• Geophysics and Geophysical Exploration
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• v.20 no.2
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• pp.88-95
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• 2017

Chogye basin, which is surrounded by country rock, has a closed-basin form. In such a basin, incident seismic energy can form multiply reflected waves, thus causing energy concentration to occur at this closed-basin area. Microtremor measurement survey was performed at the Chogye basin, which is located in Chogye-myeon and Jeokjungmyeon, Hapcheon-gun, Gyeongsangnam-do, Republic of Korea. Microtremor data were transformed into the frequency domain, and then the horizontal-to-vertical spectral ratios (HVSR) were calculated. Fundamental resonance frequencies were estimated from the HVSR results for every observation point. Using the empirical relationship between site period and thickness for sediment sites in Korea known from the previous study, the distribution of sediment thickness of the Chogye basin was estimated from the fundamental resonance frequencies. Being compared with the mountainous rim with steep slope, the measurement points inside the basin have low values of the fundamental resonance frequency with the minimum of 1.03 Hz, which corresponds to the thickness of sedimentary layer with the maximum depth of about 100 m. A three-dimensional basin model was constructed for bedrock topography of the Chogye basin by an interpolation of basin depths estimated at each measurement site.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.4
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• pp.771-785
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• 2014

As marine desertification and chlorosis in Korean coast have been intensified over time, Korean government is promoting marine afforestation projects. However, marine afforestation location is mainly decided by administrative convenience. Also, there is limited literature on location suitability about the marine afforestation. This study aims to assess location suitability of marine afforestation considering 3 significant criteria: ecological, submarine topographical, and human-social environment. Jeju, the study area of this study, first observed chlorosis in Korean coast at the small fishery town in Seogwipo. Jeju is currently suffering from chlorosis all around the island. Habitat Evaluation Procedure (HEP), 3D kriging, Analytic Hierarchy Process (AHP) is applied as analysis methods. Especially, 3D kriging is utilized for modeling 3D ocean space reflecting ocean environment appropriately. The result shows that Jocheon coast has better location suitability than Seogwipo Pyoseon coast. Jocheon coast has the maximum 61% suitability as the habitat of Ecklonia cava Kjellman, and is highly evaluated in other criteria. The results of this study are expected to find optimal marine afforestation location, and to contribute to the restoration of the Jeju coastal ecosystem and the revitalization of Jeju fishing village societies.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1291-1295
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• 2005

제천, 충주, 단양의 3 개 지자체에 걸쳐 있는 충주호는 매년 여름철 집중호우시 부유쓰레기가 $3,000\~45,000\;m^3$ 의 범위에서 반복하여 발생하고 있으며 이들 대부분은 제천시 관내에서 수거되고 있다. 현재 부유쓰레기의 수거 및 육상 집하는 수자원공사가 담당하고 있으며 제천시는 이를 폐기물 매립장으로 운반하여 매립하고 있다. 이러한 부유쓰레기는 무게로는 그리 많지 않으나 부피가 매우 커 운반시 수거 차량의 운행대수가 많아지고 매립지 용량을 크게 소모하는 등 쓰레기 처리과정상의 문제점을 발생시키고 있으며 특히 부유쓰레기의 발생은 1 회성이 아니라 매년 장마와 홍수가 발생하면 되풀이되는 현상으로, 수자원 확보 및 홍수조절을 위해 설치된 댐에 의해 집중호우시 발생된 부유쓰레기가 댐 수위가 낮아짐에 따라 댐 주변부에 잔류하게 되어 수자원 및 수질 관리에 큰 어려움을 발생시키고 있다. 이러한 부유쓰레기는 댐 상류지역에 방치된 쓰레기들이 강우시 지표류와 함께 떠내려 온 것들로서 발생원인의 완전 제거는 불가능한 실정이므로 발생된 부유쓰레기를 최대한 신속히 수거하고 수거된 쓰레기는 소각이나 톱밥 생산 등의 물질자원화 방법으로 매립 양을 최소화 할 필요가 있다. 이에 본 연구에서는 충주댐에서 매년 집중호수시 발생하는 부유쓰레기의 발생 및 수거, 처리실태를 조사하며 또한 제천관내에 부유 쓰레기의 집중되는 원인을 분석하고 이로부터 적절한 부유쓰레기 관리대책을 수립하고자 하였다. 충주댐 부유물 발생 현황 조사 및 처리대책에 관한 연구결과는 다음과 같다. 부유쓰레기 발생량은 태풍의 발생에 따라 급격히 증가하여 년간 $12,587m^3\~45,356m^3$ 이 발생하고 있었다. 댐 및 하천 흐름 해석을 위해 2 차원 동수역학 모델인 RMA2 모형을 이용하여 충주댐에서의 물의 흐름을 해석한 결과 옥순대교$\~$청풍대교 구간 사이에 댐 및 지형적 영향으로 인해 잘 발달된 와류가 하도 전체를 통하여 발생되고 있었고 이는 댐 부유물 정체현상이 나타나는 지점과 잘 일치하고 있었다.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.59-66
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• 2016

The 2011 debris flow in Mt. Umyeonsan in Seoul, South Korea caused significant damages to the surrounding urban area, unlike other similar incidents reported to have occurred in the past in the country's mountainous regions. Accordingly, landslides and debris flows cause damage in various surroundings, regardless of mountainous area and urban area, at a great speed and with enormous impact. Hence, many researchers attempted to forecast the extent of impact of debris flows to help minimize the damage. The most fundamental part in forecasting the impact extent of debris flow is to understand the debris flow behavior and sedimentation mechanism in complex three-dimensional topography. To understand sedimentation mechanism, in particular, it is necessary to calculate the amount of energy and erosion according to debris flow behavior. The previously developed debris flow models, however, are limited in their ability to calculate the erosion amount of debris flow. This study calculated the extent of damage caused by a massive debris flow that occurred in 2011 in Seoul's urban area adjacent to Mt. Umyeonsan by using DEM, created from aerial photography and airborne LiDAR data, for both before and after the damage; and developed and compared a debris flow behavioral analysis model that can assess the amount of erosion based on energy theory. In addition, simulations using the existing debris flow model (RWM, Debris 2D) and a comprehensive comparison of debris flow-stricken areas were performed in the same study area.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.61-74
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• 2016

The purpose of this paper is to analyze the relationship between the location of the epicenter of a medium-sized earthquake(magnitude 4.8) that occurred on January 20, 2007 in the Odaesan area with lineament features using a shaded relief map(1/25,000 scale) and satellite images from LANDSAT-8 and KOMPSAT-2. Previous studies have analyzed lineament features in tectonic settings primarily by examining two-dimensional satellite images and shaded relief maps. These methods, however, limit the application of the visual interpretation of relief features long considered as the major component of lineament extraction. To overcome some existing limitations of two-dimensional images, this study examined three-dimensional images, produced from a Digital Elevation Model and drainage network map, for lineament extraction. This approach reduces mapping errors introduced by visual interpretation. In addition, spline interpolation was conducted to produce density maps of lineament frequency, intersection, and length required to estimate the density of lineament at the epicenter of the earthquake. An algorithm was developed to compute the Value of the Relative Density(VRD) representing the relative density of lineament from the map. The VRD is the lineament density of each map grid divided by the maximum density value from the map. As such, it is a quantified value that indicates the concentration level of the lineament density across the area impacted by the earthquake. Using this algorithm, the VRD calculated at the earthquake epicenter using the lineament's frequency, intersection, and length density maps ranged from approximately 0.60(min) to 0.90(max). However, because there were differences in mapped images such as those for solar altitude and azimuth, the mean of VRD was used rather than those categorized by the images. The results show that the average frequency of VRD was approximately 0.85, which was 21% higher than the intersection and length of VRD, demonstrating the close relationship that exists between lineament and the epicenter. Therefore, it is concluded that the density map analysis described in this study, based on lineament extraction, is valid and can be used as a primary data analysis tool for earthquake research in the future.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.363-368
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• 2003

We have successfully developed a more effective algorithm to extract the lineament in the area covered by wide alluvial deposits characterized by a relatively narrow range of brightness in the Landsat TM image, while the currently used algorithm is limited to the mountainous areas. In the new algorithm, flat areas mainly consisting of alluvial deposits were selected using the Local Enhancement from the Digital Elevation Model (DEM). The aspect values were obtained by 3${\times}$3 moving windowing of Zevenbergen & Thorno's Method, and then the slopes of the study area were determined using the aspect values. After the lineament factors in the alluvial deposits were revealed by comparing the threshold values, the first rank lineament under the alluvial deposits were extracted using the Hough transform In order to extract the final lineament, the lowest points under the alluvial deposits in a given topographic section perpendicular to the first rank lineament were determined through the spline interpolation, and then the final lineament were chosen through Hough transform using the lowest points. The algorithm developed in this study enables us to observe a clearer lineament in the areas covered by much larger alluvial deposits compared with the results extracted using the conventional existing algorithm. There exists, however, some differences between the first rank lineament, obtained using the aspect and the slope, and the final lineament. This study shows that the new algorithm more effectively extracts the lineament in the area covered with wide alluvlal deposits than in the areas of converging slope, areas with narrow alluvial deposits or valleys.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.1-11
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• 2018

Mapping accurate spatial information is important for constructing three-dimensional (3D) spatial models and managing artificial facilities, and, especially, mapping road centerlines is necessary for constructing accurate road maps. This research developed a semi-automatic methodology for mapping road centerlines using the MMS(Mobile Mapping System) LiDAR(Light Detection And Ranging) point cloud as follows. First, the intensity image was generated from the given MMS LiDAR data through the interpolation method. Next, the line segments were extracted from the intensity image through the edge detection technique. Finally, the road centerline segments were manually selected among the extracted line segments. The statistical results showed that the generated road centerlines had 0.065 m overall accuracy but had some errors in the areas near road signs.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.33-40
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• 2009

In field surveys using the dipole-dipole electrical resistivity method, we often encounter negative apparent resistivity. The term 'negative apparent resistivity' refers to apparent resistivity values with the opposite sign to surrounding data in a pseudosection. Because these negative apparent resistivity values have been regarded as measurement errors, we have discarded the negative apparent resistivity data. Some people have even used negative apparent resistivity data in an inversion process, by taking absolute values of the data. Our field experiments lead us to believe that the main cause for negative apparent resistivity is neither measurement errors nor the influence of self potentials. Furthermore, we also believe that it is not caused by the effects of induced polarization. One possible cause for negative apparent resistivity is the subsurface geological structure. In this study, we provide some numerical examples showing that negative apparent resistivity can arise from geological structures. In numerical examples, we simulate field data using a 3D numerical modelling algorithm, and then extract 2D sections. Our numerical experiments demonstrate that the negative apparent resistivity can be caused by geological structures modelled by U-shaped and crescent-shaped conductive models. Negative apparent resistivity usually occurs when potentials increase with distance from the current electrodes. By plotting the voltage-electrode position curves, we could confirm that when the voltage curves intersect each other, negative apparent resistivity appears. These numerical examples suggest that when we observe negative apparent resistivity in field surveys, we should consider the possibility that the negative apparent resistivity has been caused by geological structure.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.2
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• pp.97-108
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• 2012

A Lagrangian particle tracking model coupled with the ECOM3D were used to study on the behavior of fresh water released from the Namgang Dam in terms of residence time in Kangjin Bay, South Sea, Korea. Model was calibrated until skill cores for elevation, velocity, temperature and salinity are satisfied over 85%. In the numerical simulation, particles were released in 1 hour time interval from the northern boundary. The different patterns of particle trajectory are identified under the varying dynamics from tidal to density-driven current. The average residence time of total particles are approximately 65.9 hours in the entire Kangjin Bay. The average residence time were increased from 55~65 to 70~80 hours during maximum discharge period. Discharge rate of fresh water and average residence time in the Kangjin Bay is high correlated with correlation coefficient over 0.81.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.227-237
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• 2022

The most critical factors for detecting changes in very high-resolution satellite images are building positional inconsistencies and relief displacements caused by satellite side-view. To resolve the above problems, additional processing using a digital elevation model and deep learning approach have been proposed. Unfortunately, these approaches are not sufficiently effective in solving these problems. This study proposed a change detection method that considers both positional and topology information of buildings. Mask R-CNN (Region-based Convolutional Neural Network) was trained on a SpaceNet building detection v2 dataset, and the central points of each building were extracted as building nodes. Then, triangulated irregular network graphs were created on building nodes from temporal images. To extract the area, where there is a structural difference between two graphs, a change index reflecting the similarity of the graphs and differences in the location of building nodes was proposed. Finally, newly changed or deleted buildings were detected by comparing the two graphs. Three pairs of test sites were selected to evaluate the proposed method's effectiveness, and the results showed that changed buildings were detected in the case of side-view satellite images with building positional inconsistencies.