• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1793-1801
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• 2021

From 2015 to June 2020, the backscattering coefficients of 532 and 1064 nm measured using LIDAR and the depolarization ratio at 532 nm were used to separate the backscattering coefficient at 532 nm as three types as PM₁₀, PM_2.5-10, PM_2.5 according to particle size. The mass extinction efficiency (MEE) of three types was calculated using the mass concentration measured on the ground. The overall mean values of the calculated MEE were 5.1 ± 2.5, 1.7 ± 3.7, and 9.3 ± 6.3 m²/g in PM₁₀, PM_2.5-10, and PM_2.5, respectively. When the mass concentration of PM₁₀ and PM_2.5 was low, higher than average MEE was calculated, and it was confirmed that the MEE decreased as the mass concentration increased. When the MEE was calculated for each type according to the mixing degree of Asian dust, PM_2.5-10 was twice at pollution aerosol as high as 2.1 ± 2.8 m²/g, compare to pollution-dominated mixture, dust-dominated mixture, and pure dust of 1.1 ± 1.8, 1.4 ± 3.3, 1.1 ± 1.5 m²/g, respectively. However, PM_2.5 MEE showed similar values irrespective of type: 9.4 ± 6.5, 9.0 ± 5.8, 10.3 ± 7.5, and 9.1 ± 9.0 m²/g. The MEE of PM₁₀ was 5.6 ± 2.9, 4.4 ± 2.0, 3.6 ± 2.9, and 2.8 ± 2.4 m²/g in pollution aerosol (PA), pollution-dominated mixture (PDM), dust-dominated mixture (DDM), and pure dust (PD), respectively, and increased as the dust ratio value decreased. Even if the same type according to the same mass concentration or Asian dust mixture was shown, as the PM_2.5/PM₁₀ ratio decreased, the MEE of PM_2.5-10 decreased and the MEE of PM_2.5 showed a tendency to increase.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1457-1468
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• 2018

The sigma naught (${\sigma}^0$) equation is essential to calculate geo-physical properties from Synthetic Aperture Radar (SAR) images for the applications such as ground target identification,surface classification, sea wind speed calculation, and soil moisture estimation. In this paper, we are suggesting new Kompsat-5 (K5) Radar Cross Section (RCS) and ${\sigma}^0$ equations reflecting the final SAR processor update and absolute radiometric calibration in order to increase the application of K5 SAR images. Firstly, we analyzed the accuracy of the K5 RCS equation by using trihedral corner reflectors installed in the Kompsat calibration site in Mongolia. The average difference between the calculated values using RCS equation and the measured values with K5 SAR processor was about $0.2dBm^2$ for Spotlight and Stripmap imaging modes. In addition, the verification of the K5 ${\sigma}^0$ equation was carried out using the TerraSAR-X (TSX) and Sentinel-1A (S-1A) SAR images over Amazon rainforest, where the backscattering characteristics are not significantly affected by the seasonal change. The calculated ${\sigma}^0$ difference between K5 and TSX/S-1A was less than 0.6 dB. Considering the K5 absolute radiometric accuracy requirement, which is 2.0 dB ($1{\sigma}$), the average difference of $0.2dBm^2$ for RCS equation and the maximum difference of 0.6 dB for ${\sigma}^0$ equation show that the accuracies of the suggested equations are relatively high. In the future, the validity of the suggested RCS and ${\sigma}^0$ equations is expected to be verified through the application such as sea wind speed calculation, where quantitative analysis is possible.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.1
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• pp.32-39
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• 2013

Although space-borne satellites are useful in obtaining information all around the world, they cannot observe at a suitable time and place. In order to overcome these limitations, an airborne remote sensing system was developed in this study. It is composed of a SAR sensor and a thermal infrared sensor. Additionally GPS, IMU, and thermometer/hygrometer were attached to the plane for radiometric and geometric calibration. The brightness of SAR image varies depending on surface roughness, and capillary waves on the sea surface, which are easily generated by sea winds, induce the surface roughness. Thus, sea surface wind can be estimated using the relationship between quantified SAR backscattering coefficient and the sea surface wind. On the other hand, thermal infrared sensor is sensitive to measure object's temperature. Sea surface temperature is obtained from the thermal infrared sensor after correcting the atmospheric effects which are located between sea surface and the sensor. Using these two remote sensing sensors mounted on airplane, four test flights were carried out along the west coast of Korea. The obtained SAR and thermal infrared images have shown that these images were useful enough to monitor coastal environment and estimate marine meteorology data.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.38 no.2
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• pp.140-148
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• 2002

The primary goal of this study is to determine the distribution characteristics using a scientific echo sounder in the Yellow Sea west of South Korea. The survey was carried out between 33$^{\circ}$00'N~37$^{\circ}$00'N latitude and 124$^{\circ}$00'E~126$^{\circ}$00'E longitude during the months of May and August, 1999 and April, 2000. The ships used in this survey were the R/V Chung-kyeong(G/T 300) and R/V Dong-baek(G/T 1,050) of Yeosu National University. The results obtained are as follows : 1. From the oceanographic data the Yellow Sea were divided into three sea areas which were the western waters of Chejudo, Mokpo and Kunsan. The oceanographic conditions were different in each of these three areas and the western waters of Chejudo were higher about 1~5$^{\circ}C$ more than the western waters of Gunsan. Generally, thermoclines were presented clearly in all three areas, but more so in August than in May according to seasons. 2. The horizontal distribution of S$_{A}$(area backscattering coefficient per unit area) value is that the western sea waters of Chejudo area are higher than that of the western sea waters of Mokpo and Gunsan. 3. The vortical distribution of S$_{A}$ value varies with thermocline that the harder thermocline is, the higher the S$_{A}$ value is. 4. The S$_{A}$ values on the types of biomass distribution are different with frequency. At the 38kHz, the demersal schools have higher values than the pelagic schools. At the 120kHz, the pelagic schools have higher values than the demersal schools.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.11-19
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• 2012

Air-borne pollen, biogenically created aerosol particle, influences Earth's radiative balance, visibility impairment, and human health. The importance of pollens has resulted in numerous experimental studies aimed at characterizing their dispersion and transport, as well as health effects. There is, however, limited scientific information concerning the optical properties of airborne pollen particles contributing to total ambient aerosols. In this study, for the first time, optical characteristics of pollen such as aerosol backscattering coefficient, aerosol extinction coefficient, and depolarization ratio at 532 nm and their effect to the atmospheric aerosol were studied by lidar remotes sensing technique. Dual-Lidar observations were carried out at the Gwangju Institute of Science & Technology (GIST) located in Gwagnju, Korea ($35.15^{\circ}E$, $126.53^{\circ}N$) for a spring pollen event from 5 to 7 May 2009. The pollen concentration was measured at the rooftop of Gwangju Bohoon hospital where the building is located 1.0 km apart from lidar site by using Burkard trap sampler. During intensive observation period, high pollen concentration was detected as 1360, 2696, and $1952m^{-3}$ in 5, 6, and 7 May, and increased lidar return signal below 1.5km altitude. Pollen optical depth retrieved from depolarization ratio was 0.036, 0.021, and 0.019 in 5, 6, and 7 May, respectively. Pollen particles mainly detected in daytime resulting increased aerosol optical depth and decrease of Angstrom exponent.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.497-508
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• 2023

Agricultural reservoirs are crucial structures for water resources monitoring especially in Korea where the resources are seasonally unevenly distributed. Optical and Synthetic Aperture Radar (SAR) satellites, being utilized as tools for monitoring the reservoirs, have unique limitations in that optical sensors are sensitive to weather conditions and SAR sensors are sensitive to noises and multiple scattering over dense vegetations. In this study, we tried to improve water body detection accuracy through optical-SAR data fusion, and quantitatively analyze the complementary effects. We first detected water bodies at Edong, Cheontae reservoir using the Compact Advanced Satellite 500(CAS500), Kompsat-3/3A, and Sentinel-2 derived Normalized Difference Water Index (NDWI), and SAR backscattering coefficient from Sentinel-1 by K-means clustering technique. After that, the improvements in accuracies were analyzed by applying K-means clustering to the 2-D grid space consists of NDWI and SAR. Kompsat-3/3A was found to have the best accuracy (0.98 at both reservoirs), followed by Sentinel-2(0.83 at Edong, 0.97 at Cheontae), Sentinel-1(both 0.93), and CAS500(0.69, 0.78). By applying K-means clustering to the 2-D space at Cheontae reservoir, accuracy of CAS500 was improved around 22%(resulting accuracy: 0.95) with improve in precision (85%) and degradation in recall (14%). Precision of Kompsat-3A (Sentinel-2) was improved 3%(5%), and recall was degraded 4%(7%). More precise water resources monitoring is expected to be possible with developments of high-resolution SAR satellites including CAS500-5, developments of image fusion and water body detection techniques.