• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.318-323
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• 2008

국부적이지만 수 mm단위까지 스캔이 가능한 지상LiDAR 장비를 이용하여 사면을 스캐닝한 후에 사면의 6개 지점에 대하여 강제로 변화를 준 후 다시 스캐닝하여 분석한 결과 0.008m의 평균편차를 나타내었다. 이것을 볼 때 미세변화 탐지를 위한 기법으로 지상 LiDAR자료의 적용이 유효할 것으로 판단된다.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.5
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• pp.42-52
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• 2024

This study aimed to utilize LiDAR, a high-precision surveying technology, to compensate for errors caused by human measurements and obtain accurate and consistent data for tree volume measurement. To this end, a comparative verification of measured tree volume values by each method was conducted using terrestrial LiDAR (TLS) and drone LiDAR (ALS). As a result of examining the 3D data of trees according to the measurement method, it was confirmed that the output data of terrestrial LiDAR had insufficient crowns, and the output data of drone LiDAR had insufficient trunks. Therefore, the study attempted to establish a complete form by aligning the two data sets. In addition, two verifications of tree volume values were conducted using the point cloud data output by each method. As a result of the first verification, the accuracy verification of terrestrial LiDAR showed a difference of 1-3 m in tree height compared to the existing field survey measurement value. The discrepancy is believed to be due to the density of trees or terrain and features according to the principle of LiDAR. In the second verification, terrestrial LIDAR, drone LIDAR, terrestrial LIDAR, and drone LIDAR alignment data were compared. In order to compare the tree height and breast height diameter according to each measurement method, Bland-Altman descriptive statistics were performed based on the field survey measurement values. Considering the results, the drone LIDAR measurement method showed the highest repeatability coefficient, indicating the least consistency, while the drone and terrestrial LIDAR alignment data values showed the lowest repeatability coefficient, indicating high consistency. For the breast height diameter, the terrestrial LIDAR measurement method showed a low repeatability coefficient similar to the drone and terrestrial LIDAR alignment data values, indicating high consistency. Therefore, it is judged that the method of overlapping drone and terrestrial LIDAR data when measuring the structure of trees can derive more precise tree volume information.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.179-186
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• 2010

In this research, an effective method for absolute positioning of feature points is proposed, which is applicable to geo-referencing of terrestrial LiDAR data scanned in dense urban areas. GPS positioning, common in absolute positioning, is apt to fail in the presence of signal disturbancein dense urban circumstances, while traditional surveying methods, including traversing and leveling, are generally more costly for wider areas. The idea is that reference points, marked on top of buildings, are surveyed by GPS positioning and then feature points are relatively positioned from the reference points. The present method, if laser scanning is accompanied, gets two advantages; one is that less feature points need to be surveyed because they can be substituredby reference points, and the other is that laser scanning can be more stably carried out. The present method was shown, from the experiments, to be cost-effective against traditional ones.

• Journal of Korean Society of Disaster and Security
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• v.12 no.3
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• pp.1-11
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• 2019

This study selected the national park area of Mt. Seorak in Inje-gun, Gangwon-do, where a lot of debris flow occurred due to the heavy rainfall and conducted a field survey. In addition, topographic spatial data were constructed using the GIS technique to analyze watershed characteristics. For the construction of terrain data after the disaster, the debris flow occurrence section was scanned and the 3D topographic data was constructed using the terrestrial LiDAR. LiDAR terrain data are compared to digital maps(before disaster) to assess precision and topographic data before and after the disaster were compared and analyzed. Debris flow diffusion area was calculated using FLO-2D model and compared debris flow occurred section.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.285-287
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• 2010

It is recently enlarged to necessity of 3D spatial information model in urban areas. and in order to that, It is increased to use the terrestrial LiDAR. The Point clouds which are received by terrestrial LiDAR take a relateive coordinate. For transform into absolute coordinate, it carry out GPS surveying. However, it is difficult to geo-referencing of point clouds using the GPS due to high buildings and facilities in urban area. This study suggests a methodology, that is geo-referencing of point clouds which is received from terresstrial LiDAR in urban area and then verified accuracy of geo-referencing of point clouds. In order to geo-Referencing of point clouds which are received in Engineering building of Yonsei Univ., it was be setout through GPS surveying, and then obtained absolute coordinate of real building. Using this coordinate, It was operated geo-referencing of point clouds, verified accuracy between check point and geo-referenced point clouds. As a result, RMSE of check point shows that GPS surveying is 6.9~8.0cm.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.333-340
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• 2008

For the indoor spatial modeling by terrestrial LiDAR and the analyzing its positional accuracy result, two terrestrial LiDARs which have different specification each other were used at test site. This paper shows disparity of accuracy between (1) the structural coordinate transformation by point cloud unit using control points and (2) the relative registration among all point cloud units then structural coordinate transformation in bulk, under condition of limited number of control points. As results, the latter had smaller size and distribution of errors than the former although different specifications and acquistion methods are used.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.233-244
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• 2021

This study investigated the application of terrestrial light detection and ranging (LiDAR) to inspect the defects of the vegetated levee. The accuracy of vegetation filtering techniques was compared by applying filtering techniques on photogrammetric point clouds of a vegetated levee generated by terrestrial LiDAR. Representative 10 vegetation filters such as CIVE, ExG, ExGR, ExR, MExG, NGRDI, VEG, VVI, ATIN, and ISL were applied to point cloud data of the Imjin River levee. The accuracy order of the 10 techniques based on the results was ISL, ATIN, ExR, NGRDI, ExGR, ExG, MExG, VVI, VEG, and CIVE. Color filters show certain limitations in the classification of vegetation and ground and classify grass flower image as ground. Morphological filters show a high accuracy of the classification, but they classify rocks as vegetation. Overall, morphological filters are superior to color filters; however, they take 10 times more computation time. For the improvement of the vegetation removal, combined filters of color and morphology should be studied.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.71-78
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• 2022

Recently, mountain disasters such as landslides and debris flows have flowed along mountain streams and hit residential areas and roads, increasing damage. In this study, in order to reduce damage and analyze causes of mountain disasters, field surveys and Terrestrial LiDAR terrain analysis were conducted targeting debris flow areas, and debris flow flow processes were simulated using FLO-2D and RAMM models, which are numerical models of debris flows. In addition, the debris flow deposition area was calculated and compared and analyzed with the actual occurrence section. The sedimentation area of the debris flow generation section of the LiDAR scan data was estimated to be approximately 21,336 ㎡, and was analyzed to be 20,425 ㎡ in the FLO-2D simulation and 19,275 ㎡ in the case of the RAMMS model. The constructed topographical data can be used as basic data to secure the safety of disaster risk areas.

• 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.