• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.507-517
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• 2018

Aerosol optical depth (AOD) data retrieved by the Communication, Ocean and Meteorological Satellite (COMS) during 2011-2014 were compared with AOD measurements from 134 Aerosol Robotic Network (AERONET) sites over the East Asia. Overall, COMS and AERONET AODs were weakly correlated (R = 0.297). The agreement between COMS and AERONET AODs was improved when data from near Korean peninsula sites were selected (R = 0.475). Regression analysis results for each AERONET site are vary from R=0.026 at AOE_Baotou to 0.905 at DRAGON_Anmyeon. It was also shown that the bias in COMS AOD was not systematic with respect to effective radius, precipitable water, surface reflectance, and sun zenith angle. Together, these results suggest that COMS AOD measurements may be suitable for near Korea. Finally, the current results will help to improve the retrieval algorithm and vary when using alternative COMS AOD version in the future.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.425-439
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• 2020

Through the operations of advanced geostationary meteorological satellite such as Himawari-8 and GK2A, higher resolution and frequency of AOD (Aerosol Optical Depth) data have become available. In this study, we analyzed the characteristics of Himawari-8/AHI (Advanced Himawari Imager) aerosol properties using the recent 4 years (2016~2019) of Sun photometer data observed at the five stations(Seoul National University, Yonsei University, Hankuk University of Foreign Studies, Gwangju Institute of Science and Technology, Anmyon island) which is a part of the AERONET (Aerosol Robotic Network). In addition, we analyzed the causes for the AOD differences between Himawari AOD and Sun photometer AOD. The results showed that the two AOD data are very similar regardless of geographic location, in particular, for the clear condition (cloud amount < 3). However, the quality of Himawari AOD data is heavily degraded compared to that of the clear condition, in terms of bias (0.05 : 0.21), correlation (0.74 : 0.64) and RMSE (Root Mean Square Error; 0.21 : 0.51), when cloud amount is increased. In general, the large differences between two AOD data are mainly related to the cloud amount and relative humidity. The Himawari strongly overestimates the AOD at all five stations when cloud amount and relative humidity are large. However, the wind speed, precipitable water, height of cloud base and Angstrom Exponent have been shown to have no effect on the AOD differences irrespective of geographic location and cloud amount. The results suggest that caution is required when using Himawari AOD data in cloudy conditions.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.861-870
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• 2021

In this study, fused Aerosol Optical Depth (AOD) data were produced using AOD products from the Geostationary Ocean Color Imager (GOCI) onboard Communication, Oceanography and Meteorology Satellite (COMS)satellite and the Advanced Himawari Imager (AHI) onboard Himawari-8. Since the spatial resolution and the coordinate system between the satellite sensors are different, a preprocessing was first preceded. After that, using the level 1.5 AOD dataset of AErosol RObotic NETwork (AERONET), which is ground-based observation, correlations and trends between each satellite AOD and AERONET AOD were utilized to produce more accurate satellite AOD data than the originalsatellite AODs. The fused AOD were found to be more accurate than the originalsatellite AODs. Root Mean Square Error (RMSE) and mean bias of the fused AODs were calculated to be 0.13 and 0.05, respectively. We also compared errors of the fused AODs against those of the original GOCI AOD (RMSE: 0.15, mean bias: 0.11) and the original AHI AOD (RMSE: 0.15, mean bias: 0.05). It was confirmed that the fused AODs have betterspatial coverage than the original AODsin areas where there are no observations due to the presence of cloud from a single satellite.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.12
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• pp.92-98
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• 1998

In this paper, we implemented an angularly multiplexed volume holographic memory system using an AOD that is controlled electronically, with rapid access time(10$mutextrm{s}$) and accurate repeatability of the reference beam. First we designed an AOD-based angular multiplexing system without the frequency compensation of the object beam, and magnified the deflection angle of AOD through the combination of lens so that we increased the storage capacity up to six times. Finally fifty-one images were stored experimentally in a photorefractive material of 1㎤ Fe:LiNbO$_3$.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.83-101
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• 2022

Accurate atmospheric correction is essential for the analysis of land surface and environmental monitoring. Aerosol optical depth (AOD) information is particularly important in atmospheric correction because the radiation attenuation by Mie scattering makes the differences between the radiation calculated at the satellite sensor and the radiation measured at the land surface. Thus, it is necessary to use high-quality AOD data for an appropriate atmospheric correction of high-resolution satellite images. In this study, we examined the Second Simulation of a Satellite Signal in the Solar Spectrum (6S)-based atmospheric correction results for the Sentinel-2 images in South Korea using raster AOD (MODIS) and single-point AOD (AERONET). The 6S result was overall agreed with the Sentinel-2 level 2 data. Moreover, using raster AOD showed better performance than using single-point AOD. The atmospheric correction using the single-point AOD yielded some inappropriate values for forest and water pixels, where as the atmospheric correction using raster AOD produced stable and natural patterns in accordance with the land cover map. Also, the Sentinel-2 normalized difference vegetation index (NDVI) after the 6S correction had similar patterns to the up scaled drone NDVI, although Sentinel-2 NDVI had relatively low values. Also, the spatial distribution of both images seemed very similar for growing and harvest seasons. Future work will be necessary to make efforts for the gap-filling of AOD data and an accurate bi-directional reflectance distribution function (BRDF) model for high-resolution atmospheric correction. These methods can help improve the land surface monitoring using the future Compact Advanced Satellite 500 in South Korea.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.4
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• pp.18-25
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• 2020

The purpose of this study is to investigate the mechanical and carbon-capture properties of foam concrete containing stainless steel argon oxygen decarbonization(AOD) slag. AOD slag was used as a binder, and foam concrete having a foaming ratio of 69 ± 0.5 % and a slurry density of 573.2 to 578.6 kg / ㎥ was produced. In order to examine the effect of carbonation, blended specimen was cured by two types : normal curing and CO₂ curing. As a result of the experiment, the specimens incorporating AOD slag showed higher compressive strength than Plain after CO₂ curing. According to the analysis of the image of foam concrete, it was confirmed that the ST30 has a lower total pore volume and average pore size than plain, resulting in high compressive strength. The SEM analysis confirmed the formation of calcite by carbonation of AOD slag. Through the thermogravimetric analysis, the increase of CO₂ uptake was confirmed by the incorporation of AOD slag. Foam concrete has a higher porosity than normal concrete, so it is expected that carbon-capture performance can be improved by using a AOD slag.

• Proceedings of the KSRS Conference
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• v.1
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• pp.232-235
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• 2006

Using 30 days of hourly visible channel data and DIScrete Ordinate Radiative Transfer (DISORT) model (6S), Aerosol optical depth (AOD) at $0.55{\mu}m$ was retrieved over the East Asia. In contrast with the AOD retrieval using low-earth-orbit satellites such as MODIS (Moderate-Res olution Spectroradiometer) or MISR (Multiangle Imaging SpectroRadiometer), this algorithm with geostationary satellite can improve the monitoring of AOD without the limitation of temporal resolution. Due to the limited number of channels in the conventional meteorological imager onboard the geostationary satellite, an AOD retrieval algorithm utilizing a single visible channel has been introduced. This single channel algorithm has larger retrieval error of AOD than other multiple-channel algorithm due to errors in surface reflectance and atmospheric property. In this study, the effects of manifold atmospheric and surface properties on the retrieval of AOD from the geostationary satellite, are investigated and compared with the AODs from AERONET and MODIS. To improve the accuracy of retrieved AOD, efforts were put together to minimize uncertainties through extensive sensitivity tests. This algorithm can be utilized to retrieve aerosol information from previous geostationary satellite for long-term climate studies.

• New & Renewable Energy
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• v.20 no.1
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• pp.79-87
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• 2024

This study introduces a method for estimating Aerosol Optical Depth (AOD) using Broadband Aerosol Optical Depth (BAOD) derived from direct normal irradiance and meteorological factors observed between 2016 and 2017. Through correlation analyses between BAOD and atmospheric components such as Rayleigh scattering, water vapor, and tropospheric nitrogen dioxide, significant relationships were identified, enabling accurate AOD estimation. The methodology demonstrated high correlation coefficients and low Root Mean Square Errors (RMSE) compared to actual AOD₅₀₀ measurements, indicating that the attenuation effects of water vapor and the direct impact of tropospheric nitrogen dioxide concentration are crucial for precise aerosol optical depth estimation. The application of BAOD for estimating AOD₅₀₀ across various time scales-hourly, daily, and monthly-showed the approach's robustness in understanding aerosol distributions and their optical properties, with a high coefficient of determination (0.96) for monthly average AOD₅₀₀ estimates. This study simplifies the aerosol monitoring process and enhances the accuracy and reliability of AOD estimations, offering valuable insights into aerosol research and its implications for climate modeling and air quality assessment. The findings underscore the viability of using BAOD as a surrogate for direct AOD₅₀₀ measurements, presenting a promising avenue for more accessible and accurate aerosol monitoring practices, crucial for improving our understanding of aerosol dynamics and their environmental impacts.

• Journal of the Korean Society for information Management
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• v.15 no.1
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• pp.149-164
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• 1998

The study aims to construct a system which can provide multimedia materials, specifically, digitalized video and audio materials on the internet. To accomplish this objective, it investigates technology on constructing a VOD/AOD system, current situations on video and audio data management in domestic and internatinal broadcasting institution and information centers. The study proposes a VOD/AOD system which can effectively manage and disseminate these materials on the internet.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.