• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.833-843
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• 2020

Ecohydraulics is a newly born discipline in the early 1990s by the interdisciplinary approach combined with aquatic ecology in one discipline and geomorphology, hydrology, and fluid hydrodynamics in another. Major areas of ecohydraulics can be delineated as habitat hydraulics (including environmental flow), vegetation hydraulics, eco-corridor hydraulics, eutrophication hydraulics, and ecological restoration hydraulics. Reviews of relevant international journals and literature reveal that ecohydraulics has remained in the limited areas of fish response, hydraulic modeling, and physical habitat response. It has not reached a truly interdisciplinary stage. Literature reviews in Korea reveal that only 3% of the total number of the papers listed in the Journal of KWRA during the last 24 years is related to ecohydraulics. It is about 20% of the total listed in the Journal of Ecology and Resilient Infrastructure. Most of those related to ecohydraulics in Korea concern vegetation hydraulics, habitat hydraulics, and ecological restoration hydraulics. In contrast, dynamic flow modeling areas, including turbulence, fauna motion simulation, and eutrophication hydraulics, are not found. Areas of further research in ecohydraulics in Korea may be specified as follows: 1) environmental flows adapted to the traits of the rivers in Korea, 2) development of the dynamic floodplain vegetation models (DFVM) to assess the changes from the white river to green river, 3) development of the eutrophication hydraulic model to predict the freshwater algal blooms, and 4) development of the models to evaluate the physical, chemical, and biological impacts of the stream restoration, decommissioning and removal of old weirs or small dams.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.5
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• pp.1-14
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• 2021

Excessive development and urbanization have destroyed animal, plant, habitats and reduced biodiversity. In order to preserve species diversity, habitat prediction studies are have been conducted at home and overseas using various modeling techniques. This study was conducted to suggest optimal habitat modeling research by comparing HSI and MaxEnt, which are widely used among habitat modeling techniques. The study was targeted on the endangered species of Prionailurus bengalensis in nearby areas (5460.35km2) including Cheonan City, and the same data were used for analysis to compare those models. According to the HSI analysis, Prionailurus bengalensis's habitat probability was 74.65% for less than 0.5 and 25.34% for more than 0.5 and the top 30% were forest (99.07%). MaxEnt's analysis showed that 56.22% of those below 0.5 and 43.79% of those above 0.5 were found to have a high explanatory power of 78.3% of AUC. The Paired Wilcoxn test, which evaluated the significance of thoes models, confirmed that the mean difference between the two models was statistically significant (p<0.05). Analysis of the differences in the results of those models using the matrix table shows that score 24.43% HSI and MaxEnt was accordance,12.44% of the 0.0 to 0.2 section, 7.22% of the 0.2 to 0.4 section, 2.73% of the 0.4 to 0.6 section, 1.96% of the 0.6 to 0.8, and 0.08% of the 0.9 to 1.0. To verify where the score difference appears, the result values of those models were reset to values from 1 to 5 and overlaid. Overlapping analysis resulted in 30.26% of the Strongly agree values, 56.77% of the agree values, and 11.92% of the Disagree values. The places where the difference in scores occurs were analyzed in the order of forest (45.23%), agricultural land (34.57%), and urbanization area (7.65%). This confirmed that the analysis of the same target species within the same target site also has differences in forecasts depending on the modelling method. Therefore, a novel analysis method combining the advantages of each modeling in habitat prediction studies should be developed, and future study may be used to select Prionailurus bengalensis and species-protected areas and species protection areas in the future. Further research is judged to require higher accuracy studies through the use of various modeling techniques and on-site verification.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.179-190
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• 2017

A terrestrial LiDAR survey was conducted and unmanned aerial vehicle(UAV) images were taken for target cultural properties to present the utilization measures of terrestrial LiDAR and UAV in three-dimensional modeling of cultural properties for the identification of the status and restoration of cultural properties. Then the accuracy of the point clouds generated through this process was compared, an overlap analysis of the 3D model was conducted, and a convergence model was created. According to the results, the modeling with terrestrial LiDAR is more appropriate for precise survey because 3D modeling for the detection of displacement and deformation of cultural properties requires an accuracy of mm units. And UAV model has limitation as the impossibility of detailed expression of parts with sharp unevenness such as cracks of bricks. However, it is found that the UAV model has a wide range of modeling and has the advantage of modeling of real cultural properties. Finally, the convergence model created in this study using the advantages of the terrestrial LiDAR model and the UAV model could be efficiently utilized for the basic data development of cultural properties.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1218-1220
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• 1999

In this paper, we developed object-oriented analysis method for electric power system. It was applied to fault diagnosis, power system stability analysis and service restoration system in emergency state. Objectoriented programming(OOP)is a more flexible method than procedural programming. We proposed flexible modeling method for power system analysis.

• Journal of International Society for Simulation Surgery
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• v.1 no.2
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• pp.83-86
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• 2014

Purpose This paper was purposed to suggest the method to produce the supportive helmet (head correction) for the infants who are suffering from plagiocephaly and to evaluate the level of transformation through 3D model. Method Either of CT or X-ray restored images has been used in making the supportive helmet (Head correction) in general, but these methods of measuring have problems in cost and safety. 3D surface measurement technology was suggested to solve such matters. Results It was to design the transformed model of the head within 0.7cm in average by scanning the surface of head and performing 3D restoration with marching cube and the changing rate of the head was compared in numerical data with 3D model. Conclusion The suggested methods displayed the better performance than the conventional method in respect of the speed and cost.

• Journal of Conservation Science
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• v.35 no.3
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• pp.217-225
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• 2019

The chimi(ridge-end tile) of Wangheungsa temple is the oldest in our country. The upper part of the chimi was excavated from the southern side of Wangheungsa temple and the lower part from the northern side. These parts are considered to be portions of the same chimi, because they are similar in shape and are excavated from two sides of the same temple structure. However, the original shape of the chimi cannot be determined owing to substantial deterioration. Hence, in this study, replicas of the deteriorated chimi portions of Wangheungsa temple were fabricated by employing 3D scanning technology and the computer numerical control machining method. While observing the bending phenomenon of the chimi, the proposed model was warped realistically on the basis of the bending direction of the actual chimi. Consequently, the restoration process was modified several times. The results indicated that no gaps can be found between the upper and lower parts, and the corresponding patterns connect naturally. Furthermore, the proposed method is contactless, safe, operable, reproducible, and appropriate for restoration of artifacts. Additionally, the modeling data is semi-permanent. Hence, if modelling data is appropriately applied as per the characteristics of artifacts, it can be utilized in various fields such as virtual exhibitions, hands-on exhibitions, cultural heritage restoration, and production of teaching aids and souvenirs.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• Spatial Information Research
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• v.22 no.5
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• pp.53-63
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• 2014

As recent interest in ecological resources increases, an effort in three-dimensional visualization of the ecological resources has increased for the restoration and preservation of the natural environment as well as the evaluation of the landscape. However, in the case of forest resources, information extraction has been active, but the effort in trying to apply that information into an effective visualization has not happened. In other words, the effort for effective visualization is lacking when it comes to the visualization of forest resources, and numerous cases are ether non-realistic or the simulation required for analysis is inappropriate. Therefore, this paper extracts information through the use of airborne LiDAR data, aerial photograph, and forest type maps to create a vegetation layer, and then uses Flora3D forest modeling tools and ArcGlobe to accurately visualize the vegetation layer into the three dimension. An effective application for restoration and preservation of ecological resources as well as analysis on the urban landscape can be considered as a result of intuitively and realistically enabling the user's awareness of forest information within the Geographic Information System.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.1
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• pp.111-122
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• 2014

The provided habitat of many services from natural capital is important. But because most ecosystem services tools qualitatively evaluated biodiversity or habitat quality, this study quantitatively analyzed those aspects using the species distribution model (MaxEnt). This study used location point data of the goat(Naemorhedus caudatus), marten(Martes flavigula), leopard cat(Prionailurus bengalensis), flying squirrel(Pteromys volans aluco) and otter(Lutra lutra) from the 3rd National Ecosystem Survey. Input data utilized DEM, landcover classification maps, Forest-types map and digital topographic maps. This study generated the MaxEnt model, randomly setting 70% of the presences as training data, with the remaining 30% used as test data, and ran five cross-validated replicates for each model. The threshold indicating maximum training sensitivity plus specificity was considered as a more robust approach, so this study used it to conduct the distribution into presence(1)-absence(0) predictions and totalled up a value of 5 times for uncertainty reduction. The test data's ROC curve of endangered mammals was as follows: growing down goat(0.896), otter(0.857), flying squirrel(0.738), marten(0.725), and leopard cat(0.629). This study was divided into two groups based on habitat: the first group consisted of the goat, marten, leopard cat and flying squirrel in the forest; and the second group consisted of the otter in the river. More than 60 percent of endangered mammals' distribution probability were 56.9% in the forest and 12.7% in the river. A future study is needed to conduct other species' distribution modeling exclusive of mammals and to develop a collection method of field survey data.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.3
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• pp.29-45
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• 2022

For biodiversity conservation, the importance of beta-diversity which is changes in the composition of species according to environmental changes has become emphasized. However, given the systematic investigation of species distribution and the accumulation of large amounts of data in the Republic of Korea(ROK), research on the spatialization of beta-diversity using them is insufficient. Accordingly, this research investigated the applicability of the Generalized Dissimilarity Modeling(GDM) to ROK, which can predict and map the similarity of compositional turnover (beta-diversity) based on environmental variables. A brief overview of the statistical description on using GDM was presented, and a model was fitted using the flora distribution data(410,621points) from the National Ecosystem Survey and various environmental spatial data including climate, soil, topography, and land cover. Procedures and appropriated spatial units required to improve the explanatory power of the model were presented. As a result, it was found that geographical distance, temperature annual range, summer temperature, winter precipitation, and soil factors affect the dissimilarity of the vegetation community composition. In addition, as a result of predicting the similarity of vegetation composition across the nation, and classifying them into 20 and 100 zones, the similarity was high mainly in the central inland area, and tends to decrease toward the mountainous areas, southern coastal regions, and island including Jeju island, which means the composition of the vegetation community is unique and beta diversity is high. In addition, it was identified that the number of common species between zones decreased as the geographic distance between zones increased. It classified the spatial distribution of plant community composition in a quantitative and objective way, but additional research and verification are needed for practical application. It is expected that research on community-level biodiversity modeling in the ROK will be conducted more actively based on this study.