• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.445-449
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• 2005

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

• 환경영향평가
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• 제10권1호
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• pp.1-8
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• 2001

Detection of red tides by satellite remote sensing can be done either by detecting enhanced level of chlorophyll pigment or by detecting changes in the spectral composition of pixels. Using chlorophyll concentration, however, is not effective currently due to the facts: 1) Chlorophyll-a is a universal pigment of phytoplankton, and 2) no accurate algorithm for chlorophyll in case 2 water is available yet. Here, red band algorithm, classification and PCA (Principal Component Analysis) techniques were applied for detecting patches of Cochlodinium polykrikoides red tides which occurred in Korean waters in 1995. This dinoflagellate species appears dark red due to the characteristic pigments absorbing lights in the blue and green wavelength most effectively. In the satellite image, the brightness of red tide pixels in all the three visible bands were low making the detection difficult. Red band algorithm is not good for detecting the red tide because of reflectance of suspended sediments. For supervised classification, selecting training area was difficult, while unsupervised classification was not effective in delineating the patches from surrounding pixels. On the other hand, PCA gave a good qualitative discrimination on the distribution compared with actual observation.

• 한국해양공학회지
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• 제24권2호
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• pp.53-56
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• 2010

Oil spills and red tide can be very damaging to the environment and fishery farming. These catastrophic accidents must be detected as quickly as possible. In this paper, we report the results of applying the wavelet transform to SAR or marine radar images for the detection of the boundaries of an oil spill or red tide. The application of the wavelet transform to these phenomena looks quite promising in detecting the boundaries of oil spills and red tide areas.

• 대한원격탐사학회지
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• 제32권2호
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• pp.87-96
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• 2016

매년 여름 우리나라 양식업에 피해를 입히는 적조를 탐지하기 위한 연구는 대부분 인공위성을 이용하였으나 양식장에 대한 정보는 인공위성으로 산출하기에는 한계를 가진다. 따라서 본 연구에서는 무인항공기를 이용한 연안촬영과 그 산출물을 이용하여 적조를 탐지하는 기법을 제시하였다. 그 결과 높은 해상도를 가진 무인항공영상을 획득 할 수 있었으며 색상을 이용한 무감독 분류와 가시광영역의 세 가지 분광밴드를 이용한 단순 알고리즘을 이용하여 적조를 탐지하였다. 기존의 천연색 영상에 비하여 시각적으로 명확한 해수색의 구분이 가능하였으며 적조의 해수면 분포를 확인할 수 있었다. 이와 같은 방법은 양식장이 설치되어 있는 연안에서 더욱 정확한 적조의 분포 상황을 모니터링 할 수 있을 것으로 판단된다.

• 대한원격탐사학회지
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• 제24권4호
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• pp.325-331
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• 2008

본 연구는 MODIS에서 제공하는 클로로필 정보를 기반으로 하여 2단계 필터링을 통해 우리나라 동해, 남해 연안에 대규모로 발생했던 Cochlodinium polykrikoides 적조를 탐지하는 알고리즘을 제시한다. 일반적으로 적조 탐지 연구들은 클로로필과 적조 발생의 상관성을 이용하여 클로로필의 농도가 높은 해역을 적조 발생 해역으로 탐지한다. 하지만 이 방법의 문제점은 적조가 발생하지 않은 해역을 적조 발생 해역으로 탐지함으로써 포함오차(Commission error)를 발생시킨다는 것이다. 따라서 본 연구에서는 이러한 문제점을 극복하기 위해 MODIS에서 제공하는 클로로필 정보를 바탕으로 적조 발생 해역을 추출하고, 2단계 필터 링 과정을 적용함으로써 진해, 여수, 남해도 부근 해역에서 발생한 포함오차를 제거하였으며, 그 결과를 국립수산과학원의 적조속보자료와 함께 시각적 정량적으로 평가하여 본 연구에서 제안한 알고리즘의 효용성을 검증하였다.

• 대한원격탐사학회지
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• 제38권6_1호
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• pp.1541-1555
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• 2022

적조는 식물성 플랑크톤의 번성현상으로써, 해양생태 및 양식업에 유해한 영향을 끼칠 수 있는 현상이다. 다양한 광학원격센서를 이용한 적조탐지 연구가 수행되어왔지만, 기개발된 적조 탐지 알고리즘들은 수심이 얕고, 부유퇴적물이 많은 연안해역에 적용하기에는 한계가 있다. 적조 해수의 광학적특성에 대한 이해를 높이기 위해서 원격탐사반사도 및 수중구성성분에 대한 분석의 중요성이 높아지고 있다. 본 연구는 선박현장조사를 통하여 적조해수의 광학변수(원격탐사반사도)와 수질변수(Chl-a_(Spec), 총부유물농도, a_ph, a_d, 종 동정, Chl-a_(HPLC))를 취득하고 광학변수와 수질변수간의 관계를 분석하였다. 메조디니움과 코클로디니움 두가지 적조 종 및 엽록소농도에 따른 원격탐사반사도와 식물성플랑크톤 흡광계수에 대한 분석을 수행하였고, 원격탐사반사도의 특정 파장대를 이용한 적조 엽록소농도의 추정 가능성을 제시하였다. 분석 결과, 적조의 엽록소농도와 식물성플랑크톤 흡광계수는 결정계수 0.9의 상관도를 나타냈으며, RE_diff를 이용한 기법이 B-G ratio를 이용한 기법보다 적조농도를 더욱 정확하게 추정하는 것으로 나타났다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.131-134
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• 2007

In this paper, we evaluate a red tide detection possibility of GOCI(Geostationary Ocean Color Imager) which will be launched in 2008. To detect red tide, we use a similar wavelength range of MODIS normalized water-leaving radiance data instead of GOCI data. Supposed to GOCI, red tide detection algorithm is based on MRI(MODIS Red tide Index) and use 667nm band to filter turbid water. The algorithm's effectiveness is verified by detecting large Cochlodinium polykrikoides red tide event that was appeared in Korean coastal waters. The evaluation was done by comparing the result with the update data provided by the NFRDI.

• 대한원격탐사학회지
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• 제29권3호
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• pp.331-335
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• 2013

This study detected red tide areas using the existing Moderate-Resolution Imaging Spectroradiometer(MODIS) and Geostationary Ocean Color Imager(GOCI), and then compared the results between results of two sensors. The coasts of Jeollanam-do in the South Sea of Korea were set as the study area based on the red tide data which occurred on Aug. 26th, 2012. This study compared the results of sensors to detect red tides by using a satellite. In the results of analyzing MODIS by limiting it as chlorophyll concentration and the sea surface temperature which is considered to have red tides by the existing researches, it was possible to delete considerable amount of errors compared to the case of detecting red tides by using only chlorophyll while still there were differences from the range of red tides actually observed. In the results of GOCI by using empirical algorithm for detecting red tides, currently used by Korea Institute of Ocean Science & Technology(KIOST), it was possible to obtain more detailed results than MODIS. However, there was an area misjudged as red tides due to the influence of clouds. Also both MODIS and GOCI extracted red tides were not actually occurring, which might be because they were not able to perfectly distinguish red tides from turbid water in coastal areas with high turbidity.

• 대한원격탐사학회지
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• 제15권4호
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• pp.321-327
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• 1999

As an example of many possible applications of OSMI data, we present a method to detect red tides. In Korean waters, red tides usually occur in the South Sea where the turbidity is usually high due to strong tidal mixing in the shallow sea. The conventional case 1 chlorophyll algorithm cannot be applied since it cannot distinguish chlorophyll from SS (suspended sediments). In October 1998, a red tide outbreak occurred off the coast of KunSan. We analyzed the SeaWiFS data of the outbreak. The standard SeaWiFS chlorophyll algorithm OC-2 was poor in identifying the red tides. However, comparison of spectra of normalized water-leaving radiance indicates that red tide pixels can be distinguished from sediment-laden pixels. Channel 443 and 555 were effective in showing the spectral characteristics. We suggest K490 algorithm as an example in summarizing the information of the spectra and thereby in distinguishing the red tide pixels. Further development is desirable.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.381-385
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• 1999

As an example of many possible applications of OSMI data, we present a method to detect red tides. In Korean waters, red tides usually occur in the South Sea where the turbidity is usually high due to strong tidal mixing in the shallow sea. The conventional case 1 chlorophyll algorithm cannot be applied since it cannot distinguish chlorophyll from SS (suspended sediments). In October 1998, a red tide outbreak occurred off the coast of Kunsan. We analyzed the SeaWiFS data of the outbreak. The standard SeaWiFS chlorophyll algorithm OC2 was poor in identifying the red tides. However, comparison of spectra of normalized water-leaving radiance indicates that red tide pixels can be distinguished from sediment-laden pixels. Channel 443 and 555 were effective in showing the spectral characteristics. We suggest K490 algorithm as an example in summarizing the information of the spectra and thereby in distinguishing the red tide pixels. Further development is desirable.