• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.249-255
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• 1999

Water pollution is becoming a serious problem in the populous cities and coastal areas near industrial complex. Sometimes, phytoplankton is considered as the most important element in the coastal environment. Phytoplankton is easily estimated by measuring chlorophyll content in the laboratory. In this study, to build up estimating algorithm of the chlorophyll amount related to the monitoring of coastal environments in Kwangyang bay, the correlationship the respective in situ observed data with Landsat TM and SeaWiFS satellite Image was analyzed. It showed that Landsat TM band 3 image has the highest correlationship with observed data, and based upon this result the monitoring algorithm of chlorophyll in coastal area was extracted. This algorithm will be an important for extracting and controlling environment elements in coastal areas in the future. And it has a significant meaning that it has established a spatial data construction in which satellite image alone could monitor the coastal environment.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 춘계학술대회 논문집
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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.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 춘계학술대회 논문집
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• pp.95-100
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• 2006

Measurements of ocean color from space since 1970s provided vital information with reference to physical and biogeochemical properties of the oceanic waters. The utility of these data has been explored in order to map and monitor highly toxic/or harmful algal blooms (HABs) that affected most of coastal waters throughout the world due to accelerated eutrophication from human activities and certain oceanic processes. However, the global atmospheric correction and bio-optical algorithms developed for oceanic waters were found to yield false information about the HABs in coastal waters. The present study aimed to evaluate the potential use of red tide index (RI) method, which has been developed by Ahn and Shanmugam (2005), for mapping of HABs in Korean and neighboring waters. Here we employed the SSMM to remove the atmospheric effect in the SeaWiFS image data and the achieved indices by RI method were found more appropriate in correctly identifying potential areas of the encountered HABs in Korean South Sea (KSS) and Chinese coastal waters during 1999-2004. But the existence of high absorbing and scattering materials greatly interfered with the standard OC4 algorithm which falsely identified red tides in these waters. In comparison with other methods, the RI approach for the early detection of HABs can provide state managers with accurate identification of the extent and location of these blooms as a management tool.

• 한국환경과학회지
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• 제17권1호
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• pp.85-95
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• 2008

Temporal and spatial variabilities of chlorophyll a (Chl-a) in the northern East China Sea (ECS) are described, using both 8-day composite images of the SeaWiFS (Sea-viewing Wide Field-of-view Sensor) and in-situ data investigated in August and September during 2000-2005. Ocean color imagery showed that Chl-a concentrations on the continental shelf within the 50 m depth in the ECS were above 10 times higher than those of the Kuroshio area throughout the year. Higher concentrations (above $5mg/m^3$) of yearly mean Chl-a were observed along the western part of the shelf near the coast of China. The standard deviation also showed the characteristics of the spatial variability near $122-124^{\circ}E$, where the western region of the East China Sea was grater than that of the eastern region. Particularly the significant concentration of Chl-a, up to $9mg/m^3$, was found at the western part of $125^{\circ}E$ in the in-situ data of 2002. The higher Chl-a concentrations of in-situ data were consistent with low salinity waters of below 30 psu. It means that there were the close relationship between the horizontal distribution of Chl-a and low salinity water.

• 대한원격탐사학회지
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• 제28권6호
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• pp.635-651
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• 2012

To produce a level-3 monthly composite image from daily level-2 Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration data set in the East Sea, we applied four average methods such as the simple average method, the geometric mean method, the maximum likelihood average method, and the weighted averaging method. Prior to performing each averaging method, we classified all pixels into normal pixels and abnormal speckles with anomalously high chlorophyll-a concentrations to eliminate speckles from the following procedure for composite methods. As a result, all composite maps did not contain the erratic effect of speckles. The geometric mean method tended to underestimate chlorophyll-a concentration values all the time as compared with other methods. The weighted averaging method was quite similar to the simple average method, however, it had a tendency to be overestimated at high-value range of chlorophyll-a concentration. Maximum likelihood method was almost similar to the simple average method by demonstrating small variance and high correlation (r=0.9962) of the differences between the two. However, it still had the disadvantage that it was very sensitive in the presence of speckles within a bin. The geometric mean was most significantly deviated from the remaining methods regardless of the magnitude of chlorophyll-a concentration values. Its bias error tended to be large when the standard deviation within a bin increased with less uniformity. It was more biased when data uniformity became small. All the methods exhibited large errors as chlorophyll-a concentration values dominantly scatter in terms of time and space. This study emphasizes the importance of the speckle removal process and proper selection of average methods to reduce composite errors for diverse scientific applications of satellite-derived chlorophyll-a concentration data.

• 대한원격탐사학회지
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• 제27권5호
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• pp.613-623
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• 2011

본 연구에서는 Moderate Imaging Spectroradiometer(MODIS), Sea-viewing Wide Field-fo-view Sensor(SeaWiFS), Medium Resolution Imaging Spectrometer(MERIS) 등의 광역관측 위성영상을 이용한 해수나 연안수의 클로로필 농도 분석을 통해 가능성이 확인되었던 밴드 비를 이용한 비교적 간단한 추정 모델을 수체의 크기와 폭이 현저히 작고 탁도가 있는 하천에 대해 클로로필-a 농도값을 추정하고자 고해상도 위성영상에 Two-band 및 Three-band reflectance 모델을 적용하여 가능성을 파악하였다. 특히 RapidEye 영상을 이용하여 일반적으로 탁도가 있는 수체에 대해 Red와 NIR 영역을 활용하는 이들 모델에 Red-edge(RE) 밴드를 적용하였다. Red와 NIR을 이용한 Two-band Reflectance 모델은 계산식의 결정계수 $R^2$ 값이 0.38로 유의성 없는 결과를 나타내었다. 그러나 RapidEye의 Red-edge (RE) 파장 대를 이용한 Red-RE Two-band 모델과 Red-RE-NIR Three-band 모델을 이용한 계산식에 대해서는, 2차함수에 의한 Three-band 모델의 결과는 Red-RE Two-band 모델의 결과와 통계적인 값이 거의 유사하였고 Two-band와 3차함수에 의한 Three-band 모델 추정식은 각각 0.66, 0.73 의 $R^2$값을 나타내어 Red-edge 밴드의 적용 가능성을 보였고, 실측치와의 Root Mean Square Error (RMSE)는 24.8, 22.4 mg $m^{-3}$, Relative Percent Difference(RPD)는 각각 1.30, 1.29로 1.5 이하의 대략적인 추정(Approximate Prediction) 수준을 나타내었다. 고해상도 위성영상에 Red-RE-NIR Three-band 모델을 적용한 계산식을 이용해 대략적인 추정이지만 가장 유의한 수준의 클로로필-a 농도를 추정할 수 있었다. 영상에서 추정된 클로로필-a 분포를 비교하였을 때 3차함수에 의한 Three-band 모델 추정식이 Two-band 모델에 비해 낮은 값의 분포를 보였다. 향후 하천의 스펙트럼을 실측하여 파장별 부유물질, 유기물과의 상관성 및 클로로필 농도와의 간섭 정도를 시뮬레이션하여 보정식을 산출 적용한다면 탁도가 다소 높은 하천에서의 클로로필-a 농도 계산식의 정확도를 더욱 높일 수 있을 것으로 기대된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.90-93
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• 2006

The first Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meteorological Satellite (COMS) is scheduled for launch in 2008. GOCI includes the eight visible-to-near-infrared (NIR) bands, 0.5km pixel resolution, and a coverage region of 2500 ${\times}$ 2500km centered at 36N and 130E. GOCI has had the scope of its objectives broadened to understand the role of the oceans and ocean productivity in the climate system, biogeochemical variables, geological and biological response to physical dynamics and to detect and monitor toxic algal blooms of notable extension through observations of ocean color. The special feature with GOCI is that like MODIS, MERIS and GLI, it will include the band triplets 660-680-745 for the measurements of sun-induced chlorophyll-a fluorescence signal from the ocean. The GOCI will provide SeaWiFS quality observations with frequencies of image acquisition 8 times during daytime and 2 times during nighttime. With all the above features, GOCI is considered to be a remote sensing tool with great potential to contribute to better understanding of coastal oceanic ecosystem dynamics and processes by addressing environmental features in a multidisciplinary way. To achieve the objectives of the GOCI mission, we develop the GOCI Data Processing System (GDPS) which integrates all necessary basic and advanced techniques to process the GOCI data and deliver the desired biological and geophysical products to its user community. Several useful ocean parameters estimated by in-water and other optical algorithms included in the GDPS will be used for monitoring the ocean environment of Korea and neighbouring countries and input into the models for climate change prediction.

• 대한원격탐사학회지
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• 제16권4호
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• pp.305-313
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• 2000

A vicarious calibration method was developed for the OSMI sensor calibration. Employing measured aerosol optical thickness by a sunphotometer and a sky radiometer and water leaving radiance by ship measurements as inputs, TOA (top of the atmosphere) radiance at each OSMI band was simulated in conjunction with a radiative transfer model (Rstar5b) by Nakajima and Tanaka (1988). As a case of examining the accuracy of this method, we simulated TOA radiance based on water leaving radiance measured at NASA/MOBY site and aerosol optical thickness estimated nearby at Lanai, and compared simulated results with SeaWiFS-estimated TOA radiances. The difference falls within about $\pm$5%, suggesting that OMSI sensor can be calibrated with the suggested accuracy. In order to apply this method for the OSMI sensor calibration, ground-based sun photometry and ship measurements were carried out off the east coast of Korean peninsula on May 31, 2000. Simulations of TOA radiance by using these measured data as input to the radiative transfer model show that there are substantial differences between simulated and OSMI-estimated radiances. Such a discrepancy appears to be mainly due to the cloud contamination because satellite image indicates optically thin clouds over the experimental area. Nevertheless results suggest that sensor calibration can be achieved within 5% uncertainty range if there are ground-based measurements of aerosol optical thickness, and water leaving radiances under clear-sky and optically thin atmospheric conditions.

• 대한원격탐사학회지
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• 제15권3호
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• pp.227-238
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• 1999

발사 이전에 OSMI 모의 복사량을 산출함은 실제로 관측할 자료를 추정하고, 자료처리를 위한 준비에 매우 유용하다. 1999년 발사예정인 다목적 실용위성의 탑재체 중의 하나인 OSMI 자료처리 시스템은 SeaWIFS 자료처리 시스템을 OSMI에 맞추어 재개발된 것이다. 모의 복사량 계산은 OSMI 센서의 파장대역 및 스캔방식, 다목적 실용위성의 궤도에 관한 정보가 고려되어야 한다. 본 연구에서는 대양에서의 OSMI 모의 복사량을 산출하기 위해 CZCS에서 관측한 엽록소를 다목적 실용위성이 관측한다는 가정을 하게 되었다. 궤도 예측에는 수정된 Brouwer-Lyddane 모델이, water-leaving 복사량을 산출하기 위해 CZCS 엽록소 농도가, OSMI가 관측할 대기에 의한 복사량 계산에는 여러 가지 복사모델이 이용되었다. OSMI의 412, 443, 490, 555, 765, 865nm 6가시광선 파장대역에서 모의 복사량을 산출하였다. 예상대로, 총 복사량 중 water-leaving 복사량은 아주 작으며 (10% 미만), 태양해면반사에 의한 영향은 태양 적위 근처에서 관측된다. 그러므로 대기보정은 총 복사량으로부터 엽록소 농도를 계산하는데 매우 중요하다. 태양해면반사에 의해 영향을 받는 자료는 사용할 수 없으므로 OSMI 임무 기간내에 지속적인 전구 해양관측을 위해서는 체계적인 자료수집 계획이 요구된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.376-381
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• 1998

In this study, we was measured the radiance reflectance by using multi-spectral image of low resolution camera(LRC) which will be loaded in the multi-purpose satellite(KOMPSAT) to use the data in analyzing water pollution. Also we investigated the possibility of extraction of water quality factors in rivers and water body by using high resolution remote sensing data such as Airborne MSS. Especially, we tried to extract the environmental factors related with eutrophication, and also tried to develop the process technique and the radiance feature of reflectance related with eutrophication. The results were summarized as follows: First, the spectrum of sun's rays which reaches the surface of the earth was consistent with visible rays bands of 0.4${\mu}{\textrm}{m}$~0.7${\mu}{\textrm}{m}$ and about 50% of total quantity of radiation were there. And at around 0.5${\mu}{\textrm}{m}$ of green spectral band in visible rays bands, the spectrum was highest. Second, as a result of the radiance reflectance Chlorophyll-a represented high spectral reflectance mainly around 0.52${\mu}{\textrm}{m}$ of green spectral band, and suspended sediments and turbidity represented high spectral reflectance at 0.8${\mu}{\textrm}{m}$ and at 0.57${\mu}{\textrm}{m}$ each. Third, as a result of the water quality analysis by using Airborne MSS, Chlorophyll-a could have a distribution chart when carried out ratio of B3 and BS to B7. And Band 7 was useful for making the distribution chart of suspended sediments. And when we carried out PCA, suspended sediments and turbidity had distributions at PC 1 , PC 4 each similarly to ground truth data. Above results can be changed according to the change of season and time. Therefore, in order to analyze more exactly the environmental factors of water quality by using LRC data, we need to investigate constantly the ground truth data and the radiance feature of reflectance of water body. Afterward in this study, we will constantly analyze the radiance feature of the surface of water in water body by measuring the on-the-spot radiance reflectance and using low resolution satellite image(SeaWiFs). Besides, we will gather the data of water quality analysis in water body and analyze the pattern of water pollution.