• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.

• Journal of the Korean earth science society
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• v.37 no.1
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• pp.29-39
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• 2016

In this study, we estimated solar radiation by multiple regression analysis using sunshine duration and precipitation data, which are highly correlated to solar radiation. We found the regression equation using data obtained from GROM (Gangwon Regional Office of Metrology, station 105, 1980-2007) located in Gangneung, South Korea and validated the equation by applying data obtained from new GROM (newly relocated, station 104, 2009-2014) and data obtained from GWNU (Gangneung-Wonju National University, 2013-2014) located between stations 104 and 105. By using sunshine duration data alone, the estimation using data from station 104 resulted in a correlation coefficient of 0.96 and a standard error of $1.16MJm^{-2}$, which was similar to the previous results; the estimation using data from GWNU yielded better results with a correlation coefficient of 0.99 and a standard error of $0.57MJm^{-2}$. By using sunshine duration and precipitation data, the estimation (using data from station 104) yielded a correlation coefficient of 0.96 and a standard error of $0.99MJm^{-2}$, resulting in a lower standard error compared to what was obtained using sunshine duration data alone. The maximum solar radiation bias increased from -26.6% (March 2013) to -31.0% (February 2011) when both sunshine duration and precipitation data were incorporated into the estimation rather than when sunshine duration data alone was incorporated. This was attributed to the concentrated precipitation found during May and July-September, which resulted in negative coefficients of the estimating equation in other months. Therefore, the monthly average solar radiation should be estimated carefully when employing the monthly average precipitation for those places where precipitation is concentrated during summer, such as the Korean peninsula.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.251-262
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• 2010

In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

• Journal of Korean Ophthalmic Optics Society
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• v.13 no.4
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• pp.65-73
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• 2008

Purpose: The purpose of this study is to investigate the effect of age in the response to long-term overnight orthokeratology (OK) lens wearing. Methods: Among volunteers, ninety-five healthy subjects who had no eye diseases and could wear OK contact lens at least for 8 hours every day were divided into three groups children, youngsters and young adults. Unaided logMAR visual acuity, refractive error, apical corneal radius, corneal asphericity and central corneal thickness were measured with different period; before and after one day, one week, two weeks, one month, three months and six months of OK lens wear. Paired student t-test, ANOVA analysis and Pearson correlation were used with a critical p value of 0.05 for statistical analysis. Results: All groups showed statistically significant (p<0.001) improvement in unaided visual acuity, a trend for flattening in the apical corneal radius, decrease in central corneal thickness and less prolate after OK lens wear. The child group showed significantly rapid change (p<0.001) in visual acuity, and apical corneal radius showed that they reached the targeted refractive change earlier compared with youngster and adult groups. The visual effect of OK lens was significantly related with the change in central corneal thickness after long-term OK lens wear, especially in child and youngster group, and central corneal thickness were highly correlated with the targeted refractive change. Conclusions: Visual acuity change is statistically correlated with the central corneal thickness change, which is highly correlated with targeted refractive change in the long-term orthokeratology and younger lens wearers showed a rapid response to OK lens wear, suggesting a reduced epithelial response with increasing age. The results found this study extends our understanding and development in the long-term orthokeratology.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.2
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• pp.142-149
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• 1995

This study was conducted to investigate the relationships between yearly variation of climatic components and yearly variations of productivity in monoculture cotton. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components from the four varieties(Kinggus, Yongdang local. 113-4, 380) were collected from 1978 to 1992 in Mokpo area. The meteorological data gathered at the Mokpo Weather Station for the same period were used to find out the relationships between climatic components and productivity. Yearly variation of the amount of precipitation and number of stormy days in July are large with coefficients of the variations(C.V)84.89 and 97.05%, respectively, while yearly variation, of the average temperature, maximum temperature, minimum temperature from May to Sep. are relatively small. Seed cotton yield before frost in Sep. and Oct. very greatly with C.V. of 68.77, 78.52%, respectively. Number of boll bearing branches and lint percentage show more or less small in C.V. with 11.77 and 19.13%, respectively and flowering date and boll opening date show still less variation. Correlation coefficients between precipitation in May and number of boll bearing branches, duration of sunshine in July and number of bolls per plant, maximum temperature in July and total seed cotton before the frost in Sep., Oct., and Nov. evaporation in Aug. are positively sig-nificant at the 1% level. There are highly significantly positive correlated relationships among yield(total seed cotton) and yield components. Total seed cotton yield(Y) can be predicted by multiple regression equation with independent variables of climatic factors in July such as monthly averages of average temperature($X_1$), maximum temperature($X_2$) and minimum temperature($X_3$), monthly amount of precipitation ($X_4$), evaporation($X_5$), monthly average of relative humidity($X_6$), monthly hours with sunshine($X_7$) and number of rainy days($X_8$). The equation is estimatedas Y =-1080.8515 + 144.7133$X_1$+15.8722$X_2$ + 164.9367$X_3$ + 0.0802$X_4$ + 0.5932$X_5$ + 11.3373$X_6$ + 3.4683$X_7$- 9.0846$X_8$. Also, total seed cotton yield(Y) can be predicted by the same method with climatic components in Aug., Y =2835.2497 + 57.9134$X_1$ - 46.9055$X_2$ - 41.5886X$_3$ + 1.2559$X_5$ - 21.9687$X_6$ - 3.3763$X_7$- 4.1080$X_8$- 17.5586$X_9$. And the error between observed and theoretical yield were less with approached linear regression.

• Economic and Environmental Geology
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• v.43 no.1
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• pp.53-66
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• 2010

We report petrologic characteristics including $^{40}Ar-^{39}Ar$ absolute ages of the subsurface lavas recovered from borehole cores in two islets, Marado and Gapado, off the southwestern coast of Jeju in southernmost Korea and discuss on the volcanism in the region. The lavas in Gapado are apparently divided into one unit with bright colored, aphanitic texture and sheet jointed, and another unit with dark colored and massive. The outcrops often show differentially weathered pattern due to textural difference. While, the lavas in Marado have vesicular and glomerporphyric texture, even though each lava flow unit in Marado has slight unique texture with variation of vesicularity and phenocrysts. The chemical composition of rock core samples from Gapa borehole and Mara borehole shows that the lavas from Gapado and Marado are classified into basaltic trachyandesite($SiO_2$ 52.6-53.6 wt%, $Na_2O+K_2O$ 7.3-7.5 wt%) and tholeiitic andesite($SiO_2$ 51.7-52.8 wt%, $Na_2O+K_2O$ 3.6-4.1 wt%), respectively. The measured $^{40}Ar-^{39}Ar$ plateau ages range from $824{\pm}32\;Ka$(MSL -69 m) to $758{\pm}\;Ka$(MSL 19 m) for core samples of Gapa borehole and $259{\pm}168\;Ka$(MSL -26 m) for a core sample of Mara borehole, respectively. The absolute age of Gapado basaltic trachyandesite is well correlated with that of Sanbangsan trachyte(Won et al., 1986). Meanwhile, the age of a sample in Marado has $259{\pm}168\;Ka$(MSL -26 m) with poor plateau age formation and high error range. We report the data in caution but the rock composition and absolute age of Marado tholeiitic andesite are relatively correlated with those of lava units from Duksu and Sangmo-2 boreholes, indicating the volcanism during 260-150 Ka. On the basis of interpretation of occurrences of exposed and subsurface volcanic rocks of the study area, stratigraphic relationship with adjacent borehole cores and the bathymetry chart of surrounding area, it indicates that the lavas in Gapado were formed around 800 Ka during relatively early stage of volcanic activity in Jeju Island. Meanwhile, Marado may have originated around 260-150 Ka during relatively young stage of volcanism in Jeju Island. It is inferred that the volcanisms have originated in land and these islets were individual ancient volcanoes. The apparent topography has been re-shaped by tidal erosion due to transgression.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.5
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• pp.278-284
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• 2014

Water temperature due to climate change can be estimated using the air temperature because the air and water temperatures are closely related and the water temperatures have been widely used as the indicators of the environmental and ecological changes. It is highly necessary to estimate the frequency distribution of the air and water temperatures, for the climate change derives the change of the coastal water temperatures. In this study, the distribution function of the air temperatures is estimated by using the long-term coastal air temperature data sets in Korea. The candidate distribution function is the bi-modal distribution function used in the previous studies, such as Cho et al.(2003) on tidal elevation data and Jeong et al.(2013) on the coastal water temperature data. The parameters of the function are optimally estimated based on the least square method. It shows that the optimal parameters are highly correlated to the basic statistical informations, such as mean, standard deviation, and skewness coefficient. The RMS error of the parameter estimation using statistical information ranges is about 5 %. In addition, the bimodal distribution fits good to the overall frequency pattern of the air temperature. However, it can be regarded as the limitations that the distribution shows some mismatch with the rapid decreasing pattern in the high-temperature region and the some small peaks.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Journal of the Korean Chemical Society
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• v.54 no.1
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• pp.150-157
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• 2010

In this study, we investigated the differences of mapping understanding and the types of mapping errors by the levels of students' cognitive/affective variables and the relationships between mapping understanding and these variables in learning 'concentration and reaction rate' with analogy. After administering the tests regarding logical thinking ability, visual imagery ability, analogical reasoning ability, self efficacy, and need for cognition as pretests, students learned with analogy. Then, students' familiarity and mapping understanding were examined. Analyses of the results revealed that the scores of the mapping understanding for the students with higher levels of all cognitive/affective variables except visual imagery ability and familiarity were significantly higher than those for the students with lower levels. The differences in the types of the mapping errors such as overmapping, failure to map, impossible mapping, artificial mapping, mismapping, rash mapping, and retention of a base feature were also found by the levels of students' cognitive and affective variables. The scores of students' mapping understanding were positively correlated with those of all cognitive and affective variables. The results of multiple regression analysis indicated that students' science achievement, logical thinking ability, and familiarity were significant predictors of mapping understanding. Educational implications of these findings are discussed.

• Journal of Korean Ophthalmic Optics Society
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• v.19 no.2
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• pp.225-229
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• 2014

Purpose: The study was to analyze the correlation between kinetic visual acuity (KVA), visual acuity(static visual angle, SVA) and contrast sensitivity. Methods: Ninety-nine undergraduate students studying Ophthalmic Optics were fully corrected by the Topcon CV-3000 Phoropter. The contrast sensitivity was measured for the participants under the photopic condition ($100cd/m^2$) with Vector Vision CSV-1000E at 2.5 meter, while KVA was measured with KOWA AS-4A. The participants were classified into three groups L, M and H depending on the KVA (0.1~0.3, 0.31~0.6 and greater than 0.61, respectively) and were analyzed whether there was the correlation between the contrast sensitivity, visual acuity and refractive error. Results: The KVA was correlated with the contrast sensitivity for 3 cpd (r=0.26), for 6 cpd (r=0.48), for 12 cpd (r=0.38) and 18 cpd (r=0.47). Except for the low frequency of 3 cpd, they all were higher than the one of the SVA and the KVA (r = -0.37). The contrast sensitivity for 3, 6, 12 and 18 cpd was 59.41, 92.22, 38.41 and 14.39 in the group L, respectively. The contrast sensitivity in the group M was 66.03, 108.78, 53.51 and 19.20 and the one in the group H was 70.90, 146.10, 62.90 and 25.33 for 3, 6, 12 and 18 cpd, respectively. Conclusions: The correlation of the contrast sensitivity and the KVA was higher than the one of the contrast sensitivity and the SVA. It can be assumed that the contrast sensitivity will be high if the KVA is high, except for the case for low spatial frequency.