• Title/Summary/Keyword: Case 2 Water

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Examination of Cross-calibration Between OSMI and SeaWiFS: Comparison of Ocean Color Products

  • Kim, Yong-Seung;Lee, Sun-Gu
    • Korean Journal of Remote Sensing
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    • v.19 no.3
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    • pp.201-208
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    • 2003
  • Much effort has been made in the radiometric calibration of the ocean scanning multispectral imager (OSMI) since after the successful launch of KOMPSAT-1 in 1999. A series of calibration coefficients for OSMI detectors were obtained in collaboration with the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary (SIMBIOS) project office. In this study, we ompare the OSMI level-2 products (e.g., chorophyll-a concentration) calculated from the NASA cross-calibration coefficients with the SeaWiFS counterparts. Sample study areas are some of diagonostic data sites recommended by the SIMBIOS working group. Results of this study show that the OSMl-derived chlorophyll-a concentration agrees well with the SeaWiFS counterpart in Case 1 water; however, differences become larger in Case 2 water.

Multi-temporal Remote Sensing Data Analysis using Principal Component Analysis (주성분분석을 이용한 다중시기 원격탐사 자료분석)

  • Jeong, Jong-Chul
    • Journal of the Korean Association of Geographic Information Studies
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    • v.2 no.3
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    • pp.71-80
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    • 1999
  • The aim of the present study is to define and tentatively to interpret the distribution of polluted water released from Lake Sihwa into the Yellow Sea using Landsat TM. Since the region is an extreme Case 2 water, empirical algorithms for detecting concentration of chlorophyll-a and suspended sediments have limitations. This work focuses on the use of multi-temporal Landsat TM data. We applied PCA to detect evolution of spatial feature of polluted water after release from the lake Sihwa. The PCA results were compared with in situ data, such as chlorophyll-a, suspended sediments, Secchi disk depth(SDD), surface temperature, remote sensing reflectance at six channel of SeaWiFS. Also, the in situ remote sensing reflectance obtained by PRR-600(Profiling Reflectance Radiometer) was compared with PCA results of Landsat TM data sets to find good correlation between first Principal Component and Secchi disk depth($R^2$=0.7631), although other variables did not result in such a good correlation. Therefore, Problems in applying PCA techniques to multi-spectral remotely sensed data were also discussed in this paper.

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Characteristics of Chlorophyll a Absorption in Case 2 Water for Using Remote Sensing Data

  • Islam, Monirul;Sado, Kimiteru
    • Proceedings of the KSRS Conference
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    • pp.1-3
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    • 2003
  • In this study, spectroradiometer data were coupled with fluorometer data to find out the best suited bands ratio to monitor the chlorophyll a concentration for inland water. Remote sensing reflectance measurements were used to evaluate the performance of several default ocean color chlorophyll algorithms for SeaWiFS data. This study shows that the chlorophyll a concentration from fluorometer and reflectance from spectroradiometer lies in exploiting the signal provided by the chlorophyll a red absorption peak near 670nm. Two-band ratio based on a ratio of reflectance 670 and 700nm provided a good correlation for a linear model, compare with blue-green two band ratio.

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Water quality observation using Principal Component Analysis

  • Jeong, Jong-Chul;Yoo, Sing-Jae
    • Proceedings of the KSRS Conference
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    • pp.58-63
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    • 1998
  • The aim of the present study is to define and tentatively to interpret the distribution of polluted water released from Lake Sihwa into Yellow Sea using Landsat TM. Since the region is an extreme case 2 water, empirical algorithms for chlorophyll-a and suspended sediments have limitations. This work focuses on the use of multi-temporal Landsat TM. We applied PCA to detect evolution of spatial feature of polluted water after release from the lake. The PCA results were compared with in situ data, such as chlorophyll-a, suspended sediments, Secchi disk depth (SDD), surface temperature, radiance reflectance at six bands. The in situ remote sensing reflectance was analysed with PCA. On the basis of these In situ data we found good correlation between first Principal Component and Secchi disk depth ($R^2$=0.7631), although other variables did not result in such a good correlation. The problems in applying PCA techniques to multi-spectral remote sensed data are also discussed.

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Detection of Red Tide Patches using AVHRR and Landsat TM data (AVHRR과 Landsat TM 자료를 이용한 적조 패취 관측)

  • Jeong, Jong-Chul
    • Journal of Environmental Impact Assessment
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    • v.10 no.1
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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.

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Comparison of Bio-Optical Properties of the Yellow Sea and the East Sea using SeaWiFS Data (SeaWiFS 자료를 이용한 황해와 동해의 생물광학 특성 비교)

  • Jeong, Jong-Chul
    • Journal of the Korean Association of Geographic Information Studies
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    • v.4 no.2
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    • pp.38-45
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    • 2001
  • Three lines from $36_{\circ}$ N, $124_{\circ}$ E, and $132_{\circ}$ E of the East Sea and the Yellow Sea were chosen to extract spectra of normalized water leaving radiances. Comparative analysis of the OCTS algorithm and SeaWiFS(OC-2) algorithms was presented here. OCTS algorithm have more overestimate than SeaWiFS(OC-2 algorithm) for detecting chlorophyll concentration. Atmospheric correction algorithm that is excluded the effect of SS in the case 2 water need for long term ocean environmental monitoring of the East Sea and the Yellow Sea. And, considered the effect of CDOM and SS, bio-optical algorithm have to be developed in this research.

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Development of the Regional Algorithms to Quantify Chlorophyll a and Suspended Solid in the Korean Waters using Ocean Color (한국 근해 Ocean Color 위성자료의 정량화)

  • Suh Young Sang;Jang Lee Hyun;Lee Na Kyung;Kim Bok Kee
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.35 no.3
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    • pp.207-215
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    • 2002
  • Ocean color properties can be quantified by the relationship between the band ratios of the sensor on the ocean color satellites and the measured field ocean color parameters, A tool to determine the abundance of primary organism using the observed ocean color properties from satellite is presented. Coincident to ocean color satellite passes over the Korean waters, the research vessels were deployed to survey the East Sea, the South Sea and the West Sea around the Korean waters, We have been able to have more than 101) data sets containing coincident in situ chlorophyll a and the estimated chlorophyll a derived from SeaWiFS (Sea-viewing Wide Field-of-view Sensor) from february, 1999 to October, 2001. We were able to develop three proper regional algorithms for the East Sea, the South Sea and the West Sea of the Korean peninsula to estimate chlorophyll a, and set up regional algorithms to quantify the suspended solid in the southern sea of the Korean peninsula, Futhermore we were successful in finding out a simple way of estimating chlorophyll a in the turbid water (Case 2 water) using the relationship between in situ chlorophyll a and the estimated chlorophyll a from the processed level 2 data, using the NASA's global algorithm.

New Methods for Correcting the Atmospheric Effects in Landsat Imagery over Turbid (Case-2) Waters

  • Ahn Yu-Hwan;Shanmugam P.
    • Korean Journal of Remote Sensing
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    • v.20 no.5
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    • pp.289-305
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    • 2004
  • Atmospheric correction of Landsat Visible and Near Infrared imagery (VIS/NIR) over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper introduces two methods, a modified dark-pixel substraction technique (path--extraction) and our spectral shape matching method (SSMM), for the correction of the atmospheric effects in the Landsat VIS/NIR imagery in relation to the retrieval of meaningful information about the ocean color, especially from Case-2 waters (Morel and Prieur, 1977) around Korean peninsula. The results of these methods are compared with the classical atmospheric correction approaches based on the 6S radiative transfer model and standard SeaWiFS atmospheric algorithm. The atmospheric correction scheme using 6S radiative transfer code assumes a standard atmosphere with constant aerosol loading and a uniform, Lambertian surface, while the path-extraction assumes that the total radiance (L/sub TOA/) of a pixel of the black ocean (referred by Antoine and Morel, 1999) in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it extracts the path signal from the L/sub TOA/ by matching-up the in-situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have good agreement with the in-situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in-situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Because of the standard atmosphere with constant aerosols and models adopted in 6S radiative transfer code, a large error is possible between the retrieved and in-situ spectra. The efficiency of spectral shape matching has also been explored, using SeaWiFS imagery for turbid waters and compared with that of the standard SeaWiFS atmospheric correction algorithm, which falls in highly turbid waters, due to the assumption that values of water-leaving radiance in the two NIR bands are negligible to enable retrieval of aerosol reflectance in the correction of ocean color imagery. Validation suggests that accurate the retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical algorithms, but is feasible with SSMM.

Overview and Prospective of Satellite Chlorophyll-a Concentration Retrieval Algorithms Suitable for Coastal Turbid Sea Waters (연안 혼탁 해수에 적합한 위성 클로로필-a 농도 산출 알고리즘 개관과 전망)

  • Park, Ji-Eun;Park, Kyung-Ae;Lee, Ji-Hyun
    • Journal of the Korean earth science society
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    • v.42 no.3
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    • pp.247-263
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    • 2021
  • Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.