• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.187-199
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• 2002

Correlation between chlorophyll a in the East China Sea and spectral bands (412, 443, 490, (510), 555, (676, 765)nm) of Ocean Scanning Multi-Spectral Imager (OSMI) including the profile multi-spectral radiometer (PRR-800) was studied. The values of remote sensing reflectance (Rrs) at the bands corresponding to the field chlorophyll $\alpha$ in the East China Sea were much higher than those in clear waters off California, USA. In case of the particle absorptions related to the chlorophyll a concentration at the spectral bands (440, 670nm) were much higher in the East China Sea than the ones in the clean waters off California. The normalized water leaving radiances (nLw) at 412, 443, 490, 555 nm of OSMI and the field chlorophyll a in the East China Sea were correlated each other. According to the results, the relationship between field chlorophyll $\alpha$ and nLw 410 nm in OSMI bands was the lowest, whereas that between field chlorophyll a and nLw 555 nm in the bands was the highest. Reciprocal action between the field chlorophyll a and the band ratio of the OSMI bands (nLw410/nLw555, nLw443/nLw555, nLw490/nLw555) was also studied. Relationship between the chlorophyll $\alpha$ and the band ratio (nLw490/nLw555) was highest in the OSMI bands. Relationship between the chlorophyll $\alpha$ and the ratio (nLw490/nLw555) was higher than one in the nLw410/nLw555. The difference in the estimated chlorophyll $\alpha$ (mg/m$^3$) between OSMI and SeaWiFS (Sea Viewing Wide Field-of-View Sensor) at the special observing stations in the northern eastern sea of Jeju Island in February 25, 2002 was about less than 0.3 mg/m$^3$ within 3 hours. It is suggested that OC2 (ocean color chlorophyll 2 algorithm) be used to get much better estimation of chlorophyll $\alpha$ from OSMI than the ones from the updated algorithms as OC4.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.189-198
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• 2022

In this present study, we investigated the effect of the offset correction factor calculation method on the sulfur dioxide (SO₂) column density in the SO₂ retrieval algorithm of the Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020. The GEMS operational SO₂ retrieval algorithm is the Differential Optical Absorption Spectroscopy (DOAS) - Principal Component Analysis (PCA) Hybrid algorithm. In the GEMS Hybrid algorithm, the offset correction process is essential to correct the absorption effect of ozone appearing in the SO₂ slant column density (SCD) obtained after spectral fitting using DOAS. Since the SO₂ column density may depend on the conditions for calculating the offset correction factor, it is necessary to apply an appropriate offset correction value. In this present study, the offset correction values were calculated for days with many cloud pixels and few cloud pixels, respectively. And a comparison of the SO₂ column density retrieved by applying each offset correction factor to the GEMS operational SO₂ retrieval algorithm was performed. When the offset correction value was calculated using radiance data of GEMS on a day with many cloud pixels was used, the standard deviation of the SO₂ column density around India and the Korean Peninsula, which are the edges of the GEMS observation area, was 1.27 DU, and 0.58 DU, respectively. And around Hong Kong, where there were many cloud pixels, the SO₂ standard deviation was 0.77 DU. On the other hand, when the offset correction value calculated using the GEMS data on the day with few cloud pixels was used, the standard deviation of the SO₂ column density slightly decreased around India (0.72 DU), Korean Peninsula (0.38 DU), and Hong Kong (0.44 DU). We found that the SO₂ retrieval was relatively stable compared to the SO₂ retrieval case using the offset correction value on the day with many cloud pixels. Accordingly, to minimize the uncertainty of the GEMS SO₂ retrieval algorithm and to obtain a stable retrieval, it is necessary to calculate the offset correction factor under appropriate conditions.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1423-1444
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• 2022

In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.609-625
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• 2022

Validation of satellite data products is critical for subsequent analysis that is based on the data. Particularly, performance of ocean color products in turbid and shallow near-land ocean areas has been questioned for long time for its difficulty that stems from the complex optical environment with varying distribution of water constituents. Furthermore, validation with ship-based or station-based measurements has also exhibited clear limitation in its spatial scale that is not compatible with that of satellite data. This study firstly performed validation of major GOCI-II products such as remote sensing reflectance, chlorophyll-a concentration, suspended particulate matter, and colored dissolved organic matter, using the in-situ measurements collected from ship-based field campaign. Secondly, this study also presents preliminary analysis on the use of drone images for product validation. Multispectral images were acquired from a MicaSense RedEdge camera onboard a UAV to compensate for the significant scale difference between the ship-based measurements and the satellite data. Variation of water radiance in terms of camera altitude was analyzed for future application of drone images for validation. Validation conducted with a limited number of samples showed that GOCI-II remote sensing reflectance at 555 nm is overestimated more than 30%, and chlorophyll-a and colored dissolved organic matter products exhibited little correlation with in-situ measurements. Suspended particulate matter showed moderate correlation with in-situ measurements (R²~0.6), with approximately 20% uncertainty.