• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.2 s.109
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• pp.71-82
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• 2005

A large scale of riverside rearrangement has been recently done in the major rivers in Korea. So inundation possibility in agricultural area closed by these rivers has been higher than the possibility a few years ago. However, land use in this area has not been adjusted to a change of this situation near the rivers. Therefore, when typhoon or heavy rain is happened on this area, it can cause a large damage in agricultural area. This study analyzed inundation potentiality in agricultural area at Ibang-myeon, Changnyeong-gun, Kyeongnam-province, Korea by using the logistic regression model and the piecewise regression model. The first thing we did was to transfer the inundation area per elevation to the accumulated inundation area per elevation. This accumulated inundation area per elevation as an distribution function could be described by the logistic regression model(LRM), and piecewise regression model(PRM) could make it much more accurate to analyze the inundation area per elevation. As a result, the regression models derived from LRM and PRM showed $R^2$ over 0.950. The models derived from LRM and PRM in Ibang-myeon noted that frequently inundated area(FIA) was shown up to 12.12m in elevation, and potentially inundated area(PIA) was shown up to 14.60m in elevation. In FIA, regular agricultural activity would be impossible. And It would be not easy to continue the regular agricultural activity in PIA. So, this land should be rearranged to be used for a buffer zone for ecosystem protection, landscape conservation and things like that in riverside.

• Journal of Korean Neurosurgical Society
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• v.46 no.2
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• pp.99-102
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• 2009

Objective: Cardiac dysfunction after aneurysmal subarachnoid hemorrhage (SAH) is associated with elevation of serum cardiac troponin I (cTnl) levels. Elevation of cTnl predicts cardiopulmonary and neurological complications, and poor outcome. Methods: We retrospectively reviewed the medical and radiologic records of 114 (male: 30, female: 84) patients who developed aneurysmal SAH between January 2006 and June 2007 and had no history of previous cardiac problems. We evaluated their electrocardiography and cTnl level, which had been measured at admission. A cTnl level above 0.5 $\mu$g/L was defined as an indicator of cardiac injury following SAH. We examined various clinical factors for their association with cTnl elevation and analyzed data using chi-square test, t-test and logistic regression test with SPSS version 12.0. The results were considered significant at p< 0.05. Results: The following parameters shows a correlation with cTnl elevation: higher Hunt-Hess (H-H) grade (p = 0.000), poor Glasgow Outcome Scale (GOS) score (p = 0.000), profound pulmonary complication (p = 0.043), higher heart rate during initial three days following SAH (p = 0.029), ruptured aneurysm on communicating segment of internal carotid artery (p = 0.025), incidence of vasospasm (p = 0.421), and duration of hyperdynamic therapy for vasospasm (p = 0.292). A significant determinants for outcome were cTnl elevation (p = 0.046) and H-H grade (p = 0.000) in a multivariate study. Conclusion: A cTnl is a good indicator for cardiopulmonary and neurologic complications and outcome following SAH. Consideration of variable clinical factors that related with cTnl elevation may be useful tactics for treatment of SAH and concomitant complications.

• Journal of People, Plants, and Environment
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• v.24 no.1
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• pp.39-51
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• 2021

Background and objective: Urban topology can be characterized as impervious, which changes the hydrologic features of an area, increasing surface water flow during local heavy rain events. The pluvial flooding is also influenced by the vertical structures of the urban area. This study suggested a modified digital elevation model (DEM) to identify changes in urban hydrological conditions and segmentalized urban micro catchment areas using a geographical information system (GIS). Methods: This study suggests using a modified DEM creation process based on Rolling Ball Method concepts along with a GIS program. This method proposes adding realized urban vertical data to normal DEM data and simulating hydrological analyses based on RBM concepts. The most important aspect is the combination of the DEM with polygon data, which includes urban vertical data in three datasets: the contour polyline, the locations of buildings and roads, and the elevation point data from the DEM. DEM without vertical data (DCA) were compared with the DEM including vertical data (VCA) to analyze catchment areas in Shin-wol district, Seoul, Korea. Results: The DCA had 136 catchments, and the area of each catchment ranged from 3,406 m² to 423,449 m². The VCA had 2,963 catchments, with the area of each ranging from 50 m² to 16,209 m². The most important finding is that in the overlapped VCA; the boundary of areas directly affected by flooding and the direction of surface water flow could be identified. Flooding data from September 21, 2010 and July 27, 2011 in the Shin-wol district were applied as ground reference data. The finding is that in the overlapped VCA; the boundary of areas directly affected by flooding and the direction of surface water flow could be identified. Conclusion: The analysis of the area vulnerable to surface water flooding (SWF) was more accurately determined using the VCA than using the DCA.

• Journal of Ecology and Environment
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• v.32 no.2
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• pp.115-121
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• 2009

In order to elucidate the mechanisms affecting plant distributions in the reclaimed dredging area in the Gwangyang steelworks, in the Gwangyang Bay, Korea, we examined soil characteristics and plant distributions in four study sites and a control site in the study area. Desalination occurring along a gradient with increasing elevation, resulting in decrease of soil pH, EC, P, K, Cl, Ca, Mg, and salt and an increase in soil T-N, silt, clay contents. From site 1 (the lowest-elevation site) to site 5 (the highest-elevation site), halophytes decreased in abundance and nonhalophytes increased. The dominant species in each site were: Phragmites communis, Limonium tetragonum, and 12 additional species at site 1, Carex pumila, Suaeda japonica, and 15 additional species at site 2, Spergularia marina, Scirpus planiculmis, and 22 additional species at site 3, Miscantus sinensis, Lespedeza bicolor, and 26 additional species at site 4 and Pinus thunberii, Rhododendron mucronulatum, and 39 additional species at site 5, which resembled a naturally-occurring P. thinbergii community. Cluster analysis of the vegetation data matrix grouped the 35 plots into 5 major groups, and cluster analysis using the soil environment data matrix revealed 4 major groups. CCA of the floristic and environmental data matrix showed a positive relationship of SAR, EC, Na, Cl, and Ca, which are related to salt, in the $1^{st}$ axis and $2^{nd}$ axis, but negative relationships for altitude, organic contents, silt, and clay contents. Notably, plant species in the reclaimed dredging area that were separated along the $1^{st}$ axis showed strong relationships with factors that related to salt. Long-term exposure to natural rainfall in the reclaimed dredging area changed the soil characteristics, such as salinity. This change in soil characteristics might alter the SAR, which affects plant survival strategies in a given habitat. These results strongly indicated that factors related to salt and elevation play important roles in determining the overall plant distribution in the reclaimed dredging area.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.319-325
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• 2012

A new formulae for the estimation of the exposure duration in the inter-tidal zone are developed. The exposure duration is one of the most important factors influencing the habitat distribution of the benthic organisms. The formulae can estimate the exposure duration only using the four major tidal harmonic constants available in almost coastal areas. It is easier than the existing method using the frequency analysis of the hourly tidal elevation data. The estimation results by using the formulae suggested in this study are compared with the value by using the observed tidal elevation data analysis in the west coast, Korea. The mean RMS (root-mean squared) errors ranged form 0.8 to 1.4%. It can be used to simply estimate the accurate exposure duration in the region not having the longterm hourly tidal elevation data.

• Journal of the Korean Society of Safety
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• v.24 no.6
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• pp.1-6
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• 2009

This study describes a construction procedure of 3D virtual space using the NGIS data and its application to simulation. 3D space topography is modeled by using DEM consisted with triangular regular network. The elevations of nodal points of DEM are calculated through the interpolation with contour line and elevation points from the NGIS. Also, data for 2D roads and their environments, such as trees, lamps, and traffic signals, were extracted from the NGIS and projected on the DEM surfaces to get 3D virtual space. To give a reality to 3D virtual space and accelerate its graphic speed, data were converted into the directX format. It is believed that the virtual space constructed in this work can be applicable to the ubiqutous because DEM data can be converted to the AutoCAD format and ASCII code.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.39-48
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• 2012

Filtering process that separates ground and non-ground points from LIDAR data is important in order to create the digital elevation model (DEM) or extract objects on the ground. The purpose of this research is to select the most effective filtering algorithm through qualitative and quantitative analysis for the existing filtering method used to extract ground points from LIDAR data. For this, four filtering methods including Adaptive TIN(ATIN), Perspective Center-based filtering method(PC), Elevation Threshold with Expand Window(ETEW) and Progressive Morphology(PM) were applied to mountain area, urban area and the area where building and mountains exist together. Then the characteristics for each method were analyzed. For the qualitative comparison of four filtering methods used for the research, visual method was applied after creating shaded relief image. For the quantitative comparison, an absolute comparison was conducted by using control points observed by GPS and a relative comparison was conducted by the digital elevation model of the National Geographic Information Institute. Through the filtering experiment of the LIDAR data, the Adaptive TIN algorithm extracted the ground points in mountain area and urban area most effectively. In the area where buildings and mountains coexist, progressive morphology algorithm generated the best result. In addition, as a result of qualitative and quantitative comparisons, the applicable filtering algorithm regardless of topographic characteristics appeared to be ATIN algorithm.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.5
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• pp.307-314
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• 2006

Elevation differences within a paddy field relate strongly to plant health, crop homogeneity, and pest control. For precision agriculture (PA), the elevation within a field should be precisely controlled. We analyzed variation in elevation within two rice paddies over one crop cycle. The study took place in two rectangular plots (Field A and Field B, each $50m{\times}30m$). Elevations within the two plots were measured by a laser-equipped surveying instrument, that could determine elevations to precisions of 1 mm. The test fields were divided into grids with 30 squares; elevation was measured at the center of each $5{\times}10-m$ grid square. This study measured elevation during nine observation periods from pre-plowing to post-harvest. Descriptive statistics showed the highest elevations after plowing due to soil disturbance. One-way analysis of variance (ANOVA) revealed significant elevation differences before and after plowing and transplanting, although elevations were similar over the period of crop growth. Comparison of pre-plowing and post-harvest data showed differences in elevations, indicating that elevation changes occurred during plowing, rice transplanting, plant growth, and harvesting. In summary, the above statistical analyses indicated that elevation changes occurred due to plowing but not during the plant growth season or due to harvesting.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

• Journal of Korean Society of Forest Science
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• v.79 no.2
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• pp.216-221
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• 1990

Vegetational data from Mt. Gyeryong and Deokyu in central Korea were analysed in relation to 15 environmental variables. Two multivariate methods were applied : two-way indicator species analysis (TWINSPAN) for classification and detrended canonical correspondence analysis(DCCA), a recent technique which extracts ordination axes that can be related to environmental factors. The relationship between the distribution of dominant species of forest vegetation and soil condition in Mt. Gyeryong and Deokyu was investigated by analyzing elevation and soil nutrition gradient. Quercus mongolica forest was distributed in the high elevation and good nutrition area, Carpinzrs laxiflora and Fraxinus rhynclzophylla forest in the medium elevation and good nutrition area, Piszus densiflora-Quercus mongolica and Quercus variabilis forest in the medium elevation and medium nutrition area, Styrax jabozaica forest in the low elevation and medium nutrition area, and Pinus densiflora forest in the low elevation and poor nutrition area. The dominant compositional gradient related to elevation.