• Title/Summary/Keyword: satellite salinity

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Detection of low Salinity Water in the Northern East China Sea During Summer using Ocean Color Remote Sensing

  • Suh, Young-Sang;Jang, Lee-Hyun;Lee, Na-Kyung
    • Korean Journal of Remote Sensing
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    • v.20 no.3
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    • pp.153-162
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    • 2004
  • In the summer of 1998-2001, a huge flood occurred in the Yangtze River in the eastern China. Low salinity water less than 28 psu from the river was detected around the southwestern part of the Jeju Island, which is located in the southern part of the Korean Peninsula. We studied how to detect low salinity water from the Yangtze River, that cause a terrible damage to the Korean fisheries. We established a relationships between low salinity at surface, turbid water from the Yangtze River and digital ocean color remotely sensed data of SeaWiFS sensor in the northern East China Sea, in the summer of 1998, 1999, 2000 and 2001. The salinity charts of the northern East China Sea were created by regeneration of the satellite ocean color data using the empirical formula from the relationships between in situ low salinity, in situ measured turbid water with transparency and SeaWiFS ocean color data (normalized water leaving radiance of 490 nm/555 nm).

Satellite data analysis of the China Coastal Waters in the Seas surrounding Jeju Island, Korea

  • Yoon, Hong-Joo
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.344-347
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    • 2006
  • China Coastal Water (CCW) usually appears in the seas surrounding Jeju Island annually (June?October) and is very pronounced in August. The power spectrum density (PSD), sea level anomalies (SLAs), and sea surface temperatures (SSTs) were found to peak annually and semiannually. The peaks at intervals of 80-, 60-, and 43-days are considered to be influenced by CCW and the Kuroshio Current. Generally, low-salinity water appears to the west of Jeju Island from June through October and gradually propagates to the east, where CCW meets the Tsushima Current. Empirical orthogonal function (EOF) analysis of SLAs and SSTs indicated that the variance in SLAs and SSTs was 55.70 and 98.09% in the first mode, respectively. The PSD for the first mode of EOF analysis of SLAs was stronger in the western than in the eastern waters because of the influence of CCW. The PSD for the EOF analysis of SSTs was similar in all areas (the Yangtze Estuary and the waters to the west and east of Jeju Island), with a period of approximately 260 days.

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Modeling of Suspended Solids and Sea Surface Salinity in Hong Kong using Aqua/MODIS Satellite Images

  • Wong, Man-Sing;Lee, Kwon-Ho;Kim, Young-Joon;Nichol, Janet Elizabeth;Li, Zhangqing;Emerson, Nick
    • Korean Journal of Remote Sensing
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    • v.23 no.3
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    • pp.161-169
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    • 2007
  • A study was conducted in the Hong Kong with the aim of deriving an algorithm for the retrieval of suspended sediment (SS) and sea surface salinity (SSS) concentrations from Aqua/MODIS level 1B reflectance data with 250m and 500m spatial resolutions. 'In-situ' measurements of SS and SSS were also compared with coincident MODIS spectral reflectance measurements over the ocean surface. This is the first study of SSS modeling in Southeast Asia using earth observation satellite images. Three analysis techniques such as multiple regression, linear regression, and principal component analysis (PCA) were performed on the MODIS data and the 'in-situ' measurement datasets of the SS and SSS. Correlation coefficients by each analysis method shows that the best correlation results are multiple regression from the 500m spatial resolution MODIS images, $R^2$= 0.82 for SS and $R^2$ = 0.81 for SSS. The Root Mean Square Error (RMSE) between satellite and 'in-situ' data are 0.92mg/L for SS and 1.63psu for SSS, respectively. These suggest that 500m spatial resolution MODIS data are suitable for water quality modeling in the study area. Furthermore, the application of these models to MODIS images of the Hong Kong and Pearl River Delta (PRO) Region are able to accurately reproduce the spatial distribution map of the high turbidity with realistic SS concentrations.

Improvement of the accuracy of XBT based underwater sound speed using the unmanned maritime system and satellite remote sensing data in the Yellow Sea (해양무인체계와 위성 원격탐사 자료를 이용한 XBT 기반의 황해 수중음속 정확도 향상 방안)

  • Kil, Bum-Jun
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.6
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    • pp.621-629
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    • 2019
  • A logical measure is suggested to estimate an accurate Sound Speed Profile (SSP) for the unusual variation of salinity in the Yellow Sea. Based on National Aeronautics and Space Administration (NASA)'s Aqua and Soil Moisture Active Passive (SMAP) satellite data, this measure identifies the area of temperature inversion effect and expansion of low salinity (<30.5 psu) water. Subsequently, on the area, the Conductivity, Temperature, and Depth (CTD) mounted unmanned maritime system estimates accurate SSP. In order to carry out this measure conveniently, a flow chart is demonstrated in this research. By using this measure which finds the high variational salinity area, the inaccuracy issue for calculating SSP from Expandable Bathy Thermograph (XBT) is expected to be solved.

Estimation of potential area for red tide occurrence in the Korean coasts by Marine GIS

  • Yoon, Hong-Joo;Whang, Wha-Jeung
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.876-878
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    • 2003
  • It was studied on the choice of potential area for red tide occurrence from oceanographic factors. Oceanographic factors of favorable marine environmental conditions for the red tide formation included warm water temperature, low salinity, high suspended solid, low phosphorus, low nitrogen. It was founded the potential areas for red tide occurrence in August 2000 by GIS conception: Yeosu~Dolsan coast, Gamak bay, Namhae coast, Marado coast, Goheung coast, Deukryang bay, respectively.

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Influence Analysis of China Coastal Water in the Seas Surrounding Jeju Island using Satellite Data and Empirical Orthogonal Function Analysis (위성자료와 경험직교함수를 이용한 제주도 주변해역의 중국대륙연안수 영향 연구)

  • Yoon Hong-Joo;Cho Han-Keun;Ahn Yu-Hwan
    • Korean Journal of Remote Sensing
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    • v.21 no.6
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    • pp.469-482
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    • 2005
  • China Coastal Waters (CCW) usually appears in the seas surrounding Jeju Island annually(June to October) and is very pronounced in August. Generally, low-salinity water appears to the western seas of Jeju Island from June through October and gradually propagates to the eastern seas, where CCW meets the Tsushima Current. Empirical orthogonal function (EOF) analysis of SLAs and SSTs indicated that the variance in SLAs and SSTs was $95.01\%$(the first mode to third mode) and $98.09\%$(the first mode), respectively. The PSD of the western waters for the first mode of EOF analysis of SLAs was stronger than that of the eastern waters because of the influence of CCW. The PSD for the EOF analysis of SSTs was similar in all areas (the Yangtze Estuary and the seas to the west and east of Jeju Island), with a period of approximately 260 days.

Calibration and validation of the level 2 data of the Korean OSMI ocean color satellite

  • Suh, Y.S.;Jang, L.H.;Lee, N.K.;Lim, H.S.;Kim, Y.S.;Ahn, Y.H.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.703-705
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    • 2003
  • A comparison was made between the chlorophyll a and suspended solid (SS) retrievals from OSMI and SeaWiFS sensor to chlorophyll a and SS values determined with the standard method during the NFRDI's research cruises. The percentage of organic and inorganic materials from the SS was calculated to study the contribution of turbid water in the northern part of the East China Sea. The open sea waters in the Kuroshio regions of the East China Sea showed relatively higher concentration of volatile SS. However, towards the northwestern part of the East China Sea, the situation became much more optically different with the non-volatile SS from the Yangtze river and the sea bottom sources in the sea in winter and spring seasons. Furthermore, in order to indirectly detect low salinity water with high turbidity, which related to the Yangtze river using remote sensed data from the satellites, a comparison between the results of the band ratio(nLw 490nm/nLw 555nm) of SeaWiFS (OSMI) and the distribution of low salinity around the Jeju Island was presented.

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Thermohaline Structure of the Shelf Front in the Korea Strait in Early Winter (초겨울 大韓海峽에서 形成되는 淺海前線의 構造)

  • Lee, Jae Chul;Na, Jung Yul;Chang, Sun-Duck
    • 한국해양학회지
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    • v.19 no.1
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    • pp.56-67
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    • 1984
  • Mesoscale thermohaline structures of the meandering front in the Korea Strait during November 1976, 1980 and 1982 are studied by means of closely spaced oceanographic observations and the satellite infrared images. Strong thermal and salinity fronts coincide each other and show a wavelike meander motion with wavelengths of 40-60km and amplitudes of, 15-20km. Salinity minimum band of less than 33.0 is found along the onshore edge of the front. Width of the frontal zone corresponds approximately to the internal radius of deformation (R=5-10km) and the slope of density interface is confined to about 2R. A series of satellite infrared images with the interval of 4-5 days show a noticeable growth of frontal meander over the flat shelf west of the Korea Strait. Possible mechanisms of frontal meander and its growth are discussed.

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Estimation of High Resolution Sea Surface Salinity Using Multi Satellite Data and Machine Learning (다종 위성자료와 기계학습을 이용한 고해상도 표층 염분 추정)

  • Sung, Taejun;Sim, Seongmun;Jang, Eunna;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.38 no.5_2
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    • pp.747-763
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    • 2022
  • Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.