• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.173-182
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• 2013

The early Sea-viewing Wide Field-of-view Sensor(SeaWiFS) atmospheric correction algorithm which is the basis of the atmospheric correction algorithm for Geostationary Ocean Color Imager(GOCI) assumes that water-leaving radiances is negligible at near-infrared(NIR) wavelengths. For this reason, all of the satellite measured radiances at the NIR wavelengths are assigned to aerosol radiances. However that assumption would cause underestimation of water-leaving radiances if it were applied to turbid Case-2 waters. To overcome this problem, Management Unit of the North Sea Mathematical Models(MUMM) atmospheric correction algorithm has been developed for turbid waters. This MUMM algorithm introduces new parameter ${\alpha}$, representing the ratio of water-leaving reflectance at the NIR wavelengths. ${\alpha}$ is calculated by statistical method and is assumed to be constant throughout the study area. Using this algorithm, we can obtain comparatively accurate water-leaving radiances in the moderately turbid waters where the NIR water-leaving reflectance is less than approximately 0.01. However, this algorithm still underestimates the water-leaving radiances at the extremely turbid water since the ratio of water-leaving radiance at two NIR wavelengths, ${\alpha}$ is changed with concentration of suspended particles. In this study, we modified the MUMM algorithm to calculate appropriate value for ${\alpha}$ using an iterative technique. As a result, the accuracy of water-leaving reflectance has been significantly improved. Specifically, the results show that the Root Mean Square Error(RMSE) of the modified MUMM algorithm was 0.002 while that of the MUMM algorithm was 0.0048.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.475-486
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• 2009

Harmful algal blooms (HAB) caused by the dominant species Cochlodinium polykrikoides (C. polykrikoides) appear in the South Sea of Korea and are particularly present in summer and fall seasons. Environmental factors such as water temperature, weather conditions (air temperature, cloud cover, sunshine, precipitation and wind) influence on the initiation and subsequent development of HAB. The purpose of this research was to study spatial and temporal variations of HAB in the Yeosu area using environmental (oceanic and meteorological) and satellite data. Chlorophyll-a concentrations were calculated using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) images by an Ocean Chlorophyll 4 (OC4) algorithm, and HAB were estimated using the Red tide index Chlorophyll Algorithm (RCA). We also used the surface velocity of sequential satellite images applying the Maximum Cross Correlation method to detect chlorophyll-a movement. The results showed that the water temperature during HAB occurrences in August 2002-2008 was $19.4-30.2^{\circ}C$. In terms of the frequency of the mean of cell density of C. polykrikoides, the cell density of the HAB found at low (<300 cells/ml), medium (300-1000 cells/ml), and high (>1000 cells/ml) levels were 27.01%, 37.44%, and 35.55%, respectively. Meteorological data for 2002-2008 showed that the mean air temperature, precipitation, wind speed and direction, and sunshine duration were $22.39^{\circ}C$, 6.54 mm/day, 3.98 m/s (southwesterly), and 1-11.7 h, respectively. Our results suggest that HAB events in the Yeosu area can be triggered and extended by heavy precipitation and massive movement of HAB from the East China Sea. Satellite images data from July to October 2002-2006 showed that the OC4 algorithm generally estimated high chlorophyll-a concentration ($2-20\;mg/m^3$) throughout the coastal area, whereas the RCA estimated concentrations at $2-10\;mg/m^3$. The surface velocity of chlorophyll-a movement from sequential satellite images revealed the same patterns in the direction of the Tsushima Warm Current.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.103-106
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• 2003

Retrieval of ocean color information from Multispectral Camera (MSC) on KOMPSAT-2 was investigated to study and characterize small-scale biophysical features in the coastal oceans. Prior to the derivation of such information from space-acquired ocean color imageries, the atmospheric effects largely from path and the air-sea interface should be removed from the total signal recorded at the top of the atmosphere (T$_{TOA}$). In this study, the 'path-extraction' is introduced and demonstrated on the TM and SeaWiFS imageries of highly turbid coastal waters of Korea. The algorithms for retrieval of ocean color information were explored from the remote reflectance (R$_{rs}$) in the visible wavebands of MSC. The determination of coefficient (R$^{2}$) for log-transformed data [ N = 500] was 0.90. Similarly, the R$^{2}$ value for log-transformed data [ N = 500] was found to be 0.93.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.307-313
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• 2004

The trajectories of 8 autonomous profiling floats deployed in the Kuroshio Extension region in February 2001 are used to depict the circulation pattern at the surface and 2000db. The corresponding sea surface topography maps created from satellite altimeter and dynamic height climatology were compared with the tracks of nearly coincident floats and were found to agree well in most cases except for the period June 5 to 16 2001. It is shown that over the period the conspicuous breakaway of the floats from an expected path is possibly associated with the abnormal path of the Kuroshio Extension such as an outbreak event, as revealed by AVHRR infrared and SeaWiFS chlorophyll-a images and cruise data in cross sections.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.366-375
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• 1998

Optical characteristics of the yellow sand and their influences on the ocean color remote sensing has been studied using ocean color sensor SeaWiFS measurements. Two cases of April 18 and April 25, 1998, representing yellow sand and background aerosol, are selected for emphasizing the impact of high aerosol concentration on the ocean color remote sensing. It was shown that NASA's standard atmospheric correction algorithm treats yellow sand area as either too high radiance or cloud area, in which ocean color information is not generated. Optical thickness of yellow sand arrived over the East Asian sea waters in April 18 indicates that there are two groups loaded with relatively homogeneous yellow sand, i.e.: heavy yellow sand area with optical thickness peak around 0.8 and mild area with about 0.4, which are consistent with ground observations. The movement of the yellow sand area obtained from surface weather maps and backward trajectory analysis manifest the notion that the weak yellow sand area was originated from the outer region of the dust storm. It is also noted that high optical thickness associated with the yellow sand is significantly different from what we may observe from background aerosol, which is about 0.2. These characteristics allow us to determine the yellow sand area with an aid of atmospheric correction parameter. Results indicate that the yellow sand area can be determined by applying the features revealed in scattergrams of atmospheric correction parameter and optical thickness.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.166-173
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• 2004

By analyzing the sea surface temperature (SST), phytoplankton and NOAA/AVHRR satellite data of Gijang, located at the eastern coast of the korean peninsula during the period of 2001 to 2003, we have analyzed the daily variation in the upwelling cold water, phytoplankton, and chlorophyll a. The SST of Gijang coast appealed rapid change due to the temporal and spatial variation of the upwelling cold water. This in turn led to an increase in the number of phytoplanktons and other varieties of organisms inhabiting in the Gijang coastal region.

• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.35-42
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• 2002

The results of our observation in May 2000 indicated that the SeaWiFS algorithm (O'Reilley et al., 1998), which was adopted for OSMI data processing, overestimated the actual chlorophyll values. This was rather unexpected in that there were good reasons to expect that the bio-optical properties of East/Japan Sea belonged to Case 1 water and in such case, the OC2 algorithm would give unbiased estimates of actual chlorophyll a values. In November 2000, a cruise conducted bio-optical surveys in the same area. This time we added HPLC (High Performance Liquid Chromatography) method for measuring chlorophyll a concentration to the standard fluorometric method, which we hale been using during the past Fluorometric method with acidification is known to result in under/overestimation of chlorophyll values in many parts of the world oceans, while it is easier and cheaper than HPLC method. To our surprise, the comparison of HPLC chlorophyll and fluorometric chlorophyll values show that fluorometric values gave an underestimation up to 50%. This error was due to the presence of accessory pigments such as chlorophyll b. Considering this error, our precious result of May 2000(Yoo et al., 2000) might have to be reinterpreted. Calculation of reflectance at 490 and 555nm, however, indicated that this is not still enough to explain the discrepancies.

• Ocean and Polar Research
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• v.34 no.2
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• pp.201-218
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• 2012

The purpose of this study is to investigate climatological variations from the sea surface temperature (SST), chlorophyll-a concentration (Chl-a), and phytoplankton size class (PSC), using NOAA AVHRR, SeaWiFS, and MODIS data in the South Sea of Korea (SSK) and East China Sea (ECS). 26-year monthly SST and 13-year monthly Chl-a and PSC data, separated by whole and nine-different areas, were used to understand seasonal and inter-annual variations. SST and Chl-a clearly showed seasonal variations: higher SST and Chl-a were observed during the summer and spring, and lower values occurred during the winter and summer. The annual and monthly SST over 26 years increased by $0.2{\sim}1.0^{\circ}C$. The annual and monthly Chl-a concentration over 13 years decreased by $0.2{\sim}1.1mg/m^3$. To determine more detailed spatial and temporal variations, we used the combined data with monthly SST, Chl-a, and PSC. Between 1998 and 2010, the inter-annual trend of Chl-a decreased, with decreasing micro- and nano-size plankton, and increasing pico-size plankton. In regional analysis, the west region of the study area was spatially and temporally correlated with the area dominated by decreasing micro-size plankton; while the east region was less sensitive to coastal and land effects, and was dominated by increasing pico-size plankton. This phenomenon is better related to one or more forcing factors: the increased stratification of ocean driven by changes occurring in spatial variations of the SST caused limited contributions of nutrients and changed marine ecosystems in the study area.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.209-212
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• 2006

황해와 동중국해의 해황 변동에 관한 연구는 현장관측을 중심으로 체계적으로 많이 수행되어 왔지만, 인공위성자료를 이용한 황해와 동중국해의 해황 변동 연구는 미비한 실정이다. 이것은 인공위성자료를 통해 얻을 수 있는 관측항목이 표층수온자료에 국한되어 있었기 때문이다. 그러나 SeaWiFS 해색위성과 같은 인공위성자료들을 이용하여 부유물 농도, 엽록소 농도 등이 원활하게 생산되고 있으며 최근 연구결과에 의해 염분과 유향성분 동도 추정 및 추출이 가능케 되었으므로 이들 인공위성자료를 이용한 황해와 동중국해의 해황 변동에 관한 연구를 수행하게 되었다. 특히 2004 년도는 계절변동에 있어서 이상기후의 해라고 점철되고 있다. 2004년 봄철의 폭설과 일시적인 고온현상, 여름철에는 10년만의 무더위, 겨울철에는 36년만에 가장 포근한 날씨가 지속되었다. 이러한 이상기후의 발생은 해양과 대기의 상호작용에 의해서 기인했을 것이라고 생각되어 한반도 주변 해역에서 황해와 동중국해의 해황변동이 연안해역의 해황변동과 어떠한 연관성이 존재하고, 이러한 요인들은 2004년도에 발생한 이상기후와 어떤 상관관계를 갖는지 연구하기 위한 기초연구를 진행하였다. 2003년 12월 - 2004년 2월과 2004년 12월 2005년 2월에 통일한 시기에 관측된 NOAA 표층수온 분포 영상자료들을 황해와 동중국해 해역을 중심으로 월별로 비교해보면 2003년 12월 - 2004년 1월에 관측된 표층수온 분포값보다 2004년 12월 - 2005년 1월에 관측된 표층수온 분포값이 상대적으로 높은 분포 특성을 나타내고 있었다. 이와 같은 현상은 국립수산과학원의 2004년 10월과 12월의 정선관측자료에서도 나타나고 있었다. 그러나 이와는 반대로 2004년 2 월에 관측된 표층수온 분포값보다 2005년 2월에 관측된 표층수온 분포값이 상대적으로 낮은 분포 특성을 나타내고 있었다. 따라서 인공위성자료를 이용한 황해의 2004년 해황 분석 결과는 이상수온 상승의 원인이 쿠로시오 해류의 변통과 관련성이 높다고 판단되며 이에 대한 지속적인 연구가 현재 진행중에 있다.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.341-343
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• 2006

The current spectral shape matching method (SSMM), developed by Ahn and Shanmugam (2004), relies on the assumption that the path radiance resulting from scattered photons due to air molecules and aerosols and possibly direct-reflected light from the air-sea interface is spatially homogeneous over the sub-scene of interest, enabling the retrieval of water-leaving radiances ($L_w$) from the satellite ocean color image data. This assumption remains valid for the clear atmospheric conditions, but when the distribution of aerosol loadings varies dramatically the above postulation of spatial homogeneity will be violated. In this study, we present the second version of SSMM which will take into account the horizontal variations of aerosol loading in the correction of atmospheric effects in SeaWiFS ocean color image data. The new version includes models for the correction of the effects of aerosols and Raleigh particles and a method fur computation of diffuse transmittance ($t_{os}$) as similar to SeaWiFS. We tested this method over the different optical environments and compared its effectiveness with the results of standard atmospheric correction (SAC) algorithm (Gordon and Wang, 1994) and those from in-situ observations. Findings revealed that the SAC algorithm appeared to distort the spectral shape of water-leaving radiance spectra in suspended sediments (SS) and algal bloom dominated-areas and frequently yielded underestimated or often negative values in the lower green and blue part of the electromagnetic spectrum. Retrieval of water-leaving radiances in coastal waters with very high sediments, for instance = > 8g $m^{-3}$, was not possible with the SAC algorithm. As the current SAC algorithm does not include models for the Asian aerosols, the water-leaving radiances over the aerosol-dominated areas could not be retrieved from the image and large errors often resulted from an inappropriate extrapolation of the estimated aerosol radiance from two IR bands to visible spectrum. In contrast to the above results, the new SSMM enabled accurate retrieval of water-leaving radiances in a various range of turbid waters with SS concentrations from 1 to 100 g $m^{-3}$ that closely matched with those from the in-situ observations. Regardless of the spectral band, the RMS error deviation was minimum of 0.003 and maximum of 0.46, in contrast with those of 0.26 and 0.81, respectively, for SAC algorithm. The new SSMM also remove all aerosol effects excluding areas for which the signal-to-noise ratio is much lower than the water signal.