• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.407-413
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• 2013

The Modified Aerosol Factor (MAF) derived from spectral Single-Scattering Albedo (SSA) values was created to express the light absorption properties according to aerosol types. As a factor of the MAF, slope of a linear regression line for SSA at four wavelengths shows positive value for dust aerosol, while negative values were found for mixing with other types of aerosol. The negative values were shown by anthropogenic and smoke aerosols. The modified SSA at 1020 nm was also calculated. MAF was calculated by summing the slope and modified SSA. MAF was -1.0 for the anthropogenic and smoke aerosol and 1.5 for the dust particles. Those values were decreased by increasing light absorption property.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.559-570
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• 2014

Backscatter signal observed from the space-borne Light Detection And Ranging (LIDAR) system is providing unique 3-dimensional spatial distribution as well as temporal variations for atmospheric aerosols. In this study, the continuous observations for aerosol profiles were analyzed during a years of 2012 by using a Cloud-Aerosol LIDAR with Orthogonal Polarization (CALIOP), carried on the Cloud-Aerosol LIDAR and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. The statistical analysis on the particulate extinction coefficient and depolarization ratio for each altitude was conducted according to time and space in order to estimate the variation of optical properties of aerosols over Northeast Asia ($E110^{\circ}-140^{\circ}$, $N20^{\circ}$ $-50^{\circ}$). The most frequent altitudes of aerosols are clearly identified and seasonal mean aerosol profiles vary with season. Since relatively high particle depolarization ratios (>0.5) are found during all seasons, it is considered that the non-spherical aerosols mixed with pollution are mainly exists over study area. This study forms initial regional 3-dimensional aerosol information, which will be extended and improved over time for estimation of aerosol climatology and event cases.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.307-312
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• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agency of Japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy-and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is as-sumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays vey similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.403-406
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• 2006

An algorithm for detection of yellow sand aerosols has been developed with infrared bands. This algorithm is a hybrid algorithm that has used two methods combined. The first method used the differential absorption in brightness temperature difference between $11{\mu}m\;and\;12{\mu}m\;(BTD1)$. The radiation at $11{\mu}m$ is absorbed more than at $12{\mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{\mu}m\;and\;11{\mu}m(BTD2)$. This technique is sensitive to dust loading, which the BTD2 is enhanced by reflection of $3.7{\mu}m$ solar radiation. First the Principle Component Analysis (PCA), a form of eigenvector statistical analysis from the two methods, is performed and the aerosol pixel with the lowest 10% of the eigenvalue is eliminated. Then the aerosol index (AI) from the combination of BTD 1 and 2 is derived. We applied this method to Multi-functional Transport Satellite-l Replacement (MTSAT-1R) data and obtained that the derived AI showed remarkably good agreements with Ozone Mapping Instrument (OMI) AI and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.961-970
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• 2017

Despite of large demand for high spatial resolution products of aerosol properties from satellite remote sensing, it has been very difficult due to the weak signal by a single pixel and higher noise from clouds. In this study, aerosol retrieval algorithm with the high spatial resolution ($500m{\times}500m$) was developed using Geostationary Ocean Color Imager (GOCI) data during the Korea-US Air Quality (KORUS-AQ) period in May-June, 2016.Currently, conventional GOCI Yonsei aerosol retrieval(YAER) algorithm provides $6km{\times}6km$ spatial resolution product. The algorithm was tested for its best possible resolution of 500 m product based on GOCI YAER version 2 algorithm. With the new additional cloud masking, aerosol optical depth (AOD) is retrieved using the inversion method, aerosol model, and lookup table as in the GOCI YAER algorithm. In some cases, 500 m AOD shows consistent horizontal distribution and magnitude of AOD compared to the 6 km AOD. However, the 500 m AOD has more retrieved pixels than 6 km AOD because of its higher spatial resolution. As a result, the 500 m AOD exists around small clouds and shows finer features of AOD. To validate the accuracy of 500 m AOD, we used dataset from ground-based Aerosol Robotic Network (AERONET) sunphotometer over Korea. Even with the spatial resolution of 500 m, 500 m AOD shows the correlation coefficient of 0.76 against AERONET, and the ratio within Expected Error (EE) of 51.1%, which are comparable to the results of 6 km AOD.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.681-691
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• 2016

Using various satellite measurements in UV, visible and IR, diverse algorithms to retrieve aerosol information have been developed and operated to date. Advanced Himawari Imager (AHI) onboard the Himawari 8 weather satellite was launched in 2014 and has 16 channels from visible to Thermal InfRared (TIR) in high temporal and spatial resolution. Using AHI, it is very valuable to retrieve aerosol optical properties over dark surface to demonstrate its capability. To retrieve aerosol optical properties using visible and Near InfRared (NIR) region, surface signal is very important to be removed which can be estimated using minimum reflectivity method. The estimated surface reflectance is then used to retrieve the aerosol optical properties through the inversion process. In this study, we retrieve the aerosol optical properties over dark surface, but not over bright surface such as clouds, desert and so on. Therefore, the bright surface was detected and masked using various infrared channels of AHI and spatial heterogeneity, Brightness Temperature Difference (BTD), etc. The retrieval result shows the correlation coefficient of 0.7 against AERONET, and the within the Expected Error (EE) of 49%. It is accurately retrieved even for low Aerosol Optical Depth (AOD). However, AOD tends to be underestimated over the Beijing Hefei area, where the surface reflectance using the minimum reflectance method is overestimated than the actual surface reflectance.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.663-670
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• 2013

Total Vertical Column Density (VCD) of $NO_2$, a key component in air quality and tropospheric chemistry was measured using a ground-based instrument, Pandora, in Seoul from March 2012 to October 2013. The $NO_2$ measurements using Pandora were compared with those obtained by satellite remote sensing from Ozone Monitoring Instrument (OMI) where the intercomparison characteristics were analyzed as a function of measurement geometry, cloud amount and aerosol loading. The negative biases of the OMI $NO_2$ VCD were larger when cloud amount and Aerosol Optical Depth (AOD) were higher. The correlation coefficient between $NO_2$ VCDs from Pandora and OMI was 0.53 for the entire measurement period, whereas the correlation coefficient between the two was 0.74 when the cloud amount and AOD were low (cloud amount<3, AOD<0.4). The low bias of OMI data was associated with the shielding effect of the cloud and the aerosols.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.95-99
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• 1999

We proposed a new retrieval method for aerosol's real part of refractive index, optical thickness, and Angstrom exponent using POLDER's directional reflectance and polarization data. We showed that aerosol's real part of refractive index can be retrieved systematically using multi-directional PR(polarization and reflectance) diagrams in a single infrared band by our algorithm for the first time. We examined the retrieved results, by comparing with the simultaneously measured sky observation data at the study site and we obtained a reasonable agreement between them.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.605-615
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• 2010

This study demonstrates the feasibility of small satellite, namely PROBA platform with the compact high resolution imaging spectrometer (CHRIS), for aerosol retrieval in Hong Kong. The rationale of our technique is to estimate the aerosol reflectances by decomposing the Top of Atmosphere (TOA) reflectances from surface reflectance and Rayleigh path reflectances. For the determination of surface reflectances, the modified Minimum Reflectance Technique (MRT) is used on three winter ortho-rectified CHRIS images: Dec-18-2005, Feb-07-2006, Nov-09-2006. For validation purpose, MRT image was compared with ground based multispectral radiometer measurements and atmospherically corrected Landsat image. Results show good agreements between CHRIS-derived surface reflectance and both by ground measurement data as well as by Landsat image (r>0.84). The Root-Mean-Square Errors (RMSE) at 485, 551 and 660nm are 0.99%, 1.19%, and 1.53%, respectively. For aerosol retrieval, Look Up Tables (LUT) which are aerosol reflectances as a function of various AOT values were calculated by SBDART code with AERONET inversion products. The CHRIS derived Aerosol Optical Thickness (AOT) images were then validated with AERONET sunphotometer measurements and the differences are 0.05~0.11 (error=10~18%) at 440nm wavelength. The errors are relatively small compared to those from the operational moderate resolution imaging spectroradiometer (MODIS) Deep Blue algorithm (within 30%) and MODIS ocean algorithm (within 20%).

• Proceedings of KOSOMES biannual meeting
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• 2009.06a
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• pp.53-54
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• 2009

The influence of atmospheric aerosol on satellite ocean color data were evaluated using SeaWiFS monthly standard mapped image products. The atmospheric optical thickness (AOT) was increased in spring and summer, and it showed the strong positive correlation with remote sensing reflectance, normalized waterleaving radiance /solar irradiance, at 555 nm (Rrs555) which is a component of the satellite chlorophyll estimation. Such the high AOT and high Rrs555 pixels showed overestimation of satellite chlorophyll in spring, especially in the area which showed large phytoplankton absorption which 1s expressed by low remote sensing reflectance at 443, 490 and 510 nm (Rrs 443, Rrs490 and Rrs510).