• Journal of the Korean Geotechnical Society
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• v.23 no.4
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• pp.161-167
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• 2007

In this study, ultimate lateral load capacity of piles is analyzed with consideration of lateral stress effect. Based on results obtained in this study, a method for the estimation of ultimate lateral load capacity is proposed. This makes it possible to more realistically estimate the ultimate lateral load capacity under various stress states caused by in-situ soil condition and pile installation process. Calibration chamber test results with various soil conditions were used in the analysis. From the test results, it was found that effect of the lateral stress was greater than that of the vertical stress on the ultimate lateral load capacity of piles. It was also found that, as the relative density increases, displacements required to reach the ultimate state increases, showing relative displacements of around 14% and 18-25% for $D_R$ : 55% and 86%, respectively. Based on results obtained in this study, a methodology for the estimation of ultimate lateral load capacity of piles using correction factors was proposed. Results from proposed method matched well measured results.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.3
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• pp.323-335
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• 2020

In this study, a series of site measurement of particulate and gases pollutants at five tunnels were carried out along with case studies to review the suitability of the current road tunnel ventilation design standards. Previous studies by other researchers have shown that the ratios of the level of measurement to the standard were 27.9%, 1.6% and 3.4% for TSP, CO and NOx, respectively. Those measured in this site study shows even lower ratios; the ratios were 2.6%, 0.8% and 0.3%, for TSP, CO and NOx, respectively. The particle size analysis of TSP for the five tunnels shows that PM10 including tire wear and re-suspended road dust exceeded 20.4%. This implies that non-exhaust particulate matter must be taken into account, since the current design standards for the particulate matter (visibility) include only the engine emission. Based on the recent research results, for vehicle emission rate and slope-speed correction factors, revision of ventilation design standards for pollutants is required. WRA (PIARC) also emphasizes the necessity of the ventilation design standards for pollutants. In addition, enactment of a new road tunnel ventilation system operation standard or guideline is strongly recommended when considering the low operating rate of the ventilation system with jet-fans.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1181-1194
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• 2018

This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• Journal of Chest Surgery
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• v.32 no.4
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• pp.388-393
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• 1999

Background: Correct preoperative staging of esophageal cancer is a prerequisite for adequate treatment. We prospectively compared the accuracy of positron emission tomography (PET) with [fluorine-18]FDG in the staging of esophageal cancer to that of computed tomography (CT). Material and Method: The findings of FDG PET and of chest CT including lower neck and the upper abdomen of 20 biopsy-proven squamous cell carcinoma patients (male, 19; female, 1; mean age, 61) were compared with the pathologic findings obtained from a curative esophagectomy with lymph node dissection. Result: The sensitivities of FDG PET and CT for diagnosis of primary tumor were the same, 90.0% (18/20). Both FDG PET and CT failed to show the primary tumor in 2 of 20 patients; one had a 1cm sized carcinoma in situ and the other had T1 stage cancer. By using the results of the pathologic examinations of 193 removed lymph node groups, we calculated the diagnostic sensitivities, specificities and accuracies of PET and CT (*$\chi$2 p < 0.005). Sensitivity** Specificity Accuracy* PET 55.6%(30/54) 97.1%(135/139) 85.5%(165/193) CT 13.0%(7/54) 98.6%(137/139) 74.6%(144/193) One of four patients with a false-positive for PEThad had active pulmonary tuberculosis. Among the 24 tumor involved lymph node groups, PET failed to show tumor metastasis in 5 lymph node groups abutting the tumor and in 14 lymph node groups located where the decay correction was not performed. Conclusion: Based on the above findings, it is suggested that [F-18]FDG-PET is superior to CT in the detection of nodal metastases and in the staging of patients with esophageal cancer.

• 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.