• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1165-1178
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• 2018

Collapse of an Antarctic ice shelf and its flow velocity changes has the potential to reduce the restraining stress to the seaward flow of the Antarctic Ice Sheet, which can cause sea level rising. In this study, variations in ice velocity from 2000 to 2017 for the Nansen Ice Shelf in East Antarctica that experienced a large-scale collapse in April 2016 were analyzed using Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) images. To extract ice velocity, image matching based on orientation correlation was applied to the image pairs of blue, green, red, near-infrared, panchromatic, and the first principal component image of the Landsat multispectral data, from which the results were combined. The Landsat multispectral image matching produced reliable ice velocities for at least 14% wider area on the Nansen Ice Shelf than for the case of using single band (i.e., panchromatic) image matching. The ice velocities derived from the Landsat multispectral image matching have the error of $2.1m\;a^{-1}$ compared to the in situ Global Positioning System (GPS) observation data. The region adjacent to the Drygalski Ice Tongue showed the fastest increase in ice velocity between 2000 and 2017. The ice velocity along the central flow line of the Nansen Ice Shelf was stable before 2010 (${\sim}228m\;a^{-1}$). In 2011-2012, when a rift began to develop near the ice front, the ice flow was accelerated (${\sim}255m\;a^{-1}$) but the velocity was only about 11% faster than 2010. Since 2014, the massive rift had been fully developed, and the ice velocity of the upper region of the rift slightly decreased (${\sim}225m\;a^{-1}$) and stabilized. This means that the development of the rift and the resulting collapse of the ice front had little effect on the ice velocity of the Nansen Ice Shelf.

• Economic and Environmental Geology
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• v.44 no.1
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• pp.71-82
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• 2011

The unsaturated soil column tests were carried out for weathered gneiss soil and weathered granite soil in order to obtain the relationship between rainfall intensity and infiltration velocity of rainfall on the basis of different unit weight conditions of soil. In this study, volumetric water content and pore water pressure were measured using TDR sensors and tensiometers at constant time interval. For the column test, three different unit weights were used as in-situ condition, loose condition and dense condition, and rainfall intensities were selected as 20 mm/h and 50 mm/h. In 20 mm/h rainfall intensity condition, average rainfall infiltration velocities for both gneiss and weathered granite soils were obtained as $2.854{\times}10^{-3}$ cm/s ~ $1.297{\times}10^{-3}$ cm/s for different unit weight values and $2.734{\times}10^{-3}$ cm/s ~ $1.707{\times}10^{-3}$ cm/s, respectively. In 50 mm/h rainfall intensity condition, rainfall infiltration velocities were obtained as $4.509{\times}10^{-3}$ cm/s ~ $2.016{\times}10^{-3}$ cm/s and $4.265{\times}10^{-3}$ cm/s ~ $3.764{\times}10^{-3}$ cm/s respectively. The test results showed that the higher rainfall intensity and the lower unit weight of soil, the faster average infiltration velocity. In addition, the weathered granite soils had faster rainfall infiltration velocities than those of the weathered gneiss soils except for the looser unit weight conditions. This is due to the fact that the weathered granite soil had more homogeneous particle size, smaller unit weight condition and larger porosity.

• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.589-597
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• 2016

In this study, we investigated the use of satellite-derived flow (SDF) signals and a data-based model for the estimation of outflow for the river reach where in situ measurements are either completely unavailable or are difficult to access for hydraulic and hydrology analysis such as the upper basin of Imjin River. It has been demonstrated by many studies that the SDF signals can be used as the river width estimates and the correlation between SDF signals and river width is related to the shape of cross sections. To extract the nonlinear relationship between SDF signals and river outflow, Artificial Neural Network (ANN) model with SDF signals as its inputs were applied for the computation of flow discharge at Imjin Bridge located in Imjin River. 15 pixels were considered to extract SDF signals and Partial Mutual Information (PMI) algorithm was applied to identify the most relevant input variables among 150 candidate SDF signals (including 0~10 day lagged observations). The estimated discharges by ANN model were compared with the measured ones at Imjin Bridge gauging station and correlation coefficients of the training and validation were 0.86 and 0.72, respectively. It was found that if the 1 day previous discharge at Imjin bridge is considered as an input variable for ANN model, the correlation coefficients were improved to 0.90 and 0.83, respectively. Based on the results in this study, SDF signals along with some local measured data can play an useful role in river flow estimation and especially in flood forecasting for data-scarce regions as it can simulate the peak discharge and peak time of flood events with satisfactory accuracy.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.297-307
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• 2011

This study investigates relation of food safety incidents with climate. Therefore food safety incidents and climate data during 1999 to 2009 have been analyzed. In situ observations of monthly mean temperature, maximum temperature, minimum temperature, precipitation, and relative humidity in 60 observation stations of Korean Meteorological Administration (KMA) have been used in this study. Food safety incidents data have been constructed by searching media reports following Park's method (2009) during the same period. According to the Park's method, 729 events were collected. To analyze its relations, food safety incidents data have been classified into chemical, biological, and physical hazards. Pearson product-moment correlation coefficients have been applied to analyze the relations. The correlation of food safety incidents has negative one with precipitation (-0.48), and positive one with minimum temperature(0.45). Precipitation has been correlated with biological and physical hazards more than chemical hazard. Temperatures (mean temperature, maximum temperature, and minimum temperature) have been correlated closely with chemical hazard than others. Food safety incidents data has been interblended with human behavior factor through decision-making processes in food manufacturing, processing, and consumption phases of "farm-totable" food processing. Act in the preventing damage will be obvious if the hazard were apparent. Therefore abnormal condition could be more dangerous than that of apparent extreme events because apparent events or extreme events become one of alarm over hazards. Therefore, human behavior should be considered as one of the important factors for analysis of food safety incidents. The result of this study can be used as a better case study for food safety researches related to climate change.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.28-43
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• 2022

This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the T_MRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

• Journal of the Korean Geotechnical Society
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• v.23 no.9
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• pp.5-16
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• 2007

The simple linear elastic-perfectly plastic model with soil parameters $s_u,\;E_u$ and n of undrained condition is usually applied to predict the displacement of a constructed diaphragm wall(DW) on soft soils during excavation. However, the application of this soil model for finite element analysis could not interpret the continued increment of the lateral displacement of the DW for the large and deep excavation area both during the elapsed time without activity of excavation and after finishing excavation. To study the characteristic behaviors of soil behind the DW during the periods without excavation, a series of tests on soft Bangkok clay samples are simulated in the same manner as stress condition of soil elements happening behind diaphragm wall by triaxial tests. Three kinds of triaxial tests are carried out in this research: $K_0$ consolidated undrained compression($CK_0U_C$) and $K_0$ consolidated drained/undrained unloading compression with periodic decrement of horizontal pressure($CK_0DUC$ and $CK_0UUC$). The study shows that the shear strength of series $CK_0DUC$ tests is equal to the residual strength of $CK_0UC$ tests. The Young's modulus determined at each decrement step of the horizontal pressure of soil specimen on $CK_0DUC$ tests decreases with increase in the deviator stress. In addition, the slope of Critical State Line of both $CK_0UC$ and $CK_0DUC$ tests is equal. Moreover, the axial and radial strain rates of each decrement of horizontal pressure step of $CK_0DUC$ tests are established with the function of time, a slope of critical state line and a ratio of deviator and mean effective stress. This study shows that the results of the unloading compression triaxial tests can be used to predict the diaphragm wall deflection during excavation.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.83-94
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• 1998

To have a basic idea on the spectral reflectance signature in paddy rice canopy, we measured spectral reflectance from paddy rice canopy(Ilpumbyeo) using spectroradiometer (GER Inc. SFOV : 0.35~2.50 ${\mu}{\textrm}{m}$) in situ weekly or biweekly from transplanting to ripening stage. Spectral reflectance of the visible range (0.4~0.7 ${\mu}{\textrm}{m}$) was decreased to below 5% and then slightly increased again after heading stage in rice canopy. Meanwhile spectral reflectance of the near-infrared range (0.7~1.1 ${\mu}{\textrm}{m}$) was increased to 40~50% and then decreased a great deal after panicle initiation stage in rice canopy. Landsat TM equivalent band set ($\bar{p}$$_{TMi}$) was created by averaging spectral reflectance values to the real TM bands. Correlation analysis between the rice crop variables (LAI, total dry matter) and TM equivalent band set ($\bar{p}$$_{TMi}$) showed that LAI and total dry matter of rice were highly correlated with visible bands such as $\bar{p}$$_{TM1}$, $\bar{p}$$_{TM2}$, and $\bar{p}$$_{TM3}$. Ratio values ($\bar{p}$$_{TMi}$/$\bar{p}$$_{TMi}$) such as $\bar{p}$$_{TM4}$/$\bar{p}$$_{TM2}$ were also highly correlated with rice crop variables such as LAI and total dry matter.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.21-36
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• 2019

Dead fuel moisture content is a key variable in fire danger rating as it affects fire ignition and behavior. This study evaluates simple regression models estimating the moisture content of standardized 10-h fuel stick (10-h FMC) at three sites with different characteristics(urban and outside/inside the forest). Equilibrium moisture content (EMC) was used as an independent variable, and in-situ measured 10-h FMC was used as a dependent variable and validation data. 10-h FMC spatial distribution maps were created for dates with the most frequent fire occurrence during 2013-2018. Also, 10-h FMC values of the dates were analyzed to investigate under which 10-h FMC condition forest fire is likely to occur. As the results, fitted equations could explain considerable part of the variance in 10-h FMC (62~78%). Compared to the validation data, the models performed well with R2 ranged from 0.53 to 0.68, root mean squared error (RMSE) ranged from 2.52% to 3.43%, and bias ranged from -0.41% to 1.10%. When the 10-h FMC model fitted for one site was applied to the other sites, $R^2$ was maintained as the same while RMSE and bias increased up to 5.13% and 3.68%, respectively. The major deficiency of the 10-h FMC model was that it poorly caught the difference in the drying process after rainfall between 10-h FMC and EMC. From the analysis of 10-h FMC during the dates fire occurred, more than 70% of the fires occurred under a 10-h FMC condition of less than 10.5%. Overall, the present study suggested a simple model estimating 10-h FMC with acceptable performance. Applying the 10-h FMC model to the automatic mountain weather observation system was successfully tested to produce a national-scale 10-h FMC spatial distribution map. This data will be fundamental information for forest fire research, and will support the policy maker.

• The Korean Journal of Nuclear Medicine
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• v.37 no.2
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• pp.73-82
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• 2003

Objectives: A new software (Cardiac SPECT Analyzer: CSA) was developed for quantification of volumes and election fraction on gated myocardial SPECT. Volumes and ejection fraction by CSA were validated by comparing with those quantified by Quantitative Gated SPECT (QGS) software. Materials and Methods: Gated myocardial SPECT was peformed in 40 patients with ejection fraction from 15% to 85%. In 26 patients, gated myocardial SPECT was acquired again with the patients in situ. A cylinder model was used to eliminate noise semi-automatically and profile data was extracted using Gaussian fitting after smoothing. The boundary points of endo- and epicardium were found using an iterative learning algorithm. Enddiastolic (EDV) and endsystolic volumes (ESV) and election fraction (EF) were calculated. These values were compared with those calculated by QGS and the same gated SPECT data was repeatedly quantified by CSA and variation of the values on sequential measurements of the same patients on the repeated acquisition. Results: From the 40 patient data, EF, EDV and ESV by CSA were correlated with those by QGS with the correlation coefficients of 0.97, 0.92, 0.96. Two standard deviation (SD) of EF on Bland Altman plot was 10.1%. Repeated measurements of EF, EDV, and ESV by CSA were correlated with each other with the coefficients of 0.96, 0.99, and 0.99 for EF, EDV and ESV respectively. On repeated acquisition, reproducibility was also excellent with correlation coefficients of 0.89, 0.97, 0.98, and coefficient of variation of 8.2%, 5.4mL, 8.5mL and 2SD of 10.6%, 21.2mL, and 16.4mL on Bland Altman plot for EF, EDV and ESV. Conclusion: We developed the software of CSA for quantification of volumes and ejection fraction on gated myocardial SPECT. Volumes and ejection fraction quantified using this software was found valid for its correctness and precision.

• 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%.