• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.3
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• pp.69-81
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• 2009

This study was intended to evaluate the objective landscape of rural region using an additive integration index method in the Seondong region of Gochang-gun, Jeollabuk-do, Korea. This study consisted of the following three steps. First, this study developed an additive integration index calculation model for landscape assessment based on indicators and weight to each space type in accordance with three landscape fields which were developed by the expert Delphi method. Second, this study used NDVI (Normalized Difference Vegetation Index) and permeable area rate, which were available from high resolution satellite image, to calculate the green naturality degree, area rate, and building coverage respectively. Third, this study has calculated the landscape assessment index of rural regions using an additive integration index method made of assessment data and weight for each indicator. This study has found the following results: 1) landscape level was very poor in all 6 types of space, marking grade five; 2) while the highest level of natural landscape and mixed landscape was grade two, that of artificial landscape was grade five; 3) based on objective landscape, grade five showed the highest frequency, and grade one, two, three, and four followed in that order.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.45-52
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• 2011

Seawater circulations between a bay and the open sea play an important role to make the ecosystem healthy, providing nutrient and oxygen to the benthic environments and cleaning up pollutions. The health of the benthic environment in a bay is closely related to the flushing characteristics of seawater. In this study, to estimate the seawater distribution and circulation characteristics of benthic environment in the Geunso bay, we calculated the hydraulic turn-over time by a hydro-hypsographic analysis. Digital elevation model (DEM) which was generated using waterline method based upon remotely sensed data and water depth of the subtidal zone estimated by echo-sounding survey was applied to the hydro-hypsograhic analysis through a geographic information system (GIS) spatial analysis. The results showed that 95% of the total area of the bay was tidal flat and the hydraulic turn-over time was 1.03 tidal cycle, which indicated that the flushing characteristics of the Geunso bay was very good. Geunso bay was revealed to occupy relatively wide area of benthic environment and to have relatively big tidal range over other domestic and foreign coastal environment, therefore it could have a better seawater circulation characteristics. This result can be effectively applied as fundamental information to establish the system for a quantitative estimate of health of coastal environment in the west coast of Korea and manage the ecosystem in benthic environments.

• Journal of the Korean Geographical Society
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• v.39 no.6 s.105
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• pp.907-921
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• 2004

Lots of characteristics such as dwelling, neighborhood, and accessibility characteristics affect to the housevalue. Many researches have been done to identify values of each characteristic using hedonic technique. However, there is a limit to identify interaction of each characteristic and variation of each characteristic among the accessibility context. This paper has implemented the Expansion Method research paradigm to model the housevalue determination process in the city of Seoul. The findings of this paper have revealed the presence of contextual variations in the housevalue determination process. The initial model for housevalue reveals that as $F_1$ increases (i.e., larger the number of rooms/bathrooms, larger parking space) and/or $F_2$ increases (i.e., higher owner occupied housing units, higher apartment housing units) and/or $F_3$ increases, (i.e., higher the ratio of higher than college graduated households, 8 school zone, older housing units) the estimated housevalue increases. However, the above relationships drift across their respective contexts. The houses which have negative $F_1$ value, the housevalue does not fluctuate according to the distance to the city center or subcenters. However, the houses which have positive $F_1$ value, the closer to the subcenters or shorter to the river, the higher the estimated housevalues. On the other hand, in areas far from the subcenters, the estimated housevalues does not fluctuate much according to the corresponding $F_2$ level. In areas close to the subcenters, the estimated housevalues vary tremendously according to the $F_2$ value. In the residual analysis, it is revealed that large apartment which are located in Kangnam, IchongDong, MokDong are underestimated. This paper has contributed to our understanding of the housevalue determination process by providing an alternative conceptualization to the traditional approach.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.38-41
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• 2008

In this research, we propose a new method for tracking the release rate using the concentration data obtained from the sensor. We used a sensor network that has already been set surrounding the area where hazardous gas releases can occur. From the real-time sensor data, we detected and analyzed releases of harmful materials and their concentrations. Based on the results, the release rate is estimated using the neural network. This model consists of 14 input variables (sensor data, material properties, process information, meteorological conditions) and one output (release rate). The dispersion model then performs the simulation of the expected dispersion consequence by combining the sensor data, GIS data and the diagnostic result of the source term. The result of this study will improve the safety-concerns of residents living next to storage facilities containing hazardous materials by providing the enhanced emergency response plan and monitoring system for toxic gas releases.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.975-987
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• 2021

Potential habitat mapping of Meretrix lyrata which is found in large parts of South East Asian tidal flat was carried out to find out causes of collective death. Frequency Ratio (FR) method, one of geospatialstatistical method, was employed with some benthic environmental factors; Digital elevation model (DEM) made from Landsat imagery, slope, tidal channel distance, tidal channel density, sedimentary facesfrom WorldView-02 image. Field survey was carried out to measure elevation of each station and to collect surface sediment and benthos samples. Potential habitat maps of the all clams and the juvenile clams were made and accuracy of each map showed a good performance, 76.82 % and 69.51 %. Both adult and juvenile clams prefer sand dominant tidal flat. But suitable elevation of adult clams is ranged from -0.2 to 0.2 m, and that of juvenile clams is ranged from 0 to 0.3 m. Tidal channel didn't affect the habitat of juvenile clams, but it affected the adult clams. In the furtherstudy, comparison with case of Korean tidal flat will be carried out to improve a performance of the potential habitat map. Change in the benthic echo-system caused by climate change will be predictable through potential habitat mapping of macro benthos.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.287-293
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• 2018

The Korean peninsula has been known as an area that is free of volcanic disasters. However, recent observations and research results of volcanoes in Far East Asia, including Baedu Mountain and Japanese volcanoes, show that the Korean peninsula is no longer a safe area from volcanic disasters. Since 2012, the Korean government has been developing an IT-based construction technology, VDRS (Volcanic Disaster Response System), for effective volcanic disaster response system. The main users of VDRS are public officers in central or local governments. However, most of them have little experience and knowledge about volcanic disasters. Therefore, it is essential to develop education contents and implement training on volcanic disaster response for effective response in a real disaster situation. In this paper, we deal with the development of a mobile application based on virtual reality (VR) for realistic volcanic disaster response training. The objectives of training are the delivery of knowledge and experience for volcanic disasters. First, VR contents were generated based on spatial information. A 3D model was constructed based on a Digital Elevation Model (DEM), and visualization models for meterological effects and various volcanic disaster diffusion effects were implemented for the VR contents. Second, the mobile application for the volcanic disaster response training was implemented. A 12-step story board is proposed for volcanic disaster experience. The application was developed with the Unity3D engine based on the proposed story board to deliver knowledge of various volcanic disasters (volcanic ash, pyroclastic flows, volcanic mudflow etc.). The results of this paper will be used for volcanic disaster response and prevention training and for more realistic training linked with augmented reality technology in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.133-139
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• 2021

Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

• Korean Journal of Environment and Ecology
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• v.37 no.6
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• pp.450-463
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• 2023

The objective of this study is to derive the core habitat of the Kirengeshoma koreana Nakai utilizing Habitat Suitability Index (HSI) and Maximum Entropy (MaxEnt) models. Expert-based models have been criticized for their subjective criteria, while statistical models face difficulties in on-site validation and integration of expert opinions. To address these limitations, both models were employed, and their outcomes were overlaid to derive the core habitat. Five variables were identified through a comprehensive literature review and spatial analysis based on appearance coordinates. The environmental variables encompass vegetation zone, forest type, crown density, annual precipitation, and effective soil depth. Through surveys involving six experts, importance rankings and SI (Suitability Index) scores were established for each variable, subsequently facilitating the creation of an HSI map. Using the same variables, the MaxEnt model was also executed, resulting in a corresponding map, which was merged to construct the definitive core habitat map. Out of 16 observed locations of K. koreana, 15 were situated within the identified core habitat. Furthermore, an area historically known to host K. koreana but not verified in the present, Mt. Yeongchwi, was found to lack a core habitat. These findings suggest that the developed models exhibit a high degree of accuracy and effectively reflect the current ecological landscape.

• Journal of the Korean GEO-environmental Society
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• v.25 no.9
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• pp.5-14
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• 2024

In Korea, torrential rain frequency and intensity have surged over the past five years (2019-2023), breaking rainfall records. Due to insufficient observation facilities for rainfall and runoff data in small mountainous catchments, preparing for unexpected floods is challenging. This study examines the Bidogyo catchment in Goesan-gun, Chungcheongbuk-do, comparing design flood discharge calculated with optimized parameters versus standard guidelines. Using HEC-HMS and Q-GIS for model construction, five rainfall events were analyzed with data from the National Water Resources Management Information System. The time of concentration (Tc) and storage constant (K) were calculated using the Seokyeongdae formula and model optimization. Results showed that optimized parameters produced higher objective function values for flood events. The design flood discharge varied by -10.7% to 17.3% from the standard guidelines when using optimized parameters. Moreover, optimized parameters yielded flood discharges closer to observed values, highlighting limitations of the Seokyeongdae formula for all catchments. Further research aims to develop suitable parameter estimation methods for small mountainous catchments in Korea.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.