• 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.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.589-601
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• 2023

We compare high-resolution seabed bathymetry data and seafloor backscattering data acquired, using multi-beam, between 2018 and 2021 to understand topographic changes in the coastal area of Dokdo. The study area, conducted within a 500 m × 500 m in the southern coast between the islands where Dongdo Port is located, has been greatly affected by human activities, waves and ocean currents. The depth variations exhibit between 5 - 70 m. Irregular underwater rocks are distributed in areas with a depth of 20 m or less and 30 - 40 m. As a whole, water depth ranges similar in the east-west direction and become flatter and deeper. The bathymetry contour in 2020 tends to move south as a whole compared to 2018 and 2019. The south moving of the contours in the survey area indicates that the water depth is shallower than before. Since the area where the change in the depth occurred is mainly formed of sedimentary layers, the change in the coast of Dokdo were mainly caused by the inflow of sediments, due to the influence of wind and waves caused by these typhoons (Maysak and Haishen) in 2020. In the Talus area, which developed on the shallow coast between Dongdo and Seodo, the bathymetry changed in 2020 due to erosion or sedimentation, compared to the bathymetry in 2019 and 2018. It is inferred that the changes in the seabed environment occur as the coastal area is directly affected by the typhoons. Due to the influence of the typhoons with strong southerly winds, there was a large amount of sediment inflow, and the overall tendency of the changes was to be deposited. The contours in 2021 appears to have shifted mainly northward, compared to 2020, meaning the area has eroded more than 2020. In 2020, sediments were mainly moved northward and deposited on the coast of Dokdo by the successive typhoons. On the contrary, the coast of Dokdo was eroded as these sediments moved south again in 2021. Dokdo has been largely affected by the north wind in winter, so sediments mainly move southward. But it is understood that sediments move northward when affected by strong typhoons. Such continuous coastal change monitoring and analysis results will be used as important data for longterm conservation policies in relation to topographical changes in Dokdo.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.229-241
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• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.32 no.6
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• pp.737-747
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• 1999

To estimate biomass and distribution of the Antarctic krill (Euphausia superba), hydroacoustic survey was conducted on board of R/V Yuzhmorgeologiya, which was chartered by Korea Antarctic Research Program (KARP) group from 18 to 21 December 1998, in the northern part of the South Shetland Islands, Antarctic Ocean, The scientific echo sounder (towing body type) used was EK- 500 (SIMRAD, Norway) with echo integrator (BI-500) at 38 kHz frequency and recorded mean backscattering cross-section coefficient (SA) per 1 $mile^2$ of sea surface. Also, Bongo net sampling was carried out to determine the size of krill and CTD (Conductivity, Temperature and Depth) casting to understand physical structure. Water column was divided into 5 layers (22$\~$65 m, 65$\~$115 m, l15$\~$65 m, 165$\~$215 m and 215$\~$315 m) to know vertical distribution of krill biomass. The standard length of krill collected was between 30 mm and 51 mm, and adult krill had single mode (41 mm). Maximum horizontal length of krill patch was about 35 nautical mile and vertical thickness was about 275 m. High density of krill was appeared in frontal area between Circumpolar Deep Water (>$1^{\circ}C$) and very low temperature water mass (< $-0.5^{\circ}C$) that originate from Weddell Sea. According to the results calculated using target strength equation, krill density was totally higher in continental slope and open water areas than in coastal area. In the study area, krill seems to distribute in depth; density was low at first layer ($\={\rho}=17.0\;g/m^2$) and higher at fourth layer ($\={\rho}=40.19\;g/m^2$). The estimated krill biomass at total survey area and water column was about 2.77 million metric ion ($\={\rho}=151.0\;g/m^2$) and coefficient of valiance ( CV, $\%$) was 19.92. The proportions and biomass of krill biomass at each layer were as follows; layer 1 ($11.3\%$, 0.31 million metric ton, CV=16.24), layer 2 ($13.3\%$, 0.37 million metric ton, CV=34.91), layer 3 ($23.7\%$, 0.66 million metric ton, CV=41.5), layer 4 ($26.6\%$, 0.74 million metric ton, CV=27.84) and layer 5 ($25\%$, 0.69 million metric ton, CV= 26.83).

• Radiation Oncology Journal
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• v.1 no.1
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• pp.21-24
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• 1983

The thickness of the part being irradiated is finite. Percent depth dose tables being used routinely are generally obtained from dosimetry in a phantom much thickner than usual patient. At or close to exit surface, the dose should be less than that obtained from the percent depth dose tables, because of insufficient volume for backscattering. To know the difference between the true absorbed dose and the dose obtained from percent depth dose table, the doses at or close to the exit surface were measured with plate type ionization chamber with volume of 0.5ml. The results are as follows; 1. In the case of $^{60}Co$, percent depth dose at a given depth increases with underlying phantom thickness up to the 5cm. 2. In the case of $^{60}Co$, the dose correction factor at exit surface which is less than 1, increases with part thickness and decreases with field size. 3. Exposure time may not be corrected when the part above 10cm in thickness is treated by $^{60}Co$. 4. In the case of 10MV x-ray, the dose correction factor is nearly 1 and constant for the underlying phantom thickness and field size, so the correction of monitor unit is not necessary for part thickness.

• 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.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.205-214
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• 2015

In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

• 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.