• Geotechnical Engineering
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• v.14 no.4
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• pp.17-32
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• 1998

has been much progress in theories and construction techniques to secure the stability of the underground structures. Recently, several studios have shown that it is possible to predict the existence of discontinuities ahead of a tunnel face by analyzing 3-dimensional absolute displacements measured during tunnel excavation. This paper concentrated on the development of a methodology to predict the existence and location of the discontinuities, or the void space(abandoned mine) , by performing 3-dimensional FEM analysis and considering the stress relocation caused by arching effect during excavation. Also, this study tried to verify deformation for choosing the most suitable support system. The results of this study might provide a way of safer and economical tunnel construction by utilizing the in-situ monitoring data.

• Korean Journal of Environmental Agriculture
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• v.37 no.3
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• pp.179-188
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• 2018

BACKGROUND: Reclamation of heavy metal-contaminated agricultural fields has intensively been done to ensure the soil quality and food security. This study evaluated the efficiency and longevity of current physical and chemical approaches for heavy metal-contaminated soils. METHODS AND RESULTS: Concentrations of 0.1 N HCl-leachable trace metals of Cd, Pb, and As from the stabilizing agents-treated soils decreased by 50%, 70%, and 40%, respectively, compared to the control. Among the stabilizing agents, the $CaCO_3$ was the best for stabilization. For physical stabilization, the soil dressing reduced the concentrations of Cd, Pb, and As by 88%, 94%,and 88%, respectively, compared to the control. Moreover, the dilution of the contaminated soils decreased the metals by an average of 25.3% when compared with the control. The longevity of each stabilization method was determined by using the availability assessment of heavy metals in the soils. Results showed that the leaching methods using HCl and $NH_4NO_3$ had 120 and 32 weeks longevity, respectively. Interestingly, any stabilization efficacy was not found over the time for Cd and Pb (i.e., cation metals), whereas the stabilization efficacy of As was sharply decreased under 50% after 32 weeks. However, the change of metal concentration was not significant with the physical stabilization compared to the chemical stabilization. CONCLUSION: The stabilization methods should carefully be selected based on long-term monitoring under climate conditions.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.919-928
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• 2023

Rainfall characteristics in Korea are concentrated during the summer flood season. In particular, when a large amount of turbid water flows into the dam due to the increasing trend of concentrated rainfall due to abnormal rainfall and abnormal weather conditions, prolonged turbid water phenomenon occurs due to the overturning phenomenon. Much research is being conducted on turbid water prediction to solve these problems. To predict turbid water, turbid water data from the upstream inflow is required, but spatial and temporal data resolution is currently insufficient. To improve temporal resolution, the development of the Turbidity-SS conversion equation is necessary, and to improve spatial resolution, multi-item water quality measurement instrument (YSI), Laser In-Situ Scattering and Transmissometry (LISST), and hyperspectral sensors are needed. Sensor-based measurement can improve the spatial resolution of turbid water by measuring line and surface unit data. In addition, in the case of LISST-200X, it is possible to collect data on particle size, etc., so it can be used in the Turbidity-SS conversion equation for fraction (Clay: Silt: Sand). In addition, among recent remote sensing methods, the spatial distribution of turbid water can be presented when using UAVs with higher spatial and temporal resolutions than other payloads and hyperspectral sensors with high spectral and radiometric resolutions. Therefore, in this study, the Turbidity-SS conversion equation was calculated according to the fraction through laboratory analysis using LISST-200X and YSI-EXO, and sensor-based field measurements including UAV (Matrice 600) and hyperspectral sensor (microHSI 410 SHARK) were used. Through this, the spatial distribution of turbidity and suspended sediment concentration, and the turbidity calculated using the Turbidity-SS conversion equation based on the measured suspended sediment concentration, was presented. Through this, we attempted to review the applicability of the Turbidity-SS conversion equation and understand the current status of turbid water occurrence.

• Journal of the Korean Vacuum Society
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• v.10 no.1
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• pp.22-26
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• 2001

Microstructures of AlN thin films on Si substrates grown by plasma assisted molecular beam epitaxy were analyzed with various growth temperatures and substrate orientations. Reflection high energy electron diffraction (RHEED) patterns were checked for the in-situ monitoring of the growth condition. X-ray diffraction(XRD), double crystal X-ray diffraction (DCXD), and transmission electron microscopy/diffraction (TEM/TED) techniques were employed to characterize the microstructure of the films after growth. On Si(100) sub-strates, AlN thin films were grown mostly along the hexagonal c-axis orientation at temperature higher than $850^{\circ}C$. On the other hand the AlN films on Si(111) were epitaxially grown with directional coherencies in AlN(0001)/Si(111), AlN(1100)/Si(110), and AlN(1120)/Si(112). The microstructure of AlN thin films on Si(111) substrates, with a full width at half maximum of almost 3000 arcsec at 2$\theta$=$36.2^{\circ}$, showed that the single crystal films were grown, even if they includ a lot of crystal defects such as dislocations and stacking faults.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.173-188
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• 2005

The present study aims to derive and compare narrow and broad bandwidths of ocean color sensor’s algorithms for the study of monitoring highly dynamic coastal oceanic environmental parameters using high-resolution imagery acquired from Multi-spectral Camera (MSC) on KOMPSAT-2. These algorithms are derived based on a large data set of remote sensing reflectances ($R_{rs}$) generated by using numerical model that relates $b_b/(a + b_b)$ to $R_{rs}$ as functions of inherent optical properties, such as absorption and backscattering coefficients of six water components including water, phytoplankton (chl), dissolved organic matter (DOM), suspended sediment (SS) concentration, heterotropic organism (he) and an unknown component, possibly represented by bubbles or other particulates unrelated to the first five components. The modeled $R_{rs}$ spectra appear to be consistent with in-situ spectra collected from Korean waters. As Kompsat-2 MSC has similar spectral characteristics with Landsat-5 Thematic Mapper (TM), the model generated $R_{rs}$ values at 2 ㎚ interval are converted to the equivalent remote sensing reflectances at MSC and TM bands. The empirical relationships between the spectral ratios of modeled $R_{rs}$ and chlorophyll concentrations are established in order to derive algorithms for both TM and MSC. Similarly, algorithms are obtained by relating a single band reflectance (band 2) to the suspended sediment concentrations. These algorithms derived by taking into account the narrow and broad spectral bandwidths are compared and assessed. Findings suggest that there was less difference between the broad and narrow band relationships, and the determination coefficient $(r^2)$ for log-transformed data [ N = 500] was interestingly found to be $(r^2)$ = 0.90 for both TM and MSC. Similarly, the determination coefficient for log-transformed data [ N = 500] was 0.93 and 0.92 for TM and MSC respectively. The algorithms presented here are expected to make significant contribution to the enhanced understanding of coastal oceanic environmental parameters using Multi-spectral Camera.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.548-557
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• 2021

Cypripedium japonicum Thunb. is an endemic plant in East Asia, distributed only in Korea, China, and Japan. At the global level, the IUCN Red List evaluates it as "Endangered Species (EN)," and at the national level in Korea, it is evaluated as "Critically Endangered Species (CR)." In this study, we investigated the characteristics of the age structure and the sustainability of the population based on the data obtained by demographic monitoring conducted for seven years in the natural habitat. C. japonicum habitats were observed in 7 regions of Korea (Pochoen, Gapyeong, Hwacheon, Chuncheon, Yeongdong, Muju, Gwangyang), and 4,356 individuals in 15 subpopulations were identified. The population size and structure differed from region to region, and artificial management had a very important effect on the size and structural change of the population. Population viability analysis (PVA) based on changes in the number of individuals of C. japonicum showed a very diverse tendency by region. And the probability of population extinction in the next 100 years was 0.00% for Pocheon, 10.90% for Gwangyang, 24.05% for Chuncheon, and 79.50% for Hwacheon. Since the above monitored study sites were located within the conservation shelters, which restricted access by humans, unauthorized collection of C. japonicum, the biggest threat to the species, was not reflected in the individual viability. So, the risk of extinction in Korea is expected to be significantly higher than that estimated in this study. Therefore, it is necessary to reflect population information in several regions that may represent various threats to determine the extinction risk of the C. japonicum population objectively. In the future, we should expand the demographic monitoring of the C. japonicum population known in Korea.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.339-357
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• 2009

The Saemangeum Reclamation Project was launched as a national project in 1991 to reclaim a large coastal area of 401 km$^2$ by constructing a 33-km long dyke. The final dyke enclosure in April 2006 has transformed the tidal flat into lake and land. The dyke construction has abruptly changed not only the estuarine tidal system inside the dyke, but also the coastal marine environment outside the dyke. In this study, we investigated the spatial change of SST distribution using the Landsat-5/7 and NOAA data before and after the dyke completion in the Saemangeum area. Satellite-induced SST was verified by compared with the various in situ measurements such as tower, buoy, and water sample. The correlation coefficient resulted in above 0.96 and RMSE was about 1$^{\circ}C$ in all data. 38 Landsat satellite images from 1985 to 2007 were analyzed to estimate the temporal and spatial change of SST distribution from the beginning to the completion of the Samangeum dyke's construction. The seasonal change in detailed spatial distribution of SST was measured, however, the estimation of change during the Saemangeum dyke's construction was hard to figure out owing to the various environmental conditions. Monthly averaged SST induced from NOAA data from 1998 to 2007 has been analyzed for a complement of Landsat's temporal resolution. At the inside of the dyke, the change of SST from summer to winter was large due to the relatively high temperature in summer. In this study, multi-sensor thermal remote sensing is an efficient tool for monitoring the temporal and spatial distribution of SST in coastal area.

• 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.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1503-1517
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• 2018

Mt. Baekdu is a stratovolcano located at the border between China and North Korea and is known to have formed through its differentiation stage after the Oligocene epoch in the Cenozoic era. There has been a growing interest in the magma re-activity of Mt. Baekdu volcano since 2010. Several research projects have been conducted by government such as Korea Meteorological Administration and Korea Institute of Geoscience and Mineral Resources. Because, however, the Mt. Baekdu volcano is located far from South Korea, it is quite difficult to collect in-situ observations by terrestrial equipment. Remote sensing is a science to analyze and interpret information without direct physical contact with a target object. Various types of platform such as automobile, unmanned aerial vehicle, aircraft and satellite can be used for carrying a payload. In the past several decades, numerous volcanic studies have been conducted by remotely sensed observations using wide spectrum of wavelength channels in electromagnetic waves. In particular, radar remote sensing has been widely used for volcano monitoring in that microwave channel can gather surface's information without less limitation like day and night or weather condition. Radar interferometric technique which utilized phase information of radar signal enables to estimate surface displacement such as volcano, earthquake, ground subsidence or glacial movement, etc. In 2018, long-term research project for collaborative observation for Mt. Baekdu volcano between Korea and China were selected by Korea government. A volcanic specialized research center has been established by the selected project. The purpose of this paper is to introduce about remote sensing techniques for volcano monitoring and to review selected studies with remote sensing techniques to monitor Mt. Baekdu volcano. The acquisition status of the archived observations of six synthetic aperture radar satellites which are in orbit now was investigated for application of radar interferometry to monitor Mt. Baekdu volcano. We will conduct a time-series analysis using collected synthetic aperture radar images.