• 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.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.333-343
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• 2015

This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.2
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• pp.87-97
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• 2017

Paulownia species has long been recognized in Korean traditional culture and the values of the species have been researched in various focuses. However, studies on distribution and ecological characteristics of the species are still needed. This study aimed to identify distribution trends and ecological characteristics of two Paulownia species in Busan metropolitan city using the MaxEnt model. The MaxEnt model was established based on the environmental factors such as positioning information of the Paulownia species, topography, climate and degree of anthropogenic disturbance potentiality (ADP), which was collected in the on-site research. The study verified that the accuracy of the model was appropriate as the AUC value of Paulownia coreana and P. tomentosa was 0.809, respectively. In terms of the distribution trends of the two Paulownia species in the research area depending on the distribution model, they were both mainly distributed in downtown where built-up area and bare ground were densely concentrated. The potential distribution area of the two species was identified as $137.4km^2$ for P. coreana and $135.0km^2$ for P. tomentosa. The distribution probability was high in Jung-gu, Dongrae-gu, Busanjin-gu and Yeonje-gu. As a result of the analysis on contribution of the environmental factors, it was turned out that the degree of anthropogenic disturbance potentiality (ADP) contributed to distribution of P. coreana and P. tomentosa by about 50%, and the contribution of the environmental factors had a positive correlation with the degree of ADP. The elevation had a negative correlation with both the two species, which was considered because the species must compete more with native species in natural habitats as the altitude above sea level rises. The research findings demonstrated numerically that the distribution of P.coreana and P. tomentosa depended on artificial activities, and indicated the relevance with the Korean traditional landscape. These findings are expected to provide meaningful information in using, preserving and restoring Paulownia species.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.