• Title/Summary/Keyword: SeaWiFS imagery

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Extraction of the atmospheric path radiance in relation to retrieval of ocean color information from the TM and SeaWiFS imageries

  • Ahn, Yu-Hwan;Shanmugam, P.
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.241-246
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    • 2004
  • The ocean signal that reaches the detector of an imaging system after multiple interactions with the atmospheric molecules and aerosols was retrieved from the total signal recorded at the top of the atmosphere (TOA). A simple method referred to as 'Path Extraction' applied to the Landsat-TM ocean imagery of turbid coastal water was compared with the conventional dark-pixel subtraction technique. The shape of the path-extracted water-leaving radiance spectrum resembled the radiance spectrum measured in-situ. The path-extraction was also extended to the SeaWiFS ocean color imagery and compared with the standard SeaWiFS atmospheric correction algorithm, which relays on the assumption of zero water leaving radiance at the two NIR wavebands (765 and 865nm). The path-extracted water-leaving radiance was good agreement with the measured radiance spectrum. In contrast, the standard SeaWiFS atmospheric correction algorithm led to essential underestimation of the water-leaving radiance in the blue-green part of the spectrum. The reason is that the assumption of zero water-leaving radiance at 755 and 865nm fails due to backscattering by suspended mineral particles. Therefore, the near infrared channels 765 and 865nm used fur deriving the aerosol information are no longer valid for turbid coastal waters. The path-extraction is identified as a simple and efficient method of extracting the path radiance largely introduced due to light interaction through the complex atmosphere carried several aerosol and gaseous components and at the air-sea interface.interface.

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Calibration and Validation of Ocean Color Satellite Imagery (해양수색 위성자료의 검.보정)

  • ;B. G. Mitchell
    • Journal of Environmental Science International
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    • v.10 no.6
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    • pp.431-436
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    • 2001
  • Variations in phytoplankton concentrations result from changes of the ocean color caused by phytoplankton pigments. Thus, ocean spectral reflectance for low chlorophyll waters are blue and high chlorophyll waters tend to have green reflectance. In the Korea region, clear waters and the open sea in the Kuroshio regions of the East China Sea have low chlorophyll. As one moves even closer In the northwestern part of the East China Sea, the situation becomes much more optically complicated, with contributions not only from higher concentration of phytoplankton, but also from sediments and dissolved materials from terrestrial and sea bottom sources. The color often approaches yellow-brown in the turbidity waters (Case Ⅱ waters). To verify satellite ocean color retrievals, or to develop new algorithms for complex case Ⅱ regions requires ship-based studies. In this study, we compared the chlorophyll retrievals from NASA's SeaWiFS sensor with chlorophyll values determined with standard fluorometric methods during two cruises on Korean NFRDI ships. For the SeaWiFS data, we used the standard NASA SeaWiFS algorithm to estimate the chlorophyll_a distribution around the Korean waters using Orbview/ SeaWiFS satellite data acquired by our HPRT station at NFRDl. We studied In find out the relationship between the measured chlorophyll_a from the ship and the estimated chlorophyll_a from the SeaWiFs satellite data around the northern part of the East China Sea, in February, and May, 2000. The relationship between the measured chlorophyll_a and the SeaWiFS chlorophyll_a shows following the equations (1) In the northern part of the East China Sea. Chlorophyll_a =0.121Ln(X) + 0.504, R²= 0.73 (1) We also determined total suspended sediment mass (55) and compared it with SeaWiFS spectral band ratio. A suspended solid algorithm was composed of in-.situ data and the ratio (L/sub WN/(490 ㎚)L/sub WN/(555 ㎚) of the SeaWiFS wavelength bands. The relationship between the measured suspended solid and the SeaWiFS band ratio shows following the equation (2) in the northern part of the East China Sea. SS = -0.703 Ln(X) + 2.237, R²= 0.62 (2) In the near future, NFRDI will develop algorithms for quantifying the ocean color properties around the Korean waters, with the data from regular ocean observations using its own research vessels and from three satellites, KOMPSAT/OSMl, Terra/MODIS and Orbview/SeaWiFS.

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Application of SeaWiFS Chlorophyll-a Ocean Color Image for estimating Sea Surface Currents from Geostationary Ocean Color Imagery (GOCI) data (정지궤도 해색탑재체(GOCI) 표층유속 추정을 위한 SeaWiFS 해색자료의 응용)

  • Kim, Eung;Ro, Young-Jae;Jeon, Dong-Chull
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.209-220
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    • 2010
  • One of the most difficult tasks in measuring oceanic conditions is to produce oceanic current information. In efforts to overcome the difficulties, various attempts have been carried out to estimate the speed and direction of ocean currents by utilizing sequential satellite images. In this study, we have estimated sea surface current vectors to the south of the Korean Peninsula, based on the maximum cross-correlation method by using sequential ocean color images of SeaWiFS chlorophyll-a. Comparison of surface current vectors estimated by this method with the geostrophic current vectors estimated from satellite altimeter data and in-situ ADCP measurements are good in that current speeds are underestimated by about 15% and current directions are show differences of about $36^{\circ}$ compared with previous results. The technique of estimating current vectors based on maximum cross-correlation applied on sequential images of SeaWiFS is promising for the future application of GOCI data for the ocean studies.

COMPARISON OF RED TIDE DETECTION BY A NEW RED TIDE INDEX METHOD AND STANDARD BIO-OPTICAL ALGORITHM APPLIED TO SEA WIFS IMAGERY IN OPTICALLY COMPLEX CASE-II WATERS

  • Shanmugam Palanisamy;Ahn Yu-Hwan
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.445-449
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    • 2005
  • Various methods to detect the phytoplankton/red tide blooms in the oceanic waters have been developed and tested on satellite ocean color imagery since the last two and half decades, but accurate detection of blooms with these methods remains challenging in optically complex turbid waters, mainly because of the eventual interference of absorbing and scattering properties of dissolved organic and particulate inorganic matters with these methods. The present study introduces a new method called Red tide Index (Rl), providing indices which behave as a good measure of detecting red tide algal blooms in high scattering and absorbing waters of the Korean South Sea and Yellow Sea. The effectiveness of this method in identifying and locating red tides is compared with the standard Ocean Chlorophyll 4 (OC4) bio-optical algorithm applied to SeaWiFS ocean imagery, acquired during two bloom episodes on 27 March 2002 and 28 September 2003. The result revealed that OC4 bio-optical algorithm falsely identifies red tide blooms in areas abundance in colored dissolved organic and particulate inorganic matter constituents associated with coastal areas, estuaries and river mouths, whereas red tide index provides improved capability of detecting, predicting and monitoring of these blooms in both clear and turbid waters.

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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.

DETECTION OF DUST LOADED AIRMASS IN SEAWIFS IMAGERY: AN EMPIRICAL DUST INDEX IN COMPARISON WITH MODEL-PREDICTED DUST DISTRIBUTION OVER THE PACIFIC IN APRIL,1998

  • Fukushima, H.;Schmidt, M.;Sohn, B.J.;Toratani, M.;Uno, I.
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.89-94
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    • 1999
  • The paper first proposes an empirical algorithm for detecting dust-loaded airmass observed by Sea Wide Field-of-view Scanner (SeaWiFS). The proposed dust index formula is based on the curvature of the spectral reflectance estimated from the SeaWiFS band 4 (510 nm band) through band 8 (865 nm band) data, assuming "clear ocean water" reflectance. Evaluation of the algorithm is made over several typical Asian dust images including the ones over the Pacific in April, 1998, when a major dust event was reported. The study analyzes the performance and the characteristics of the algorithm by comparing the satellite-derived dust index images with contemporaneous columnar concentration of dust particles predicted by a numerical dust transport model. The comparison reveals several small-scale differences although their dust distribution patterns show good agreement generally.

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SATELLITE DETECTION OF RED TIDE ALGAL BLOOMS IN TURBID COASTAL WATERS

  • Ahn, Yu-Hwan;Shanmugam, Palanisamy
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.471-474
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    • 2006
  • Several planktonic dinoflagellates, including Cochlodinium polykrikoides (p), are known to produce red tides responsible for massive fish kills and serious economic loss in turbid Northwest Pacific (Korean and neighboring) coastal waters during summer and fall seasons. In order to mitigate the impacts of these red tides, it is therefore very essential to detect, monitor and forecast their development and movement using currently available remote sensing technology because traditional ship-based field sampling and analysis are very limited in both space and temporal frequency. Satellite ocean color sensors, such as Sea-viewing Wide Field-of-view Sensor (SeaWiFS), are ideal instruments for detecting and monitoring these blooms because they provide relatively high frequency synoptic information over large areas. Thus, the present study attempts to evaluate the red tide index methods (previously developed by Ahn and Shanmugam et al., 2006) to identify potential areas of red tides from SeaWiFS imagery in Korean and neighboring waters. Findings revealed that the standard spectral ratio algorithms (OC4 and LCA) applied to SeaWiFS imagery yielded large errors in Chl retrievals for coastal areas, besides providing false information about the encountered red tides in the focused waters. On the contrary, the RI coupled with the standard spectral ratios yielded comprehensive information about various ranges of algal blooms, while RCA Chl showing a good agreement with in-situ data led to enhanced understanding of the spatial and temporal variability of the recent red tide occurrences in high scattering and absorbing waters off the Korean and Chinese coasts. The results suggest that the red tide index methods for the early detection of red tides blooms can provide state managers with accurate identification of the extent and location of blooms as a management tool.

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Detection of Asian Dust Air-mass based on Short Wavelength Observation of SeaWiFS

  • Fukushima, H.;Hagihara, Y.;Hoshikuma, Y.;Ohta, S.;Uno, I.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1203-1205
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    • 2003
  • To detect dust-loaded air-mass over land and ocean, we propose an index, which is essentially the difference in Rayleigh-corrected reflectance between 412 and 443 nm bands of SeaWiFS. Radiative transfer simulations are conducted to show that the index is linearly related to the optical thickness of modeled dust-contaminated aerosol while showing insensitivity against non-absorbing model aerosols. Asian SeaWiFS data set of 2001 spring is used to produce daily composite imagery of the index, which compares well with TOMS Aerosol Index and with predicted aerosol optical thickness predicted by CFORS chemical weather forecast.

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STUDY ON THE DEVELOPMENT OF $a_{dom}$ ESTIMATION ALGORITHM BY EMPIRICAL METHOD FOR GOCI OCEAN COLOR SENSOR

  • Moon, Jeong-Eon;Ahn, Yu-Hwan;Ryu, Joo-Hyung;Choi, Joong-Ki
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.49-52
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    • 2007
  • This study uses empirical method to estimate absorption coefficient of colored dissolved organic matter $(a_{dom})$ from GOCI satellite data with the relationship between band ratio of remote sensing reflectance $(R_{rs})$ and $a_{dom}$. For development of $a_{dom}$ estimation algorithm, the used data is in-situ data about ocean optical properties in the around seawater area of the Korean Peninsula during 1998 - 2005. The relationship of $R_{rs}$(412)/$R_{rs}$(555), $R_{rs}$(443)/$R_{rs}$(555), $R_{rs}$(490)/$R_{rs}$(555), $R_{rs}$(510)/$R_{rs}$(555) and $a_{dom}$(412) showed $R^2$ values of 0.707, 0.707, 0.597 and 0.552, respectively. The spectrum of $a_{dom}({\lambda})$ is shape of exponential function $a_{dom}({\lambda})$ value decreases with increasing wavelength. For estimation of $a_{dom}$ from satellite data, we developed an algorithm from the relationship of $a_{dom}$(412) and $R_{rs}$(412)/$R_{rs}$(555). This algorithm was employed on SeaWiFS imagery to estimate $R_{rs}$(412) in the South Sea, East Sea, Yellow Sea and northern East China Sea areas. Also, SeaDAS-derived $a_{dg}$(412) from same SeaWiFS imagery, These $a_{dg}$(412) was then compared with in-situ and empirical-algorithm-derived $a_{dom}$(412), but these values were different. We think two points that such different values are caused by discrepancy related to failure of standard atmospheric correction scheme, the other are caused by error related to definition of $a_{dom}$(412) and $a_{dg}$(412).

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ATMOSPHERIC CORRECTION TECHNIQUE FOR GEOSTATIONARY OCEAN COLOR IMAGER (GOCI) ON COMS

  • Shanmugam, Palanisamy;Ahn, Yu-Hwan
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.467-470
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    • 2006
  • Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meteorological Satellite (COMS) is scheduled for launch in 2008. GOCI includes the eight visible-to-near-infrared (NIR) bands, 0.5km pixel resolution, and a coverage region of 2500 ${\times}$ 2500km centered at 36N and 130E. GOCI has had the scope of its objectives broadened to understand the role of the oceans and ocean productivity in the climate system, biogeochemical variables, geological and biological response to physical dynamics and to detect and monitor toxic algal blooms of notable extension through observations of ocean color. To achieve these mission objectives, it is necessary to develop an atmospheric correction technique which is capable of delivering geophysical products, particularly for highly turbid coastal regions that are often dominated by strongly absorbing aerosols from the adjacent continental/desert areas. In this paper, we present a more realistic and cost-effective atmospheric correction method which takes into account the contribution of NIR radiances and include specialized models for strongly absorbing aerosols. This method was tested extensively on SeaWiFS ocean color imagery acquired over the Northwest Pacific waters. While the standard SeaWiFS atmospheric correction algorithm showed a pronounced overcorrection in the violet/blue or a complete failure in the presence of strongly absorbing aerosols (Asian dust or Yellow dust) over these regions, the new method was able to retrieve the water-leaving radiance and chlorophyll concentrations that were consistent with the in-situ observations. Such comparison demonstrated the efficiency of the new method in terms of removing the effects of highly absorbing aerosols and improving the accuracy of water-leaving radiance and chlorophyll retrievals with SeaWiFS imagery.

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