• Title/Summary/Keyword: 적조피해

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Red Tide Monitoring for Fish Farm Using Long-Endurance UAV (장기 체공형 무인기를 이용한 양식장에 대한 적조 모니터링)

  • Song, Moon-Soo;Yun, Hong-Sik;Kim, Gwang-Bae;Kim, Tae-Woo
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2016.11a
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    • pp.426-427
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    • 2016
  • 본 논문에서는 Unmaned Aerial Vehicle(UAV)를 이용하여 양식어장에 유입될 수 있는 적조 모니터링에 대한 연구를 실시하였다. 적조는 한반도 주변 해역을 포함한 전 세계 연안 지역에서 물고기의 집단 폐사, 해안구조물에 대한 물리적 손상등과 같이 사회 경제적인 피해를 야기 시켜왔고, 최근 해수면 온도상승과 같은 기후 변화에 의한 영향으로 증가되고 있는 실정이다. 특히 남해안과 같이 생활하수가 다량 유입되고 저층에 퇴적된 영양물질이 용출되는 곳에서 상습적으로 발생한다. 1995년에 발생한 코클로디니움에 의한 적조는 764억원의 기록적인 피해를 입히면서, 적조에 대한 신속한 대응과 효과적인 방제작업의 필요성이 대두되었다. 이렇게 양식어장 운영에 다양한 문제가 발생이 된 후 대응하는 것보다 모니터링을 통해 사전에 유입을 차단하고 대처하는 연구가 필요하고 판단된다. 원격탐사를 활용한 적조 탐지 및 모니터링 연구는 UAV에서 취득한 RGB color 영상을 통한 적조 추출 및 분석, 시계열 분석을 위한 영상자료 수집, 현장관측 자료와 위성영상에서 추출한 클로로필 농도 비료글 통해 이루어 졌다. 또한 매년 발생하는 적조생물에 관한 속성정보를 통해 적조발생지역에 대한 적조생물종과 국내 연안에서 발생한 적조의 발생 범위 등의 정보를 지리정보기반에 의한 공간분석을 실시하였다.

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A Review on Red-tides and Phytoplankton Toxins in the Coastal Waters of Korea (한국연안에 있어서 적조발생과 식물플랑크톤 독성에 관한 개관)

  • 이진환
    • Korean Journal of Environmental Biology
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    • v.17 no.3
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    • pp.217-232
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    • 1999
  • The author made a special review on/red-tides from the following points: definition, terms, yearly progress of researches, causative organisms, searching the causes, toxins, a loss of lives, damages of aquatic products, reducing aquacultural damages and removal efficiency. Red-tides in Korea were caused by diatoms in the early 1960’s, in the end of 1970’s it was caused by non-toxic dinoflagellates when marine pollutions were growing more and more serious. In the end of 1980’s, red-tides were caused by toxic dinoflagellates. Red-tide was only found in selected areas at first, but recently large-scaled red-tides are frequently found in the southern coastal waters of Korea, causing huge losses of marine life. A plan is greatly needed to reduce the damaging red-tides, and removal systems need to be developed.

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Red Tide Prediction using Neural Network and SVM (신경망과 SVM을 이용한 적조 발생 예측)

  • Park, Sun;Kim, Kyung-Jun;Lee, Jin-Seok;Lee, Seong-Ro
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.5
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    • pp.39-45
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    • 2011
  • There have been many studies on red tide because of increasing of damage to sea farming by a red tide blooms of harmful algae. The studies of red tide have mostly focused chemical properties and investigation of biological cause. If we can predict the occurrence of red tide, we will be able to minimize the damage of red tide. However, internal study of prediction of red tide blooms is only classification method that is still insufficient for red tide blooms forecast. In this paper, we proposed the red tide blooms prediction method using neural network and SVM.

Analysis of Temporal and Spatial Red Tide Change in the South Sea of Korea Using the GOCI Images of COMS (천리안 위성 GOCI 영상을 이용한 남해안의 시공간적 적조변화 분석)

  • Kim, Dong Kyoo;Yoo, Hwan Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.22 no.3
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    • pp.129-136
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    • 2014
  • This study deals with red tide detection by using the remote sensing imagery from the Geostationary Ocean Color Imager (GOCI), the world's first geostationary orbit satellite, around the southern coast of Korea where the most severe red tide occurred recently. The red tide zone was determined by the available data selection from the GOCI imagery during the period of red tide occurrence and also the severe red tide zone was detected through the spatial analysis by temporal change out of the red tide zone. This study results showed that the coast in the vicinity of the Hansan and Yokji in Tongyeong-si was classified into the severe red tide zone, and that the red tide was likely to spread from the coast of Hansan and Yokji to the one of Sanyang-eub. In addition, the comparative analysis between the area of red tide occurrence, the prevention activities of Gyeongsangnam-do provincial government and the amount of the damage cost over time showed close correlation among them. It is still early to conclude that the study is showing the severe red tide zone and the spread path exactly due to various factors for red tide occurrence and activities. In order to improve the reliability of the results, the more data analysis is required.

Seismic response of Unreinforced Masonry Residential Building (비보강 주거용 조적조의 지진거동 실험)

  • 김재관
    • Proceedings of the Earthquake Engineering Society of Korea Conference
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    • 1999.10a
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    • pp.383-387
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    • 1999
  • 우리나라에 있는 대부분의 주거용 조적조 건물의 내진설계가 되어 있지 않은 비보강 조적조이다, 비보강 조적조 건물에 막대한 피해를 준 1989년의 Loma Prieta 지진을 통해 알수 있듯이 이들에 대한 실험적이고도 이론적인 연구가 필요하다. 우리나라의 비보강 조적조의 지진거동을 알아보기 위해 1/3로 축소된 전형적인 2층 조적조 모델을 제작하였다. 진동대위에서 지진모의 실험을 수행하였다 실험결과 1층에서의 전단파괴가 지배적으로 나타났다 하지만 예상했던 것 보다는 비보강 조적조 모델의 내력이 큼을 확인할 수 있었다.

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The Temporal and Spatial Distribution Analysis of Red Tide using GIS (GIS를 이용한 적조의 시-공간적 분포 분석)

  • Jeong Jong-chul
    • Spatial Information Research
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    • v.13 no.3 s.34
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    • pp.253-260
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    • 2005
  • The aim of this study is to analyze the temporal and spatial distribution aspects of red tide using GIS techniques. The damage caused by red tide appears various aspects according to the species, concentration and spatial distribution of red tide plankton. Therefore, in order to prevent the damage of red tide it is important to understand the distribution characteristics of red tide by each species according to time and space. In this perspective, we analyzed the beginning outbreak area, spatial occurrence frequency and spatial migration of red tide. The spatial data used by this study was constructed by digitizing the red tide quick report and coupled with various attributes such as species, concentration and water temperature for construction of red tide database. We used various spatial analysis methods such as union, intersect, tracking, buffer and spatial interpolation for analyzing temporal and spatial characteristics of red tide. From the result of these spatial analyses, we could get the spatial information on the temporal and spatial distribution characteristics of red tide at the Southern Sea.

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초고주파 라디오미터 센서를 이용한 적조 관측 실험

  • 김용훈;김성현;박혁;최준호;이호진;최승운;최재연;서승원
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.449-454
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    • 2004
  • 심각한 환경문제인 적조 피해를 줄이기 위해서 효과적인 모니터링 기술이 절실히 요구되고 있다. 본 연구에서는 초고주파 라디오미터 센서를 이용한 효과적인 적조 모니터링에 대한 가능성을 조사하였다. 초고주파 라디오미터를 이용해 관측되는 밝기 온도의 차이로 적조 해수를 모니터링 할 수 있다는 아이디어에 기반하여 연구를 수행하였다. 본문에서는 이론적인 배경과 가능성 확인을 위한 실험과정, 결과가 서술되어 있다 실제 해양에서의 측정 실험에서 적조지역의 밝기 온도가 청정지역의 밝기 온도보다 높게 측정되었다. 결론으로, 본 연구를 통하여 초고주파 라디오미터를 이용한 적조 모니터링이 가능함을 확인하였다.

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Seismic Capacity Strengthened by GFS of Masonry Buildings with Earthquake Damage (지진피해를 입은 조적조 건축물의 유리섬유보강에 따른 내진성능)

  • Kwon, Ki-Hyuk;Choi, Sung-Mo;Lee, Soo-Cheul;Cho, Sang-Min
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.8 no.1
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    • pp.231-237
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    • 2004
  • Most of the masonry buildings have many structural defects under an earthquake load due to the small tensile force and ductility. In the foreign countries there are many the reinforcing methods of masonry buildings, but the glass fiber sheet reinforcements must be used due to various conditions in Korea. The purpose of this paper is to estimate the seismic capacity of masonry buildings damaged by earthquake and reinforced by Glass Fiber Sheet. On the basis of test results, the maximum base shear force and deformation of the masonry building with GFS were remarkably increased. From the comparison by existing strength equations and test data, the new strength equation of reinforced masonry buildings with GFS was developed.

Enhancing of Red Tide Blooms Prediction using Ensemble Train (앙상블 학습을 이용한 적조 발생 예측의 성능향상)

  • Park, Sun;Jeong, Min-A;Lee, Seong-Ro
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.1
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    • pp.41-48
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    • 2012
  • Red tide is a natural phenomenon temporary blooming harmful algal with changing sea color from normal to red, which fish and shellfish die en masse. It also give a bad influence to coastal environment and sea ecosystem. The damage of sea farming by a red tide has been occurred each year which it cost much to prevent disasters of red tide blooms. Red tide damage and prevention cost of red tide disasters can be minimized by means of prediction of red tide blooms. In this paper, we proposed the red tide blooms prediction method using ensemble train. The proposed method use the bagging and boosting ensemble train methods for enhancing red tide prediction and forecast. The experimental results demonstrate that the proposed method achieves a better red tide prediction performance than other single classifiers.