• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.381-384
• /
• 2005

We have applied the TOMS aerosols retrieval algorithm to GLI measurements. TOMS has utilized the aerosol index, which is a measure of the change in spectral contrast due to the wavelength-dependent effects of aerosols. We have retrieved the GLI aerosol index, which is made by the pair of 380/400nm, 380/412nm, 380/460nm, and 412/460nm. We have found that the biomass burning aerosols represent the absorbing aerosols. In addition, the pair of 380/460nm has shown the best signal for detecting aerosols in Principal Component Analysis(PCA) and comparison of aerosol optical thickness from AERONET data. The theoretical aerosol index is also shown the best signal in the pair of 380/460nm.

• Asian Journal of Atmospheric Environment
• /
• v.9 no.1
• /
• pp.91-99
• /
• 2015

The Multi-wavelength Raman LIDAR (MRL) system was developed to enable a better understanding of the complex properties of aerosols in the atmosphere. In this study, the microphysical, optical, and radiative properties of mixed aerosols were retrieved using the discrete aerosol observation products from the MRL. The dust mixing ratio, which is the proportion of dust particles to the total mixed, was derived using the particle depolarization ratio. It was employed in the retrieval of backscattering and extinction coefficient profiles for dust and non-dust particles. The vertical profiles of aerosol optical properties were then used as input parameters in the inversion algorithm for the retrieval of microphysical parameters including the effective radius, refractive index, and the single scattering albedo (SSA). Those products were successfully applied to an analysis of radiative flux using a radiative transfer model. The relationship between the MRL derived extinction and aerosol radiative forcing (ARF) in short-wavelength was assessed over Gwangju, Korea. The results clearly demonstrate that the MRL-derived extinction profiles are a good surrogate for use in the estimation of optical, microphysical, and radiative properties of aerosols. It is considered that the analytical results shown in this study can be used to provide a better understanding of air quality and the variation of local radiative effects due to aerosols.

• Asian Journal of Atmospheric Environment
• /
• v.5 no.2
• /
• pp.79-85
• /
• 2011

The purpose of this study is to evaluate the strength of the near-UV wavelength of 380 nm relative to visible and near-IR bands, and to find the suitable wavelength for detecting aerosols by using the Global Imager (GLI) sensor aboard the Advanced Earth Observing Satellite-II (ADEOS-II). Sensitivity analysis is performed for the retrieval of biomass burning aerosols by employing the radiative transfer model Rstar5b. It is determined that background surface reflectance in the blue band is similar to that in the near-UV band, and that wavelengths in the blue bands are more sensitive to the Aerosol Optical Thickness (AOT) than wavelengths in the near-UV band. The Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) is used in the indirect method used for aerosol retrieval, and the wavelength pair 380 nm and 460 nm is determined to be the most sensitive to the AOT. The results of this study suggest that wavelengths in the blue bands are suitable for detecting biomass burning aerosols over the Korean peninsula.

• Environmental Engineering Research
• /
• v.22 no.1
• /
• pp.75-86
• /
• 2017

The aerosol content dynamics in a virtual system were investigated. The outcome was extended to monitor the mean concentration diffusion of aerosols in a predefined macro and micro scale. The data set used were wind data set from the automatic weather station; satellite data set from Total Ozone Mapping Spectrometer aerosol index and multi-angle imaging spectroradiometer; ground data set from Aerosol robotic network. The maximum speed of the macro scale (West Africa) was less than 4.4 m/s. This low speed enables the pollutants to acquire maximum range of about 15 km. The heterogeneous nature of aerosols layer in the West African atmosphere creates strange transport pattern caused by multiple refractivity. It is believed that the multiple refractive concepts inhibit aerosol optical depth data retrieval. It was also discovered that the build-up of the purported strange transport pattern with time has enormous potential to influence higher degrees of climatic change in the long term. Even when the African Easterly Jet drives the aerosols layer at about 10 m/s, the interacting layers of aerosols are compelled to mitigate its speed to about 4.2 m/s (macro scale level) and boost its speed to 30 m/s on the micro scale level. Mean concentration diffusion of aerosols was higher in the micro scale than the macro scale level. The minimum aerosol content dynamics for non-decaying, logarithmic decay and exponential decay particulates dispersion is given as 4, 1.4 and 0 respectively.

• Journal of Korean Society for Atmospheric Environment
• /
• v.27 no.3
• /
• pp.326-336
• /
• 2011

The Light Detection and Ranging (Lidar) observation provides a specific knowledge of the temporal and vertical distribution and the optical properties of the aerosols. Unlike typical Mie scattering Lidars, which can measure backscattering and depolarization, the Raman Lidar can measure the quartz signal at the ultra violet (360 nm) and the visible (546 nm) wavelengths. In this work, we developed a method for estimating mineral quartz concentration immersed in Asian dust using Raman scattering of quartz (silicon dioxide, silica). During the Asian dust period of March 15, 16, and 21 in 2010, Raman lidar measurements detected the presence of quartz, and successfully showed the vertical profile of the dust concentrations. The satellite observations such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) confirmed spatial distribution of Asian dust. This approach will be useful for characterizing the quartz dominated in the atmospheric aerosols and the investigations of mineral dust. It will be especially applicable for distinguishing the dust and non-dust aerosols in studies on the mixing state of Asian aerosols. Additionally, the presented method combined with satellite observations is enable qualitative and quantitative monitoring for Asian dust.

• Proceedings of the KSRS Conference
• /
• 2006.03a
• /
• pp.341-343
• /
• 2006

The current spectral shape matching method (SSMM), developed by Ahn and Shanmugam (2004), relies on the assumption that the path radiance resulting from scattered photons due to air molecules and aerosols and possibly direct-reflected light from the air-sea interface is spatially homogeneous over the sub-scene of interest, enabling the retrieval of water-leaving radiances ($L_w$) from the satellite ocean color image data. This assumption remains valid for the clear atmospheric conditions, but when the distribution of aerosol loadings varies dramatically the above postulation of spatial homogeneity will be violated. In this study, we present the second version of SSMM which will take into account the horizontal variations of aerosol loading in the correction of atmospheric effects in SeaWiFS ocean color image data. The new version includes models for the correction of the effects of aerosols and Raleigh particles and a method fur computation of diffuse transmittance ($t_{os}$) as similar to SeaWiFS. We tested this method over the different optical environments and compared its effectiveness with the results of standard atmospheric correction (SAC) algorithm (Gordon and Wang, 1994) and those from in-situ observations. Findings revealed that the SAC algorithm appeared to distort the spectral shape of water-leaving radiance spectra in suspended sediments (SS) and algal bloom dominated-areas and frequently yielded underestimated or often negative values in the lower green and blue part of the electromagnetic spectrum. Retrieval of water-leaving radiances in coastal waters with very high sediments, for instance = > 8g $m^{-3}$, was not possible with the SAC algorithm. As the current SAC algorithm does not include models for the Asian aerosols, the water-leaving radiances over the aerosol-dominated areas could not be retrieved from the image and large errors often resulted from an inappropriate extrapolation of the estimated aerosol radiance from two IR bands to visible spectrum. In contrast to the above results, the new SSMM enabled accurate retrieval of water-leaving radiances in a various range of turbid waters with SS concentrations from 1 to 100 g $m^{-3}$ that closely matched with those from the in-situ observations. Regardless of the spectral band, the RMS error deviation was minimum of 0.003 and maximum of 0.46, in contrast with those of 0.26 and 0.81, respectively, for SAC algorithm. The new SSMM also remove all aerosol effects excluding areas for which the signal-to-noise ratio is much lower than the water signal.

• Korean Journal of Remote Sensing
• /
• v.21 no.4
• /
• pp.273-285
• /
• 2005

This study has investigated the suitable wavelength for detecting biomass burning aerosols. We have performed the analysis of the wavelength at 380nm in near-UV, 400nm, 412nm, 460nm, and 490nm in visible, and 2100nm in shortwave infrared regions from the Global Imager measurements. It is well known that the UV bands have the advantage of the aerosols retrieval due to the low surface reflectance and a weak effect of Bidirectional Reflectivity Distribution Function. However, the pure surface reflectances of shortwave visible bands, except 412nm, are as low as that of 380nm in near-UV over northeast Asia. In order to detect the aerosol signal, we have retrieved the aerosol reflectance as a function of wavelength based on the surface reflectivity contrast method for the period of May 2003. It is interesting that the retrieved aerosol reflectance with 460nm is slightly more sensitive than that with 380nm. Additionally, we have applied the TOMS aerosol index method to determine the best pair for biomass burning aerosols and found that the pair of 380 and 460nm results in the best signal for retrieving aerosols.

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

• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1697-1707
• /
• 2021

On 19 February 2020, the 2nd Geostationary Ocean Color Imager (GOCI-II), a maritime sensor of GEO-KOMPSAT-2B, was launched. The GOCI-II instrument expands the scope of aerosol retrieval research with its improved performance compared to the former instrument (GOCI). In particular, the newly included UV band at 380 nm plays a significant role in improving the sensitivity of GOCI-II observations to the absorbing aerosols. In this study, we calculated the aerosol index and detected absorbing aerosols from January to June 2021 using GOCI-II 380 and 412 nm channels. Compared to the TROPOMI aerosol index, the GOCI-II aerosol index showed a positive bias, but the dust pixels still could be clearly distinguished from the cloud and clear pixels. The high GOCI-II aerosol index coincided with ground-based observations indicating dust aerosols were detected. We found that 70.5% of dust and 80% of moderately-absorbing fine aerosols detected from the ground had GOCI-II aerosol indices larger than the 75th percentile through the whole study period.

• Korean Journal of Remote Sensing
• /
• v.24 no.6
• /
• pp.559-569
• /
• 2008

The Geostationary Ocean Color Imager (GOCI) on board the Communication Ocean Meteorological Satellite (COMS), the first geostationary ocean color sensor, requires accurate atmospheric correction since its eight bands are also affected by atmospheric constituents such as gases, molecules and atmospheric aerosols. Unlike gases and molecules in the atmosphere, aerosols can interact with sunlight by complex scattering and absorption properties. For the purpose of qualified ocean remote sensing, understanding of aerosol-radiation interactions is needed. In this study, we show micro-physical and optical properties of aerosols using the Optical Property of Aerosol and Cloud (OPAC) aerosol models. Aerosol optical properties, then, were used to analysis the relationship between theoretical satellite measured radiation from radiative transfer calculations and aerosol optical thickness (AOT) under various environments (aerosol type and loadings). It is found that the choice of aerosol type makes little different in AOT retrieval for AOT<0.2. Otherwise AOT differences between true and retrieved increase as AOT increases. Furthermore, the differences between the AOT and angstrom exponent from standard algorithms and this study, and the comparison with ground based sunphotometer observations are investigated. Over the northeast Asian region, these comparisons suggest that spatially averaged mean AOT retrieved from this study is much better than from standard ocean color algorithm. Finally, these results will be useful for aerosol retrieval or atmospheric correction of COMS/GOCI data processing.