• Journal of the Korean earth science society
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• v.36 no.1
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• pp.109-124
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• 2015

A novel approach, hybrid surface rainfall (KNU-HSR) technique developed by Kyungpook Natinal University, was utilized for improving the radar rainfall estimation. The KNU-HSR technique estimates radar rainfall at a 2D hybrid surface consistings of the lowest radar bins that is immune to ground clutter contaminations and significant beam blockage. Two HSR techniques, static and dynamic HSRs, were compared and evaluated in this study. Static HSR technique utilizes beam blockage map and ground clutter map to yield the hybrid surface whereas dynamic HSR technique additionally applies quality index map that are derived from the fuzzy logic algorithm for a quality control in real time. The performances of two HSRs were evaluated by correlation coefficient (CORR), total ratio (RATIO), mean bias (BIAS), normalized standard deviation (NSD), and mean relative error (MRE) for ten rain cases. Dynamic HSR (CORR=0.88, BIAS= $-0.24mm\;hr^{-1}$, NSD=0.41, MRE=37.6%) shows better performances than static HSR without correction of reflectivity calibration bias (CORR=0.87, BIAS= $-2.94mm\;hr^{-1}$, NSD=0.76, MRE=58.4%) for all skill scores. Dynamic HSR technique overestimates surface rainfall at near range whereas it underestimates rainfall at far ranges due to the effects of beam broadening and increasing the radar beam height. In terms of NSD and MRE, dynamic HSR shows the best results regardless of the distance from radar. Static HSR significantly overestimates a surface rainfall at weaker rainfall intensity. However, RATIO of dynamic HSR remains almost 1.0 for all ranges of rainfall intensity. After correcting system bias of reflectivity, NSD and MRE of dynamic HSR are improved by about 20 and 15%, respectively.

• Journal of the Korean earth science society
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• v.30 no.6
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• pp.721-733
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• 2009

A pattern of tropical cyclone (TC) movement in the western North Pacific area was studied using the empirical orthogonal function (EOF) and the best track data from 1951 to 2007. The independent variable used in this study was defined as the frequency of tropical cyclone passage in 5 by 5 degree grid. The $1^{st}$, $2^{nd}$ and $3^{rd}$ modes were the east-west, north-south and diagonal variation patterns. Based on the time series of each component, the signs of first and second mode changed in 1997 and 1991, respectively, which seems to be related to the fact that the passage frequency was higher in the South China Sea for 20 years before 1990s, and recent 20 years in the East Asian area. When the eigen vectors were negative values in the first and second modes and TC moves into the western North Pacific, TC was formed mainly at the east side relatively compared to the case of the positive eigen vectors. The first mode seems to relate to the pressure pattern at the south of Lake Baikal, the second mode the variation pattern around $30^{\circ}N$, and the third mode the pressure pattern around Japan. The first mode was also closely related to the ENSO and negatively related to the $Ni\tilde{n}o$-3.4 index in the correlation analysis with SST anomalies.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.121-135
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• 2024

This study examined the influence of near-surface atmospheric warming in the Arctic-East Asia region during spring (March-May) from 1991 to 2020 on the synoptic-scale meteorology of dust storm-induced dust days in Seoul, Korea, in response to the Arctic Oscillation. Increased springtime warming in the Arctic-East Asia region correlated with a reduction of six days in the occurrence of dust storm-induced dust days in Seoul, Korea, along with a decline in the intensity of these days by -1.6 ㎍ m^-3yr^-1 in PM₁₀ mass concentration. The declining number of dust storm-induced dust days in Korea during the 2010s was the result of synoptic-scale meteorological analysis, which showed increased high-pressure activity as indicated by the negative potential vorticity unit. Moreover, a distinct pattern emerged in the distribution of dust storm-induced dust days in Korea based on the Arctic Oscillation Index (AOI), showing an increase in negative AOI and a decrease in positive AOI. Although the northward shift of the polar jet weakened the southerly low-pressure system activity over Mongolia and northern China, a reinforced high-pressure system formed over the Chinese continent during dust-storm-induced dust days with a negative AOI. This resulted in both a decrease in the frequency of dust-storm-induced dust days and reduction in wind speeds, facilitating their transport from source regions to Korea. Conversely, on days with positive AOIs, an extensive warm and stagnant high-pressure system dominated mainland China, accompanied by further cooling of the northern segment of the polar jet. A notable decline in wind speed in the lower troposphere across the Mongolia-northern China-Korea region diminished the occurrence of dust storm-induced dust days and also weakened their long-range transport.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.5
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• pp.637-648
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• 2024

The frequency of extreme weather events such as heavy and extreme rainfall has been increasing due to global climate change. Accordingly, it is essential to quantify hydrometeorological variables for efficient water resource management. Among the various hydro-meteorological variables, Land Surface Temperature (LST) and Evapotranspiration (ET) play key roles in understanding the interaction between the surface and the atmosphere. In Korea, LST and ET are mainly observed through ground-based stations, which also have limitation in obtaining data from ungauged watersheds, and thus, it hinders to estimate spatial behavior of LST and ET. Alternatively, remote sensing-based methods have been used to overcome the limitation of ground-based stations. In this study, we evaluated the applicability of the National Aeronautics and Space Administration's (NASA) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) LST and ET data estimated across Korea (from July 1, 2018 to December 31, 2022). For validation, we utilized NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) data and eddy covariance flux tower observations managed by agencies under the Ministry of Environment of South Korea. Overall, results indicated that ECOSTRESS-based LSTs showed similar temporal trends (R: 0.47~0.73) to MODIS and ground-based observations. The index of agreement also showed a good agreement of ECOSTRESS-based LST with reference datasets (ranging from 0.82 to 0.91), although it also revealed distinctive uncertainties depending on the season. The ECOSTRESS-based ET demonstrated the capability to capture the temporal trends observed in MODIS and ground-based ET data, but higher Mean Absolute Error and Root Mean Square Error were also exhibited. This is likely due to the low acquisition rate of the ECOSTRESS data and environmental factors such as cooling effect of evapotranspiration, overestimation during the morning. This study suggests conducting additional validation of ECOSTRESS-based LST and ET, particularly in topographical and hydrological aspects. Such validation efforts could enhance the practical application of ECOSTRESS for estimating basin-scale LST and ET in Korea.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.14 no.1
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• pp.1-14
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• 1978

To study the fluctuation of cold water in the East China Sea in summer heat budget of the Yellow Sea in winter was analysed based on the oceanographic and meteorological data compiled from 1951 to 1974. The maintain value of insolation was observed in December($160{\sim}190ly/day$), while the maximum in February ($250{\sim}260ly/day$). The range of the annual variation was found to be less than 50 ly/day. The value of the radiation term ($Q_s-Q_r-Q_h$) was remarkably small (mean 20 ly/day) in winter. It was negative value in December and January, and a positive value in February. The minimum total heat exchange from the sea ($Q_({h+c}$) was found value (471 ly/day) in February 1962, and the maximum (882 ly/day) in January 1963. The annual total heat exchange was minimum (588 ly/day) in 1962, and maximum (716 ly/day) in 1968. If the average deviation of mean water temperature at 50m depth layer were assumed to be the horizontal index ($C_h$) of colder water, $C_h$ is $C_h=\frac{{\Sigma}\limit_i\;A_i\;T_i}{{\Sigma}\limit_i\;A_i}$ where $A_i$ denotes the area of isothermal region and $T_i$ the value of deviation from mean sea water temperature. The vertical index ($C_v$) of cold water can be expressed similarly. Consequently the total index (C) of cold water equals to the sum of the two components, i.e. $C=C_h$＋$C_v$. Taking the deviation of mean sea surface temperature(T'w) in the third ten-day of Novembers in the Yellow Sea as the value of the initial condition, the following expressions are deduced : $C－T'w＝32.06 - 0.049$ $\;Q_T$ $C_h-T'w/2=12.20-0.019\;Q_T$ $C_v-T'w/2＝18.07-0.027\;Q_T$ where $Q_T$ denotes the total heat exchange of the sea. The correlation coefficients of these regression equations were found to be greater than 0.9. Heat budget was 588 ly/day in winter, and minimum water temperature of cold water was $18^{\circ}C$ in summer of 1962. The isotherm of $23^{\circ}C$ extended narrowly to southward up to $29^{\circ}N$ in summer. However, heat budget was 716 ly/day, and minimum water temperature of cold water was $12^{\circ}C$ in summer of 1968. The isotherm of $23^{\circ}C$ extended widely to southward up to $28^{\circ}30'N$ in summer. As a result of the present study, it may be concluded that the fluctuation of cold water of the East China Sea in summer can be predicted by the calculation of heat budget of the Yellow Sea in winter.

• Journal of Korean Society of Forest Science
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• v.43 no.1
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• pp.20-30
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• 1979

The purpose of present study is to analyze the genetic variation of natural stand of Pinus densiflora. In 1976 following after the seletion of 1974 and 1975, twenty trees from each of three natural populations of the species were selected and seeds were collected, and the locations and conditions of populations are presented in table 1, 2 and figure 1. Some morphological traits of the populations were already detailed in our fifth report of this series. The morphological traits of cone, seed and seed-wing, and also the growth performances and needle characters of the seedling were observed in the present study according to the previous methods. The results obtained are summarized as follows; 1. The meteorological data obtained by averaging the records of 30 year period(1931~1960) measured from the nearest meteorological station to each population are shown in fig. 2, 3, 4. The distributional patterns of investigated climate factors are generally considered to be similar among the locations. However, the precipitation density during growing season and the air temperature during dormant season on Samchuk area (Pop. 9) were quite different from those of the other areas. 2. The measurements of fresh cone weight, length, diameter and cone index (i.e.: length to diameter ratio) are presented in table 7. As shown in table 7, all these traits except for cone diameter seem to be not significant in population and to be highly significant in family differences within population. 3. The morohological traits of seed and seed-wing are detailed in table 8, 9, and highly significant differences are recognized among the populations and the families within population in seed weight, seed length, seed thickness but not among the populations in the other observed traits. The values of correlation between the characteristics of cone and seed are presented in table 12. As shown, the correlation between cone length and seed wing length, between seed wing width and seed width were significantly positive in population 8 and 9 but in population 7. The positive correlations between seed length and seed width were calculated in all populations studied 4. Significant statistical differences among populations and families within population are observed in the growth performances of 1-0 seedling height of these progenies. But the differences in 1-1 seedling height and root collar diameter are shown only among familes within population. As shown in table 13, the most parts of correlations are not significant statistically between the growth performances of seedling and the seed characters. 5. As shown in table 15, statistical differences are considered to be significant among the populations in stomata row on both sides of the needle but not in serration density. The correlations between progenies and parents are not generally observed in the investigated traits of needle as shown in table 16.

• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.3
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• pp.25-37
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• 1988

The purpose of this study is to fmd out the bask data for irrigation plans of tomato and chinese cabbage during the growing period, such as total amount of evapotranspiration, coefficients of evapotranspiration at each growth stage, the peak stage of evapotranspiration, the maximum evapotranspiration, optimum irrigation point, total readily available moisture and intervals of irrigation date. The plots of experiment were arranged with split plot design which were composed of two factors, irrigation point for main plot and soji texture for split plot, and three levels, irrigation points with PF 1.8, PF 2.2, PF 2.6 for tomato and those with PF 1.9, PF 2.3, PF 2.7, for Chinese cabbage, soil textures of silty clay, sandy loam and sandy soil for both tomato and Chinese cabbage, with two replications. The results obtained are summarized as follows 1. There was the highest significant correlation between the evapotranspiration and the pan evaporation, beyond all other meteoralogical factors considered. Therefore, the pan evaporation is enough to be used as a meteorological index measuring the quantity of evapotranspiration. 2. 1/10 probability values of maximum total pan evaporation during growing period for tomato and Chinese cabbage were shown as 355.8 mm and 233.0 mm, respectively, and those of maximum ten day pan evaporation for tomato and Chinese cabbage, 68.0 mm and 43.8 mm, respectively. 3. The time that annual maximum of ten day pan evaporation can be occurred, exists at any stage of growing period for tomato, and at any growth stage till the late of Septemberfor Chinese cabbage. 4. The magnitude of evapotranspiration and of its coefficient for tomato and Chinese cabbage was occurred in the order of pF 1.8>pF 2.2>pF 2.6 and of pF 1.9>pF 2.3>pF 2.7 respectively in aspect of irrigation point and of silty clay>sandy loam>sandy soil in aspect of soil texture. 5. 1/10 probability value of evapotranspiration and its coefficient during the growing period of tomato were shown as 327.3 mm and 0.92 respectively, while those of Chinese cabbage, 261.0 mm and 1.12 respectively. 6. The time that maximum evapotranspiration of tomato can be occurred is at the date of fortieth to fiftieth after transplanting and the time for Chinese cabbage is presumed to he in the late of septemben At that time, 1/10 probability value of ten day evapotranspiration and its coefficient for tomato is presumed to be 74.8 mm and 1.10 respectively, while those of Chinese cabbage, 43.8 mm and 1.00. 7. In aspect of only irrigaton point, the weight of raw tomato and Chinese cabbage were mcreased in the order of pF 2.2>pF 1.8>pF 2.6 and of pF 1.9>pF 2.3>pF 2.7, respectively but optimum irrigation point for tomato and Chinese cabbage, is presumed to be pF 2.6 - 2.7 if nonsignificance of the yield between the different irrigation treatments, economy of water, and reduction in labour of irrigaion are synthetically considered. 8. The soil moisture extraction patterns of tomato and Chinese cabbage have shown that maximum extraction rate exists at 7 cm deep layer at the beginning stage of growth m any soil texture and that extraction rates of 21 cm to 35 cm deep layer are increased as getting closer to the late stage of growth. And especially the extraction rates of 21 cm deep layer and 35 cm deep layer have shown tendency to be more increased in silty clay than in any other soils. 9. As optimum irrigation point is presumed to be pF Z6-2.7, total readily available moisture of tomato in silty clay, sandy loam and sandy sofl becomes to be 19.06 mm, 21.37 mm and 20.91 mm respectively while that of Chinese cabbage, 18.51 mm, 20.27 mm, 21.11 mm respectively. 10. On the basis of optimum irrigation point with pF 2.6 - 2.7 the intervals of irrigation date of tomato and Chinese cabbage at the growth stage of maximum consumptive use become to be three days and five days respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.111-124
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• 2010

To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.109-126
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• 2014

We improved the Land Surface Emissivity (LSE) data (Kongju National University LSE v.2: KNULSE_v2) over the Communication, Ocean and Meteorological Satellite (COMS) observation region using recent(2009-2012) Moderate Resolution Imaging Spectroradiometer (MODIS) data. The surface emissivity was derived using the Vegetation Cover Method (VCM) based on the assumption that the pixel is only composed of ground and vegetation. The main issues addressed in this study are as follows: 1) the impacts of snow cover are included using Normalized Difference Snow Index (NDSI) data, 2) the number of channels is extended from two (11, 12 ${\mu}m$) to four channels (3.7, 8.7, 11, 12 ${\mu}m$), 3) the land cover map data is also updated using the optimized remapping of the five state-of-the-art land cover maps, and 4) the latest look-up table for the emissivity of land surface according to the land cover is used. The updated emissivity data showed a strong seasonal variation with high and low values for the summer and winter, respectively. However, the surface emissivity over the desert or evergreen tree areas showed a relatively weak seasonal variation irrespective of the channels. The snow cover generally increases the emissivity of 3.7, 8.7, and 11 ${\mu}m$ but decreases that of 12 ${\mu}m$. As the results show, the pattern correlation between the updated emissivity data and the MODIS LSE data is clearly increased for the winter season, in particular, the 11 ${\mu}m$. However, the differences between the two emissivity data are slightly increased with a maximum increase in the 3.7 ${\mu}m$. The emissivity data updated in this study can be used for the improvement of accuracy of land surface temperature derived from the infrared channel data of COMS.