southern coastal areas, especially during summer and fall seasons. Alonso-Rodriguez and Paez-Osuna (2003) pointed out that such enrichment of nutrients in the shrimp forming areas often result in occurrence of a series of red tides in the Gulf of California. In addition to antheropogenic nutrients, pH may play a

very significant role, particularly within enclosed and semi-enclosed environments such as the South Sea. Martinez-Lopez et al. (2001) observed the influence of high pH as wells as runoff nutrient inputs that trigged red tide blooms off the Sinaloa coast. Higher concentrations and longer persistence of C. polykrikoides bloom in such semi-enclosed environments have been reported to cause extensive damage and serious economic loss (Kim, 1998), who indicated that C. polykrikoides species has better adaptations to thrive, even in highly turbid water environments. In addition to the above factors, modification of the physical environment that causes reduced turbulence, high water residence times and high nutrients concentrations has been noted as adequate environments favoring C. polykrikoides blooms. It has also been shown that C. polykrikoides grows well in slightly eutrophic water similar to chemical oxygen demand (COD) of 1 ppm (Kim, 1998). Warm and such slightly eutrophic environment is optimal for the rapid growth of this species forming in the Southeast Sea during late August and September, when eutrophic water is mixed with warm water offshore. This warm water formation occurs mainly due to the northeastward intrusion of TWC. The low salinity waters resulting due to rain sustain the development of potentially toxic dioflagellate C. polykrikoides in the semi-enclosed bays, while TWC waters of high temperature and salinity remain the main causes controlling the dynamics and distribution of the C. polykrikoides blooms in the Southeast Sea offshore and southern East Sea. Coupled heavy rainfall and flow of warm current cause an exchange of sea water with water mass of the Jin-hae bay, which means that C. polykrikoides blooms appears to have flowed out from the Jin-hae bay. The eddy-like features inferred from AVHRRderived SST image off the southeastern coast produce vertical mixing and pumping of nutrients from bottom layers to the well-lit surface layer, which result in quick eutrophic situations with observed patterns of C. polykrikoides blooms. Considerable efforts have been made on the data collected from satellites and in situ observations to better understand the population dynamics of the C. polykrikoides blooms in waters off the Korean southeast coast. In summer and fall seasons, rapid growth and outbreaks of C. polykrikoides blooms were

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observed to occur around the Jin-hae bay and neighboring waters. During this time, the bloom reaches densities of 1000 and 28,000 cells ml
1 and discolors waters all along the entire southeastern coastal areas, causing negative impacts to aquaculture fish populations and other marine lives (Kim et al., 1994). The time series SeaWiFS-derived Chl-a captured spatial distribution of C. polykrikoides blooms during August and September (1998–2002), while AVHRR-derived SST and CTD data provided a complete overview of prevailing hydrography around the coastal bays and open oceans. Though SeaWiFSderived Chl-a provided us a means of delineating potential areas of red tide bloom with higher chlorophyll concentrations, it did not support the detection of dominant C. polykrikoides species in the bloom. In addition, SeaWiFS-derived Chl-a often falsely identified C. polykrikoides bloom in areas abundant in dissolved organic and particulate inorganic matters around river mouths and estuaries. Consequently, Chl-a appears not to be an unique indicator for identifying bloom species (Stumpf et al., 2003) as it derives from whole population rather than species of the region, and therefore researchers needed to look for other techniques based on optical properties (Brown and Yoder, 1994; Subramaniam and Carpenter, 1994) or spectral discrimination or classification techniques (Danaher and Omongain, 1992; Pasterkamp et al., 2002). Implementation of the FPCA and MSD classification techniques allowed us to correctly identify and locate the areas of C. polykrikoides bloom occurrences in the Korean Southeast Sea coastal waters using SeaWiFS and Landsat-7 ETM+ images. Though SeaWiFS image would help detection and classification of dense phase of C. polykrikoides blooms around the coastal bays, inadequate spatial resolution of this image did not allow capturing dynamic patterns of C. polykrikoides blooms from the mixed phase (coupled with turbidity) and clear waters using MSD mapping technique. In contrast, analysis of high spatial resolution Landsat-7 ETM+ imagery allowed improved detection and understanding of organized patterns of C. polykrikoides blooms and their dynamics in both turbid and clear waters. However, one of the limitations of the use of ETM+ imagery is inadequate temporal resolution to monitor the bloom in a highly heterogeneous coastal oceanic ecosystem.

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Most of the land observation satellites have similar temporal characteristics (Jensen, 1995; Shanmugam, 2002). Thus, the effective way of detecting and monitoring of the bloom is the use of high temporal and spatial resolution imagery that can be obtainable from new generation ocean color sensors. These images are readily available with low budget than those from Landsat, SPOT or other land observation satellite sensors. As a part of our continuing red tide monitoring program, various methods and approaches were attempted and demonstrated in relation to correctly identifying potential areas of C. polykrikoides bloom in the Korean Southeast Sea coastal waters using SeaWiFS and Landsat-7 ETM+ images of the period 1998–2002. When C. polykrikoides bloom starts to occur in these areas, it is very essential to monitor the bloom based on daily observations of ocean color from space and surface which coupled with other environmental data will allow us to predict subsequent development of the blooms in the affected areas and neighboring waters likely to be affected. Such observations will also allow rapid implementation of reasonable and appropriate countermeasures to mitigate the bloom.

Acknowledgements This research was supported by Ministry of Science and Technology (MOST) and Ministry of Maritime Affairs and Fisheries (MOMAF) under the KORDI contract PM 294-00 and PN 524-00. The authors are greatful to two anonymous reviewers for their valuable comments and suggestions for improving this manuscript. [SES]

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