• Title/Summary/Keyword: 해색

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A Comparative Study on Machine Learning Models for Red Tide Detection (적조 탐지를 위한 기계학습 모델 비교 연구)

  • Park, Mi-So;Kim, Na-Kyeong;Kim, Bo-Ram;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1363-1372
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    • 2021
  • Red tide, defined as the major reproduction of harmful birds, has the characteristics of being generated and diffused in a wide area. This has limitations in detection only with the existing investigation method. Therefore, in this study, red tide was detected using a remote sensing technique. In addition, it was intended to increase the accuracy of detection by using optical characteristics, not just the concentration of chlorophyll. Red tide mainly occurs on the southern coast where sea signals are complex, and the main red tide control species on the southern coast is Cochlodinium polykirkoides. Therefore, it was intended to secure objectivity by reflecting features that could not be found depending on the researcher's observation and experience, not limited to visual judgment using machine learning techniques. In this study, support background machines and random forest were used among machine learning models, and as a result of calculating accuracy as performance evaluation indicators of the two models, the accuracy was 85.7% and 80.2%, respectively.

Introduction on the Products and the Quality Management Plans for GOCI-II (천리안 해양위성 2호 산출물 및 품질관리 계획)

  • Lee, Sun-Ju;Lee, Kyeong-Sang;Han, Tae Hyun;Moon, Jeong-Eon;Bae, Sujung;Choi, Jong-kuk
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1245-1257
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    • 2021
  • GOCI-II, succeeding the mission of GOCI, was launched in February 2020 and has been in regular operation since October 2020. Korea Institute of Ocean Science and Technology (KIOST) processes and produces in real time Level-1B and 26 Level-2 outputs, which then are provided by Korea Hydrographic and Oceanographic Agency (KHOA). We introduced current status of regular GOCI-II operation and showed future improvement. Basic GOCI-II products including chlorophyll-a, total suspended materials, and colored dissolved organic matter concentration, are induced by OC4 and YOC algorithms, which were described in detail. For the full disk (FD), imaging schedule was established considering solar zenith angle and sun glint during the in-orbital test, but improved by further considering satellite zenith angle. The number of slots satisfying the condition 'Best Ocean' significantly increased from 15 to 78. GOCI-II calibration requirements were presented based on that by European Space Agency (ESA) and candidate fixed locations for calibrating local observation area were. The quality management of FD uses research ships and overseas bases of KIOST, but it is necessary to establish an international calibration/validation network. These results are expected to enhance the understanding of users for output processing and help establish detailed plans for future quality management tasks.

The GOCI-II Early Mission Ocean Color Products in Comparison with the GOCI Toward the Continuity of Chollian Multi-satellite Ocean Color Data (천리안해양위성 연속자료 구축을 위한 GOCI-II 임무 초기 주요 해색산출물의 GOCI 자료와 비교 분석)

  • Park, Myung-Sook;Jung, Hahn Chul;Lee, Seonju;Ahn, Jae-Hyun;Bae, Sujung;Choi, Jong-Kuk
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1281-1293
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    • 2021
  • The recent launch of the GOCI-II enables South Korea to have the world's first capability in deriving the ocean color data at geostationary satellite orbit for about 20 years. It is necessary to develop a consistent long-term ocean color time-series spanning GOCI to GOCI-II mission and improve the accuracy through validation using in situ data. To assess the GOCI-II's early mission performance, the objective of this study is to compare the GOCI-II Chlorophyll-a concentration (Chl-a), Colored Dissolved Organic Matter (CDOM), and remote sensing reflectances (Rrs) through comparison with the GOCI data. Overall, the distribution of GOCI-II Chl-a corresponds with that of the GOCI over the Yellow Sea, Korea Strait, and the Ulleung Basin. In particular, a smaller RMSE value (0.07) between GOCI and GOCI-II over the summer Ulleung Basin confirms the GOCI-II data's reliability. However, despite the excellent correlation, the GOCI-II tends to overestimate Chl-a than the GOCI over the Yellow Sea and Korea Strait. The similar over-estimation bias of the GOCI-II is also notable in CDOM. Whereas no significant bias or error is found for Rrs at 490 nm and 550 nm (RMSE~0), the underestimation of Rrs at 443 nm contributes to the overestimation of GOCI-II Chl-a and CDOM over the Yellow Sea and the Korea Strait. Also, we show over-estimation of GOCI-II Rrs at 660 nm relative to GOCI to cause a possible bias in Total suspended sediment. In conclusion, this study confirms the initial reliability of the GOCI-II ocean color products, and upcoming update of GOCI-II radiometric calibration will lessen the inconsistency between GOCI and GOCI-II ocean color products.

Sea Water Type Classification Around the Ieodo Ocean Research Station Based On Satellite Optical Spectrum (인공위성 광학 스펙트럼 기반 이어도 해양과학기지 주변 해수의 수형 분류)

  • Lee, Ji-Hyun;Park, Kyung-Ae;Park, Jae-Jin;Lee, Ki-Tack;Byun, Do-Seung;Jeong, Kwang-Yeong;Oh, Hyun-Ju
    • Journal of the Korean earth science society
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    • v.43 no.5
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    • pp.591-603
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    • 2022
  • The color and optical properties of seawater are determined by the interaction between dissolved organic and inorganic substances and plankton contained in it. The Ieodo - Ocean Research Institute (I-ORS), located in the East China Sea, is affected by the low salinity of the Yangtze River in the west and the Tsushima Warm Current in the south. Thus, it is a suitable site for analyzing the fluctuations in circulation and optical properties around the Korean Peninsula. In this study, seawater surrounding the I-ORS was classified according to its optical characteristics using the satellite remote reflectance observed with Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua and National Aeronautics and Space Administration (NASA) bio-Optical Marine Algorithm Dataset (NOMAD) from January 2016 to December 2020. Additionally, the variation characteristics of optical water types (OWTs) from different seasons were presented. A total of 59,532 satellite match-up data (d ≤ 10 km) collected from seawater surrounding the I-ORS were classified into 23 types using the spectral angle mapper. The OWTs appearing in relatively clear waters surrounding the I-ORS were observed to be greater than 50% of the total. The maximum OWTs frequency in summer and winter was opposite according to season. In particular, the OWTs corresponding to optically clear seawater were primarily present in the summer. However, the same OWTs were lower than overall 1% rate in winter. Considering the OWTs fluctuations in the East China Sea, the I-ORS is inferred to be located in the transition zone of seawater. This study contributes in understanding the optical characteristics of seawater and improving the accuracy of satellite ocean color variables.

Estimating Photosynthetically Available Radiation from Geostationary Ocean Color Imager (GOCI) Data (정지궤도 해양관측위성 (GOCI) 자료를 이용한 광합성 유효광량 추정)

  • Kim, Jihye;Yang, Hyun;Choi, Jong-Kuk;Moon, Jeong-Eon;Frouin, Robert
    • Korean Journal of Remote Sensing
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    • v.32 no.3
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    • pp.253-262
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    • 2016
  • Here, we estimated daily Photosynthetically Available Radiation (PAR) from Geostationary Ocean Colour Imager (GOCI) and compared it with daily PAR derived from polar-orbiting MODIS images. GOCI-based PAR was also validated with in-situ measurements from ocean research station, Socheongcho. GOCI PAR showed similar patterns with in-situ measurements for both the clear-sky and cloudy day, whereas MODIS PAR showed irregular patterns at cloudy conditions in some areas where PAR could not be derived due to the clouds of sunglint. GOCI PAR had shown a constant difference with the in-situ measurements, which was corrected using the in-situ measurements obtained on the days of clear-sky conditions at Socheongcho station. After the corrections, GOCI PAR showed a good agreement excepting on the days with so thick cloud that the sensor was optically saturated. This study revealed that GOCI can estimate effectively the daily PAR with its advantages of acquiring data more frequently, eight times a day at an hourly interval in daytime, than other polar orbit ocean colour satellites, which can reduce the uncertainties induced by the existence and movement of the cloud and insufficient images to map the daily PAR at the seas around Korean peninsula.

Cloud Detection Using HIMAWARI-8/AHI Based Reflectance Spectral Library Over Ocean (Himawari-8/AHI 기반 반사도 분광 라이브러리를 이용한 해양 구름 탐지)

  • Kwon, Chaeyoung;Seo, Minji;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.33 no.5_1
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    • pp.599-605
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    • 2017
  • Accurate cloud discrimination in satellite images strongly affects accuracy of remotely sensed parameter produced using it. Especially, cloud contaminated pixel over ocean is one of the major error factors such as Sea Surface Temperature (SST), ocean color, and chlorophyll-a retrievals,so accurate cloud detection is essential process and it can lead to understand ocean circulation. However, static threshold method using real-time algorithm such as Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Himawari Imager (AHI) can't fully explained reflectance variability over ocean as a function of relative positions between the sun - sea surface - satellite. In this paper, we assembled a reflectance spectral library as a function of Solar Zenith Angle (SZA) and Viewing Zenith Angle (VZA) from ocean surface reflectance with clear sky condition of Advanced Himawari Imager (AHI) identified by NOAA's cloud products and spectral library is used for applying the Dynamic Time Warping (DTW) to detect cloud pixels. We compared qualitatively between AHI cloud property and our results and it showed that AHI cloud property had general tendency toward overestimation and wrongly detected clear as unknown at high SZA. We validated by visual inspection with coincident imagery and it is generally appropriate.

Characteristics of Ocean Environment Before and After Coastal Upwelling in the Southeastern Part of Korean Peninsula Using an In-situ and Multi-Satellite Data (다중위성 및 현장관측을 이용한 동해남부 연안용승 발생 전후의 해양환경 특성)

  • Kim, Sang-Woo;Go, Woo-Jin;Kim, Seong-Soo;Jeong, Hee-Dong;Yamada, Keiko
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.16 no.4
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    • pp.345-352
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    • 2010
  • The objective of this paper is to explore the short-term variability of water temperature and chlorophyll a (Chl-a) derived from in-situ and satellite data (NOAA, Sea WiFS and QuikScat) in the upwelling region of the southeastern part of Korean Peninsula in June and August, 2007. Particularly we focused on the spatial variability of sea surface temperature(SST) and Chl-a in the East Korean Warm Current region. In the results of the in-situ data, the peaks of Chl-a in june was shown at a depth of 50m The peaks of Chl-a in August was shown at a depth of 10m at the stations 4 and 5 near the land, and a depth of 30m at the other stations. The Chl-a concentrations in August were also lower than those in june except for station 5. As a result, the peaks of Chl-a in August occurred at a depth of 20~40 m shallower than those of Chl-a in june. This indicates that the nutrient-rich water within the mixed layer depth may be immediately supplied by the coastal upwelling, which is due to the southerly component of wind. The relationship between SST and Chl-a showed a negative correlation, and the high concentration of Chl-a occurred in the cold water area. The southerly wind and the East Korean Warm Current influenced a remarkable offshore movement of the cold water and Chl-a near the coastal area.

Oceanographic Variability in Yellow Sea using Satellite Data: study on the Relationship of Oceanic Variation in the Offshore Area and Viewpoint of Abnormal Rise in Coastal Seawater Temperature in 2004 (인공위성자료를 이용한 황해의 해황 변동: 2004년 연안해역 이상 수온 상승과 외해 해양 변동의 연관성 연구)

  • Moon, Jeong-Eon;Yang, Chan-Su;Ahn, Yu-Hwan
    • 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.

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An Analysis of the Relationship between Inherent Optical Properties and Ocean Color Algorithms Around the Korean Waters (한반도 주변의 해수 고유광특성과 해색 알고리즘의 관계 분석)

  • Min, Jee-Eun;Ryu, Joo-Hyung;Park, Young-Je
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.473-490
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    • 2015
  • There are diverse sea areas within the coverage of GOCI which is observed around the Korea at one-hour intervals. It includes not only very clear ocean of East Sea, but also extremely turbid waters of the Yangtze River estuary. In this study, we analyzed the different optical characteristics of various sea areas using absorption coefficients of phytoplankton, Suspended Particulate Matter(SPM), Dissolved Organic Matter(DOM). Totally 959 sets of bio-optical and marine environmental data were obtained from 2009 to 2014 around the sea area of Korea. The East Sea, South Sea, East China Sea and offshore part of Yellow Sea showed similar pattern having high levels of contribution of phytoplankton and DOM. On the other hands, the coastal part of Mokpo and Gyeonggi Bay showed opposite pattern having high levels of contribution of SPM and DOM. As a result of the algorithm performance for chlorophyll-a(Chl-a) and SPM, Chl-a is mostly overestimated and SPM is mainly tended to be underestimated. Large amount of errors are induced by the SPM rather than the chl-a and DOM. These errors are primarily founded in the coastal waters having relatively high levels of $a_{SPM}$ contribution of more than 60%.

Development of Suspended Sediment Algorithm for Landsat TM/ETM+ in Coastal Sea Waters - A Case Study in Saemangeum Area - (Landsat TM/ETM+ 연안 부유퇴적물 알고리즘 개발 - 새만금 주변 해역을 중심으로 -)

  • Min Jee-Eun;Ahn Yu-Hwan;Lee Kyu-Sung;Ryu Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.22 no.2
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    • pp.87-99
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    • 2006
  • The Median Resolution Sensors (MRSs) for land observation such as Landsat-ETM+ and SPOT-HRV are more effective than Ocean Color Sensors (OCSs) for studying of detailed ecological and biogeochemical components of the coastal waters. In this study, we developed suspended sediment algorithm for Landsat TM/ETM+ by considering the spectral response curve of each band. To estimate suspended sediment concentration (SS) from satellite image data, there are two difference types of algorithms, that are derived for enhancing the accuracy of SS from Landsat imagery. Both empirical and remote sensing reflectance model (hereafter referred to as $R_{rs}$ model) are used here. This study tried to compare two algorithm, and verified using in situ SS data. It was found that the empirical SS algorithm using band 2 produced the best result. $R_{rs}$ model-based SS algorithm estimated higher values than empirical SS algorithm. In this study we used $R_{rs}$ model developed by Ahn (2000) focused on the Mediterranean coastal area. That's owing to the difference of oceanic characteristics between Mediterranean and Korean coastal area. In the future we will improve that $R_{rs}$ model for the Korean coastal area, then the result will be advanced.