• Title/Summary/Keyword: 해양적조

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Development of an Automatic Monitoring System for Ultrasound Signals Using Artificial Intelligence and Convolutional Neural Networks (인공지능을 활용한 초음파 신호와 합성곱 신경망 기반 자동 적조 모니터링 시스템)

  • Daehun Kim;Hyeon-Ju Jeon;O-Joun Lee;Hae Gyun Lim
    • Annual Conference of KIPS
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    • 2023.11a
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    • pp.662-664
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    • 2023

  • 해양 식물플랑크톤의 성장은 유해적인 적조를 유발할 수 있으며, 이는 여러 국가의 생태계에 피해를 주는 상황이다. 적조를 모니터링하는 것은 식물플랑크톤 미생물의 증가를 예방하고 통제하기 위해 중요하다. 그러나 현재의 적조 모니터링 기술은 날씨, 시간 제약 및 실시간 모니터링에 대한 어려움으로 인해 측정 정확도에 영향을 미치는 한계가 있다. 본 연구는 특히 적조 발생을 감지하기 위한 목적으로 개발된 자동 실시간 모니터링 시스템의 성공적인 개발을 보여준다. 개발한 시스템은 음향 반사파 데이터 처리를 통해 합성곱 신경망(Convolutional neural networks, CNN)을 활용하여 식물플랑크톤 농도를 정확하게 구별할 수 있다. 특히, 이 CNN 모델은 음향 신호의 변환된 주파수 스펙트럼과 Cochlodinium polykrikoides (C. polykrikoides)의 농도 간의 상관 관계를 수립하는 데 뛰어난 효과를 나타냈다. 이 CNN 은 C. polykrikoides 를 감지하는 데 0.90 의 정확도를 보여준다. 이러한 모니터링과 CNN 분류의 활용은 실시간 측정의 중요한 잠재력을 보여주며, 추가적인 절차가 필요 없는 자동 모니터링 시스템을 구축할 수 있을 것으로 예상된다.

  • https://doi.org/10.3745/PKIPS.y2023m11a.662 인용 PDF

Monitoring Red Tide in South Sea of Korea (SSK) Using the Geostationary Ocean Color Imager (GOCI) (천리안 해색위성 GOCI를 이용한 대한민국 남해안 적조 모니터링)

  • Son, Young Baek;Kang, Yoon Hyang;Ryu, Joo Hyung
    • Korean Journal of Remote Sensing
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    • v.28 no.5
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    • pp.531-548
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    • 2012

  • To identify Cochlodinium polykrikoides red tide from non-red tide water (satellite high chlorophyll waters) in the South Sea of Korea (SSK), we improved a spectral classification method proposed by Son et al.(2011) for the world first Geostationary Ocean Color Imager (GOCI). C. polykrikoides blooms and non-red tide waters were classified based on four different criteria. The first step revealed that the radiance peaks of potential red tide water occurred at 555 and 680 nm (fluorescence peak). The second step separated optically different waters that were influenced by relatively low and high contributions of colored dissolved organic matter (CDOM) (including detritus) to chlorophyll. The third and fourth steps discriminated red tide water from non-red tide water based on the blue-to-green ratio, respectively. After applying the red tide classification, the spectral response of C. polykrikoides red tide water, which is influenced by pigment concentration as well as CDOM (detritus), showed different slopes for the blue and green bands (lower slope at blue bands and higher slope at green bands). The opposite result was found for non-red tide water. This modified spectral classification method for GOCI led to increase user accuracy for C. polykrikoides and non-red tide blooms and provided a more reliable and robust identification of red tides over a wide range of oceanic environments than was possible using chlorophyll a concentration, or proposed red tide detection algorithms. Maps of C. polykrikoides red tide in SSK outlined patches of red tide covering the area near Naro-do and Tongyeong during the end of July and early of August, 2012 and extending into from Wan-do and Geoje-do during the middle of August, 2012.

  • https://doi.org/10.7780/kjrs.2012.28.5.6 인용 PDF KSCI

Statistical analyses on the relationships between red tide formation and meteorological factors in the Korean Coastal Waters and Satellite monitoring for red tide (한국 연안의 적조형성과 기상용인간의 상관성에 대한 통계학적 해석 및 위성에 의한 적조모니터링)

  • Yoon Hong-Joo;Lee Moon-Ok;Ryu Cheong-Ro
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2004.05a
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    • pp.279-284
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    • 2004

  • Red tide(harmful algae) in the Korean Coastal Waters has a given a great damage to the fishery every year. However, the aim of our study understands the influence of meteorological factors (air and water tempaerature, precipitation, sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations).

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