• Economic and Environmental Geology
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• v.54 no.2
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• pp.177-186
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• 2021

For disaster management and mitigation of earthquakes in Korea Peninsula, active fault investigation has been conducted for the past 5 years. In particular, investigation of sediment-covered active faults integrates geomorphological analysis on airborne LiDAR data, surface geological survey, and geophysical exploration, and unearths subsurface active faults by trench survey. However, the fault traces revealed by trench surveys are only available for investigation during a limited time and restored to the previous condition. Thus, the geological data describing the fault trench sites remain as the qualitative data in terms of research articles and reports. To extend the limitations due to temporal nature of geological studies, we utilized a terrestrial LiDAR to produce 3D point clouds for the fault trench sites and restored them in a digital space. The terrestrial LiDAR scanning was conducted at two trench sites located near the Yangsan Fault and acquired amplitude and reflectance from the surveyed area as well as color information by combining photogrammetry with the LiDAR system. The scanned data were merged to form the 3D point clouds having the average geometric error of 0.003 m, which exhibited the sufficient accuracy to restore the details of the surveyed trench sites. However, we found more post-processing on the scanned data would be necessary because the amplitudes and reflectances of the point clouds varied depending on the scan positions and the colors of the trench surfaces were captured differently depending on the light exposures available at the time. Such point clouds are pretty large in size and visualized through a limited set of softwares, which limits data sharing among researchers. As an alternative, we suggested Potree, an open-source web-based platform, to visualize the point clouds of the trench sites. In this study, as a result, we identified that terrestrial LiDAR data can be practical to increase reproducibility of geological field studies and easily accessible by researchers and students in Earth Sciences.

• Spatial Information Research
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• v.16 no.3
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• pp.279-290
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• 2008

Landslide, one of the serious natural disasters, has Incurred a large loss of human and material resources. Recently, many forecasting or alarm systems based on various kinds of measuring equipment have been developed to reduce the damage of landslide. However, only a few of these equipments are guaranteed to evaluate the safety of whole side of land slope with their accessibility to the slope. In this study, we performed some experiments to evaluate the applicability of a terrestrial LiDAR as a surveying tool to measure the displacement of a land slope surface far a slope collapsing protection system. In the experiments, we had applied a slope stability method to a land slope and then forced to this slope with a load increasing step by step. In each step, we measured the slope surface with both a total station and a terrestrial LiDAR simultaneously. As the result of Slope Fracturing analysis using all targets, the LiDAR system showed that three was 1cm RMSE on X-axis, irregularity errors on Y-axis and few errors on Z-axis compare with Total Station. As the result of Slope Fracturing analysis using continuous targets, the pattern of Slope Fracturing was different according to the location of continuous targets and we could detect a continuous change which couldn't be found using Total station. The accuracy of the LiDAR data was evaluated to be comparable to that of the total station data. We found that a LiDAR system was appropriate to measuring the behaviour of land slope. The LiDAR data can cover the whole surface of the land slope, whereas the total station data are available on a small number of targets. Moreover, we extracted more detail information about the behavior of land slope such as the volume and profile changes using the LiDAR data.

• Journal of the Korean Society of Safety
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• v.31 no.1
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• pp.105-110
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• 2016

Mountainous disasters such as landslides and debris flow are difficult to forecast. Debris flow in particular often flows along the valley until it reaches the road or residential area, causing casualties and huge damages. In this study, the researchers selected Seoraksan National Park area located at Inje County (Inje-gun), Gangwon Province-where many mountainous disasters occur due to localized torrential downpours-for the damage reduction and cause analysis of the area experiencing frequent mountainous disasters every year. Then, the researchers conducted the field study and constructed geospatial information data by GIS method to analyze the characteristics of the disaster-occurring area. Also, to extract more precise geographic parameters, the researchers scanned debris flow triggering area through terrestrial LiDAR and constructed 3D geographical data. LiDAR geographical data was then compared with the existing numerical map to evaluate its precision and made the comparative analysis with the geographic data before and after the disaster occurrence. In the future, it will be utilized as basic data for risk analysis of mountainous disaster or disaster reduction measures through a fine-grid topographical map.

• Economic and Environmental Geology
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• v.52 no.3
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• pp.231-241
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• 2019

Kinematic analysis determines the stability of rock slope by analyzing the relationship between the slope face orientation and the discontinuity orientation. In this study, terrestrial LiDAR was used to obtain a large amount of discontinuity orientation data and then, the probabilistic characteristics of the orientation data obtained using terrestrial LiDAR were analyzed. Subsequently, the probabilistic kinematic analysis was carried out using the discontinuity orientations generated randomly from Fisher function in Monte Carlo simulation. In addition, the probabilistic kinematic analysis was also performed using the actual orientation data obtained from the terrestrial LiDAR to compare their results. Consequently, the results of both probabilistic analyses showed similar results. Therefore, if sufficient orientation data are provided by other means such as terrestrial LiDAR, the probabilistic analysis will show reasonable results using the actual field data without randomly generating orientation data. In addition, the deterministic kinematic analysis was also carried out using representative orientation of discontinuity sets. The analysis result of the probabilistic analysis showed similar results with the deterministic analysis because the dispersion of the discontinuity orientations in a joint set is not large.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.135-142
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• 2023

Light detection and ranging (LiDAR) sensors have been most widely used in terrestrial robotic applications because they can provide dense and precise measurements of the surrounding environments. However, the reliability of LiDAR measurements can considerably vary due to the different reflectivities of laser beams to the reflecting surface materials. This study presents a robust LiDAR-based mapping method for the varying laser reflectivities in indoor environments using the framework of simultaneous localization and mapping (SLAM). The proposed method can minimize the performance degradations in the SLAM accuracy by checking and discarding potentially unreliable LiDAR measurements in the SLAM front-end process. The gaps in point-cloud maps created by the proposed approach are filled by a Gaussian process regression method. Experimental results with a mobile robot platform in an indoor environment are presented to validate the effectiveness of the proposed methodology.

• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.392-401
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• 2014

This research was carried out to understand the impact of mountainous torrent on topographical change of slope and sediment volume within a deposit line by dredging of soil erosion control dam. Terrestrial LiDAR surveys were conducted at dredged and non-dredged sites. Terrestrial LiDAR has an advantage on detecting topographical changes easily without demanding workmanship and technical skill for users. The distribution of erodible slope ($20^{\circ}-40^{\circ}$) was higher in non-dredged site than that of dredged site. However, the distribution was higher in dredged site than that of non-dredged site after rainy season. Erosion and deposition appeared regularly in a dredged site, but those occurred irregularly in the non-dredged site. The inflow of soil per square meter was 1.7 times higher in dredged site than that of non-dredged site after rainy season. The difference of rainfall in each site did not affect to soil erosion. The distribution of erodible slope was increased in dredged site than that of non-dredged site after rainy season due to inflow of soil from upper stream caused by dredging.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.140-140
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• 2017

최근 기후변화에 따른 태풍과 국지성 집중호우의 증가로 국토의 64%가 산지인 우리나라에서는 재해의 위험성을 증가시키고 있다. 재해 분석에 있어 기초자료로 사용되는 지형자료의 정확도는 재해분석결과에 있어 중요하며, 지형촬영방법에 따라 정확도의 차이가 매우 크다. 지형자료 중 하나인 DEM(Digital Elevation Model) 활용분야 또한 확대되고 있고 지도제작에 있어 DEM을 사용하면 지형도를 신속히 제작할 수 있고, 편집 용이, 수작업 인원 감축, 정확도 향상 및 데이터베이스의 구축이 이루어져 체계적으로 종합적인 지형정보를 관리할 수 있는 장점이 있다. 지상 LiDAR를 이용하여 생성한 DEM은 매우 정확한 방법이며, 접촉식 측량장비에 비하여 누락되는 데이터가 적으며 정밀하게 자료를 수집가능 한 것이 장점이다. 지상LiDAR를 이용한 자료 취득 시식생과 구조물에 의해 촬영 각도가 제한되는 경우 충분한 자료를 얻기 위해 여러 위치에서 스캔이 필요하다. 한편 전 세계적으로 드론의 도입으로 인해 다양한 분야에서 높은 가능성을 가지고 활용되고 있는 실정이며, 드론을 이용한 연구들도 활발히 진행 중이다. 소규모 및 중간 규모의 하천, 산지 등의 현장 조사의 경우 LiDAR장비의 진입이 어려운 구간의 촬영 시 드론을 활용하면 보다 효율적일 것으로 예상된다. 이에 따라 본 연구는 지상LiDAR와 드론을 이용하여 얻은 DEM 자료를 비교 분석하여 드론으로 생성된 DEM 자료 활용 가능성 여부를 검토하였다. 본 연구에서는 동일한 지역에 지상LiDAR와 드론 촬영을 실시하여 지형자료를 각각 획득한 후 후처리 프로그램을 이용하여 영상분석을 실시하였다. 또한 측점을 선정한 후 지형 좌표의 편차, 표고의 편차 등을 비교분석하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5D
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• pp.527-532
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• 2012

Terrestrial LiDAR emerges as a main mapping technology for indoor 3D cadastre, cultural heritage conservation and, building management in that it provides fast, accurate, and reliable 3D data. In this paper, a new 3D modeling method consisting of segmentation stage and outline extraction stage is proposed to develop indoor 3D model from the terrestrial LiDAR. In the segmentation process, RANSAC and a refinement grid is used to identify points that belong to identical planar planes. In the outline tracing process, a tracing grid and a data conversion method are used to extract outlines of indoor 3D models. However, despite of an improvement of productivity, the proposed approach requires an optimization process to adjust parameters such as a threshold of the RANSAC and sizes of the refinement and outline extraction grids. Furthermore, it is required to model curvilinear and rounded shape of the indoor structures.

• Journal of the Korean Geographical Society
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• v.48 no.3
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• pp.321-335
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• 2013

High resolution data for the coastal sand beach during short-term in Jinbok-ri, Uljin-gun, Gyeongsangbuk-do are obtained by terrestrial LiDAR. The micro-geomorphological changes of 8 times before and after the strong low-pressure events during June to September, 2009 and changes under the various environments of wave-energy are investigated in the study. The obvious geomorphological changes between the northern and southern sand beach in Jinbok-ri are revealed by terrestrial LiDAR as well as by grain size analysis. The strong waves by the typhoons decrease the area and volume of the beach, and especially the area is largely influenced. The erosive and depositional processes dominate the northern and southern sand beach, respectively, after high wave in September. These results suggest that lots of sand grains in the beach are largely re-transported within the beach rather than offshore.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.4192-4198
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• 2011

Terrestrial LiDAR is a high precision positioning technique to monitor the behavior and change of structures and natural slopes, but it has depended on subjective hand intensive tasks for the classification(surface and vegetation or structure and vegetation) of positioning data. Thus it has a couple of problems including lower reliability of data classification and longer operation hours due to the surface characteristics of various geographical and natural features. In order to solve those problems, the investigator developed a technique of using the NDVI, which is a major index to monitor the changes on the surface(including vegetation), to categorize land covers, combining the results with the terrestrial LiDAR data, and classifying the results according to items. The application results of the developed technique show that the accuracy of convergence was 94% even though there was a problem with partial misclassification of 0.003% along the boundaries between items. The technique took less time for data processing than the old hand intensive task and improved in accuracy, thus increasing its utilization across a range of fields.