• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1591-1604
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• 2023

In ocean color remote sensing, atmospheric correction is a vital process for ensuring the accuracy and reliability of ocean color products. Furthermore, in recent years, the remote sensing community has intensified its requirements for understanding errors in satellite data. Accordingly, research is currently addressing errors in remote sensing reflectance (R_rs) resulting from inaccuracies in meteorological variables (total ozone, pressure, wind field, and total precipitable water) used as auxiliary data for atmospheric correction. However, there has been no investigation into the error in R_rs caused by the variability of the water vapor profile, despite it being a recognized error source. In this study, we used the Second Simulation of a Satellite Signal Vector version 2.1 simulation to compute errors in water vapor transmittance arising from variations in the water vapor profile within the GOCI-II observation area. Subsequently, we conducted an analysis of the associated errors in ocean color products. The observed water vapor profile not only exhibited a complex shape but also showed significant variations near the surface, leading to differences of up to 0.007 compared to the US standard 62 water vapor profile used in the GOCI-II atmospheric correction. The resulting variation in water vapor transmittance led to a difference in aerosol reflectance estimation, consequently introducing errors in R_rs across all GOCI-II bands. However, the error of R_rs in the 412-555 nm due to the difference in the water vapor profile band was found to be below 2%, which is lower than the required accuracy. Also, similar errors were shown in other ocean color products such as chlorophyll-a concentration, colored dissolved organic matter, and total suspended matter concentration. The results of this study indicate that the variability in water vapor profiles has minimal impact on the accuracy of atmospheric correction and ocean color products. Therefore, improving the accuracy of the input data related to the water vapor column concentration is even more critical for enhancing the accuracy of ocean color products in terms of water vapor absorption correction.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1299-1312
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• 2019

As land remote sensing applications are expanding to the extraction of quantitative information, the importance of atmospheric correction is increasing. Considering the difficulty of atmospheric correction for land images, it should be applied when it is necessary. The quantitative information extraction and time-series analysis on biophysical variables in land surfaces are two major applications that need atmospheric correction. Atmospheric aerosol content and column water vapor, which are very dynamic in spatial and temporal domain, are the most influential elements and obstacles in retrieving accurate surface reflectance. It is difficult to obtain aerosol and water vapor data that have suitable spatio-temporal scale for high- and medium-resolution multispectral imagery. Selection of atmospheric correction method should be based on the availability of appropriate aerosol and water vapor data. Most atmospheric correction of land imagery assumes the Lambertian surface, which is not the case for most natural surfaces. Further BRDF correction should be considered to remove or reduce the anisotropic effects caused by different sun and viewing angles. The atmospheric correction methods of optical imagery over land will be enhanced to meet the need of quantitative remote sensing. Further, imaging sensor system may include pertinent spectral bands that can help to extract atmospheric data simultaneously.

• Proceedings of the KSRS Conference
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• v.2
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• pp.619-622
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• 2006

Atmospheric correction is one of critical procedures to extract quantitative information related to biophysical variables from hyperspectral data. In this study, we attempted to generate the water vapor contents image from hyperspectral data itself and developed the atmospheric correction algorithm for EO-1 Hyperion data using pre-calculated atmospheric look-up-table (LUT) for fast processing. To apply the new atmospheric correction algorithm, Hyperion data acquired June 3, 2001 over Seoul area is used. Reflectance spectrums of various targets on atmospheric corrected Hyperion reflectance images showed the general spectral pattern although there must be further development to reduce the spectral noise.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1295-1305
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• 2021

Satellite-derived ocean color products are required to effectively monitor clear open ocean and coastal water regions for various research fields. For this purpose, accurate correction of atmospheric effect is essential. Currently, the Geostationary Ocean Color Imager (GOCI)-II ground segment uses the reanalysis of meteorological fields such as European Centre for Medium-Range Weather Forecasts (ECMWF) or National Centers for Environmental Prediction (NCEP) to correct gas absorption by water vapor and ozone. In this process, uncertainties may occur due to the low spatiotemporal resolution of the meteorological data. In this study, we develop water vapor absorption correction model for the GK-2 combined GOCI-II atmospheric correction using Advanced Meteorological Imager (AMI) total precipitable water (TPW) information through radiative transfer model simulations. Also, we investigate the impact of the developed model on GOCI products. Overall, the errors with and without water vapor absorption correction in the top-of-atmosphere (TOA) reflectance at 620 nm and 680 nm are only 1.3% and 0.27%, indicating that there is no significant effect by the water vapor absorption model. However, the GK-2A combined water vapor absorption model has the large impacts at the 709 nm channel, as revealing error of 6 to 15% depending on the solar zenith angle and the TPW. We also found more significant impacts of the GK-2 combined water vapor absorption model on Rayleigh-corrected reflectance at all GOCI-II spectral bands. The errors generated from the TOA reflectance is greatly amplified, showing a large error of 1.46~4.98, 7.53~19.53, 0.25~0.64, 14.74~40.5, 8.2~18.56, 5.7~11.9% for from 620 nm to 865 nm, repectively, depending on the SZA. This study emphasizes the water vapor correction model can affect the accuracy and stability of ocean color products, and implies that the accuracy of GOCI-II ocean color products can be improved through fusion with GK-2A/AMI.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.305-308
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• 2008

The goal of this study is to retrieve ASTER thermal radiometry using a radiative transfer model. The MODTRAN is used for the model because it is easy to use with high spatial resolution and it is possible to specify input parameters such as profiles of temperature, water vapor density, ozone, aerosols and any of the other gasses. Most of parameters such as temperature and water vapor profiles were obtained from the Terra MODIS. The selected ASTER scene images land and coastal area. The surface radiance of ASTER TIR bands were retrieved by MODTRAN and extracted atmospheric profiles from MOD07 and US standard 76 models. Radiance estimated using MOD07 data was systematically lower by about 0.5-1.0 $W/m^2$ sr ${\mu}m$ than that by US standard 76 model between the two cases.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.535-544
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• 2009

Signals from the Global Positioning System(GPS) satellite are used to retrieve the integrated amount of water vapor or the precipitable water vapor(PWV) along the path between a transmitting satellite and ground-based receiver. In order to retrieve the PWV from GPS signal delay in the troposphere, the actual zenith wet delay, which can be derived by extracting the zenith total delay and subtracting the actual zenith hydrostatic delay computed using surface pressure observing, will be needed. Since it has been not co-located between GPS permanent station and automated weather station, the air-pressure on the mean sea level has been used to determine the actual zenith hydrostatic delay. The directly use of this air-pressure has been caused the dilution of precision on GPS PWV retrieval. In this study, Korean reverse sea level correction method of air-pressure was suggested for the improving of GPS PWV retrieval capability and the accuracy of water vapor estimated by GPS was evaluated through a comparison with radiosonde PWV.

• Spatial Information Research
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• v.18 no.4
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• pp.33-41
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• 2010

Approximately 100 permanent GPS stations are currently operational in Korea. However, only 10 sites have their own weather sensors connected directly to the GPS receiver. Thus. calculation of meteorological data through interpolation of AWS data are needed to determine precipitable water vapors at a specific GPS station without a meteorological sensor. This study analyzed the accuracy of two meteorological data interpolation methods called reverse sea level correction and kriging. As a result, the root-mean square-error of reverse sea level correction were seven times more accurate in pressure and twice more accurate in temperature than the kriging method. For the analysis of PWV accuracy, we calculated GPS PWV during the summer season in :2008 by using GPS observation data and interpolated meteorological data by reverse sea level correction. And, we compared GPS PWV s based on interpolated meteorological data with those from radiosonde observations and GPS PWV s based on onsite GPS meteorological sensor measurements. As a result, the accuracy of GPS PWV s from our interpolated meteorological data was within the required operational accuracy of 3mm.

• Fashion & Textile Research Journal
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• v.25 no.1
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• pp.119-126
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• 2023

This study aimed to determine the effects of relative humidity and fiber properties on the moisture permeability of multilayer systems by measuring water vapor transmission in the overlapping condition of various fabrics. The results confirmed that the property of the fabric in contact with the humid environment affects the moisture permeability. If the layer facing the humid environment is hydrophobic and the layer facing the dry environment is superhydrophobic, water vapor transmission increases by up to 17.8% compared to the opposite conditions. Comparing the correction values of the water vapor transmission reflecting the thickness of the specimen under the multilayer condition showed that permeability was higher when the hydrophilic or hydrophobic layer was facing the humid environment. The opposite was true from the "push-pull" effect of absorption mechanism. In the case of moisture permeability, the more hydrophilic the surface facing the humid environment, the more permeable that water vapor diffuses and passes through. It was concluded that the "pull-push" effect, in which water vapor diffuses widely through the hydrophilic facing a humid environment and then passes through the hydrophobic layer, contributes to the improvement of permeability. Permeability differed according to the multilayer overlapping condition. When the relative humidity was high, the "pull-push" effect was insignificant. This is caused by water droplets absorption after the partial migration of water due to condensation. These results suggest that the overlapping conditions and properties of fabrics should vary depending on heavy sweating or not.

• The Bulletin of The Korean Astronomical Society
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• v.32 no.2
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• pp.59.2-59.2
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• 2007

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.95-100
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• 2013

Several observation equipments are being used for determination of the water vapor content and precipitable water vapor (PWV) because the water vapor is highly variable temporally and spatially. In this study, we used GNSS systems such as GPS and GLONASS in standalone and combined modes to compute PWV and validated their accuracy with respect to the results of other water-vapor monitoring systems. The other systems used were radiosonde and microwave radiometer, and the comparisons were convenient because all three systems were collocated at the test site. The differences of PWW were in the range of 0.6-3.4 mm in the mean sense, and their standard deviations were 1.0-3.8 mm. The relatively large difference of GNSS compared with the other two systems were believed to be caused by the fact that the GNSS antenna used in this study was the kind for which the international standard of phase center variations (PCV) calibration is not available. We expect better accuracy of PWV determination and improved availability of it through integrated data processing of GPS/GLONASS when an appropriate antenna with PCV correction model is used.