• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1545-1553
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• 2018

Recent eruptive activity at Kīlauea Volcano started on at the end of April in 2018 showed rapid ground deflation between May and June in 2018. On summit area Halema'uma'u lava lake continued to drop at high speed and Kīlauea's summit continued to deflate. GPS receivers and electronic tiltmeters detected the surface deformation greater than 2 meters. We explored the time-series surface deformation at Kīlauea Volcano, focusing on the early stage of eruptive activity, using multi-temporal COSMO-SkyMed SAR imagery. The observed maximum deformation in line-of-sight (LOS) direction was about -1.5 meter, and it indicates approximately -1.9 meter in subsiding direction by applying incidence angle. The results showed that summit began to deflate just after the event started and most of deformation occurred between early May and the end of June. Moreover, we confirmed that summit's deflation rarely happened since July 2018, which means volcanic activity entered a stable stage. The best-fit magma source model based on time-series surface deformation demonstrated that magma chambers were lying at depths between 2-3 km, and it showed a deepening trend in time. Along with the change of source depth, the center of each magma model moved toward the southwest according to the time. These results have a potential risk of including bias coming from single track observation. Therefore, to complement the initial results, we need to generate precise magma source model based on three-dimensional measurements in further research.

• Journal of the Korean GEO-environmental Society
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• v.22 no.2
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• pp.35-39
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• 2021

Photogrammetry using drone can produce high-resolution ortho image and acquire high-accuracy 3D information, which is useful. Therefore, this study attempted to determine the possibility of using drone-photogrammetry in park construction by producing a topographic map using drone-photogrammetry and analyzing the problems and accuracy generated during production. For this purpose, we created ortho image and DSM (digital surface model) using drone images and created topographic status map by vectorizing them. Accuracy was compared based on topographic status map by GPS (global positioning system) and TS (total station). The resulting of analyzing mean of the residuals at check points showed that 0.044 m in plane and 0.066 m in elevation, satisfying the tolerance range of 1/1,000 numerical maps, and result of compared lake size showed a difference of about 4.4%. On the other hand, it was difficult to obtain accurate height values for terrain in which existed vegetation when producing the topographic map, and in the case of underground buried objects, it is not possible to confirm it in the image, so direct spatial information acquisition was necessary. Therefore, it is judged that the topographic status map using drone photogrammetry can be efficiently constructed if direct spatial data acquisition is achieved for some terrain.

• Journal of Environmental Impact Assessment
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• v.21 no.3
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• pp.483-501
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• 2012

The purpose of this study was to apply a multi-metric model of Lentic Ecosystem Health Assessments(LEHA) for environmental impact assessments of Cheongpyung Reservoir during 2005 - 2006 and assessed the ecological model values. The ecosystem model of LEHA was composed of eleven metrics such as biological parameters($B_p$), physical parameters($P_p$), and chemical parameters($C_p$), and determined the rank of ecological health by the criteria. The variables of $B_p$ were metrics of % sensitive species($M_2$, NMS) and insectivore species($M_5$, % $I_n$), which decrease as the water quality degradates, and these metric values were low as 1.5% and 32.4%, respectively. In contrast, the proportions of tolerant species and omnivore species as the other $B_p$ parameters were 43% and 62%, respectively, which indicate a degradation and disturbance of the ecosystem. Riparian vegetation coverage($M_9$, % $V_c$) as a variable of $P_p$, were higher in the 2nd than 1st survey, and decreased toward the dam site from the headwaters. This was due to a habitat simplification(modifications) by frequent bottom dredging of sand and rocks. The variables of $C_p$ were two metrics of specific conductivity($M_{10}$, $C_I$) as an indicator of ionic contents(cations and anions) and the Trophic State Index(TSI) based on chlorophyll-a($M_{11}$, $TSI_{CHL}$) as an indicator of trophic state. These metric values of $C_p$ had high temporal variations, but low spatial variations on the main axis of the reservoir along with the ecological health of a good condition. The environmental impact assessments using the LEHA multi-metric model indicated that the model values of LEHA averaged 30.7 in 1st survey(fair - poor condition) vs. 28 in 2nd survey(poor condition), indicating a temporal variation of the ecological health. The model values of LEHA showed a minimum(28) in the lacustrine zone(S5) and ranged from 29 to 30 in the other locations sampled, indicating a low longitudinal variation. Overall, environmental impact assessments, based on LEHA model, suggest that chemical water quality conditions were in good, but biological conditions were disturbed due to habitat modifications by frequent dredgings in the system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.4
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• pp.176-184
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• 2011

Cold air on sloping surfaces flows down to the valley bottom in mountainous terrain at calm and clear nights. Based on the assumption that the cold air flow may be the same as the water flow, current models estimate temperature drop by regarding the cold air accumulation at a given location as the water-like free drainage. At a closed catchment whose outlet is blocked by man-made obstacles such as banks and roads, however, the water-like free drainage assumption is no longer valid because the cold air accumulates from the bottom first. We developed an empirical model to estimate quantitatively the effect of cold pool on nocturnal temperature in a closed catchment. In our model, a closed catchment is treated like a "vessel", and a digital elevation model (DEM) was used to calculate the maximum capacity of the cold pool formed in a closed catchment. We introduce a topographical variable named "shape factor", which is the ratio of the cold air accumulation potential across the whole catchment area to the maximum capacity of the cold pool to describe the relative size of temperature drop at a wider range of catchment shapes. The shape factor is then used to simulate the density profile of cold pool formed in a given catchment based on a hypsometric equation. The cold lake module was incorporated with the existing model (i.e., Chung et al., 2006), generating a new model and predicting distribution of minimum temperature over closed catchments. We applied this model to Akyang valley (i.e., a typical closed catchment of 53 $km^2$ area) in the southern skirt of Mt. Jiri National Park where 12 automated weather stations (AWS) are operational. The performance of the model was evaluated based on the feasibility of delineating the temperature pattern accurately at cold pool forming at night. Overall, the model's ability of simulating the spatial pattern of lower temperature were improved especially at the valley bottom, showing a similar pattern of the estimated temperature with that of thermal images obtained across the valley at dawn (0520 to 0600 local standard time) of 17 May 2011. Error in temperature estimation, calculated with the root mean square error using the 10 low-lying AWSs, was substantially decreased from $1.30^{\circ}C$ with the existing model to $0.71^{\circ}C$ with the new model. These results suggest the feasibility of the new method in predicting the site-specific freeze and frost warning at a closed catchment.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.499-505
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• 2015

Trend Impact Analysis(: TIA) is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. An adaptive neuro-fuzzy inference system is a kind of artificial neural network that integrates both neural networks and fuzzy logic principles, It is considered to be a universal estimator. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using Adaptive Neuro-Fuzzy Inference System(: ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes. The trigger attributes can be calculated by a stochastic dynamic model; then different scenarios are generated using Monte-Carlo simulation. To compare the proposed method, a simple simulation is provided concerning the impact of river basin drought on the annual flow of water into a lake.

• Journal of the Korean association of regional geographers
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• v.22 no.1
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• pp.240-250
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• 2016

Monitoring for water quantity and quality was conducted in this study for 2 years (2012~2013) in Oenam Stream which is a tributary of Seomjin River and upstream of Juam Lake. Suspended solid and total phosphorous(TP) were monitored and analyzed, then water quantity and quality as well as their relation with landuses were identified based on the previous study. Flow showed the similar pattern with precipitation but some discrepancies existed due to the distance between weather station(Gwangju) and study area. Watershed was modeled based on observed data using SWAT(Soil and Water Assessment Tool). Model calibration was conducted using data obtained in 2012 and validation was conducted using data in 2013. The coefficient of determination ($R^2$) between observed and modeled showed 0.6644 and 0.5176 for flow and TP, respectively for model calibration period. For validation period, $R^2$ was 0.7529 for flow and 0.7057 for TP, which were higher than calibration period. Hot spots were determined for watershed management by analyzing the amount of sediment and TP outcome from each sub-watershed. TP loading by landuse determined that cropland, of which the area takes only 5% from entire watershed, generated 53.6% of TP and residential and cowshed was responsible for 23.5% of TP loading.

• Journal of The Korean Astronomical Society
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• v.33 no.2
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• pp.111-121
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• 2000

Many models of globular cluster formation assume the presence of cold dense clouds in early universe. Here we re-examine the Fall & Rees (1985) model for formation of proto-globular cluster clouds (PGCCs) via thermal instabilities in a protogalactic halo. We first argue, based on the previous study of two-dimensional numerical simulations of thermally unstable clouds in a stratified halo of galaxy clusters by Real et al. (1991), that under the protogalactic environments only nonlinear (${\delta}{\ge}1$) density inhomogeneities can condense into PGCCs without being disrupted by the buoyancy-driven dynamical instabilities. We then carry out numerical simulations of the collapse of overdense douds in one-dimensional spherical geometry, including self-gravity and radiative cooling down to T = $10^4$ K. Since imprinting of Jeans mass at $10^4$ K is essential to this model, here we focus on the cases where external UV background radiation prevents the formation of $H_2$ molecules and so prevent the cloud from cooling below $10^4$ K. The quantitative results from these simulations can be summarized as follows: 1) Perturbations smaller than $M_{min}\~(10^{5.6}\;M{\bigodot})(nh/0.05cm^{-3})^{-2}$ cool isobarically, where nh is the unperturbed halo density, while perturbations larger than $M_{min}\~(10^8\;M{\bigodot})(nh/0.05cm^{-3})^{-2}$ cool isochorically and thermal instabilities do not operate. On the other hand, intermediate size perturbations ($M_{min} < M_{pgcc} < M_{max}$) are compressed supersonically, accompanied by strong accretion shocks. 2) For supersonically collapsing clouds, the density compression factor after they cool to $T_c = 10^4$ K range $10^{2.5} - 10^6$, while the isobaric compression factor is only $10^{2.5}$. 3) Isobarically collapsed clouds ($M < M_{min}$) are too small to be gravitationally bound. For supersonically collapsing clouds, however, the Jeans mass can be reduced to as small as $10^{5.5}\;M_{\bigodot}(nh/0.05cm^{-3})^{-1/2}$ at the maximum compression owing to the increased density compression. 4) The density profile of simulated PGCCs can be approximated by a constant core with a halo of $p{\infty} r^{-2}$ rather than a singular isothermal sphere.

• Journal of Korean Society on Water Environment
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• v.29 no.6
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• pp.832-841
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• 2013

In recent years, eutrophication in the Paldang Lake has become one of the major environmental problems in Korea as it may threaten drinking water safety and human health. Thus it is important to understand the phenomena and predict the time and magnitude of algal blooms for applying adequate algal reduction measures. This study performed seasonal water quality assessment and chlorophyll-a prediction using Bayseian simple/multiple linear regression analysis. Bayseian regression analysis could be a useful tool to overcome limitations of conventional regression analysis. Also it can consider uncertainty in prediction by using posterior distribution. Generally, chlorophyll-a of a P2(Paldang Dam 2) site showed high concentration in spring and it was similar to that of P4(Paldang Dam 4) site. For the development of Bayseian model, we performed seasonal correlation. As a result, chlorophyll-a of a P2 site had a high correlation with P5(Paldang Dam 5) site in spring (r = 0.786, p<0.05) and with P4 in winter (r = 0.843, p<0.05). Based on the DIC (Deviance Information Criterion) value, critical explanatory variables of the best fitting Bayesian linear regression model were selected as a $PO_4-P$ (P2), Chlorophyll-a (P5) in spring, $NH_3-N$ (P2), Chlorophyll-a (P4), $NH_3-N$ (P4) in summer, DTP (P2), outflow (P2), TP (P3), TP (P4) fall, COD (P2), Chl-a (P4) and COD (P4) in winter. The results of chlorophyll-a prediction showed relatively high $R^2$ and low RMSE values in summer and winter.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.236-241
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• 2023

Water quality problems in rivers, lakes, and estuaries have become serious in Korea. In order to overcome eutrophication of freshwater lakes and river basins, systematic management of water quality is necessary. To manage water quality in freshwater lakes and basins, apply hydrological models suitable for the basin and water quality models such as rivers and lakes to reduce water pollution based on the prediction results of these models. Improvement measures must be presented. In order to apply appropriate water pollution improvement measures in the watershed, accurate pollution sources must be identified and pollution loads must be predicted and presented. Based on GIS, the connection between the pollutant database and the hydrological and water quality prediction model will be integrated based on spatial location, making it possible to provide systematic support to improve watershed water quality by comprehensively including the water quality modeling process. In this paper, in order to accurately predict water pollution in freshwater lakes and river basins, a water quality model system is established using GIS-based spatial information to present a comprehensive water quality management method for freshwater lake basins in the future, and to systematically manage pollution sources through water quality modeling. This study was conducted to easily and efficiently operate hydrological and water quality models using automated spatial information.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.6
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• pp.708-722
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• 2016

Land-Ocean Interactions in the Coastal Zone (LOICZ) models for nutrient budgets were used to estimate the seasonal capacity of the Youngsan Estuary and Youngam-Geumho Estuary to sink and/or supply nutrients such as dissolved inorganic phosphorus (DIP) and nitrogen (DIN) to provide an understanding of the behavior of the coupled biogeochemical cycles of phosphorus and nitrogen in the estuaries (Youngsan Estuary, Youngam-Geumho Estuary) near Mokpo Harbor. During non-stratified periods (May, September, and November, 2008), simple three-box models were applied in each sub-region of the system, while a two-layer box model was applied during on-site observation of stratification development (July, 2008). The resulting mass-balance calculation indicated that even after large discharges from artificial lakes (in May and July), DIP influxes due to a mixing exchange ($V_{X-3}$, or $V_{deep}$) were more than terrigenous loads, indicating the backward transportation of nutrients from a marine source. The model results also indicated that for nutrient loads (DIP and DIN fluxes) in September, an extreme congestion of nutrients occurred around the mouths (sub-region III of the model) of the estuaries, possibly due to an imbalance in physical circulations between the estuaries and offshore locations. In November, the Youngam-Geumho Estuary, into which freshwater was discharged from artificial lakes (Youngam and Geumho Lake), showed nutrient enrichment in the water column, but the Youngsan Estuary showed nutrient depletion. In conclusion, to efficiently control water quality in the estuaries near Mokpo Harbor, integrated environmental management programs should be implemented. I.e., the reduction of nutrient loads from land basins as well as the deposit of nutrient loads into adjacent coastal lines.