• Title/Summary/Keyword: 3D 지상 레이저 스캔

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3D Modeling of Both Exterior and Interior of Traditional Architectures by Terrestrial Laser Scanning at Multi-Stations (다중 지점 지상레이저스캐닝에 의한 전통 건축물의 내부와 외부의 3차원 모델링)

  • LEE, Jin-Duk;BHANG, Kon-Joon;Schuhr, Walter
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.4
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    • pp.127-135
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    • 2021
  • The purpose of this research is to present about a series of processes for 3D model generation from scan data of two types of Korean styled architectures, namely, a pavilion and a house, which were acquired with the terrestrial LiDAR and evaluate a 3D surveying method to document digitally the traditional buildings, cultural properties, archeological sites, etc. Since most ancient buildings and cultural assets which require digital documentation by the terrestrial laser scanner usually need to acquire data from multi-directions. Therefore this paper suggested a process of acquiring and integrating data from mult-stations around the object. Also we presented a way for reconstructing automatically at once both the interior and exterior surfaces of buildings from laser scan data.

Study of Servo Controller for Improving Position Accuracy of 3D Terrestrial Laser Scanner (지상용 3차원 레이저 스캐너의 측정 위치 정확도 향상을 위한 서보 제어기의 연구)

  • Yu, Jong-Wook;Jeong, Joong-Yeon;Kim, Tae-Hyung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.2
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    • pp.187-194
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    • 2009
  • This study is to improve position accuracy by selecting proper a servo motor and applying FOC(Field Oriented Control) on developing a 3D terrestrial laser scanner. A 3D terrestrial laser scanner under developing has range of scanning of azimuth 360$^\circ$and elevation 270$^\circ$. It is implemented by precise controlling of a azimuth motor and a elevation motor. In the consequence of study, we have known that position accuracy of the motor can be able to be improved with constant torque of the motor by using FOC(Field Oriented Control). The control technic of the motor is possible to apply a 3D terrestrial laser scanner as well as a robotic total station.

Reconfiguration of Physical Structure of Vegetation by Voxelization Based on 3D Point Clouds (3차원 포인트 클라우드 기반 복셀화에 의한 식생의 물리적 구조 재구현)

  • Ahn, Myeonghui;Jang, Eun-kyung;Bae, Inhyeok;Ji, Un
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.6
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    • pp.571-581
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    • 2020
  • Vegetation affects water level change and flow resistance in rivers and impacts waterway ecosystems as a whole. Therefore, it is important to have accurate information about the species, shape, and size of any river vegetation. However, it is not easy to collect full vegetation data on-site, so recent studies have attempted to obtain large amounts of vegetation data using terrestrial laser scanning (TLS). Also, due to the complex shape of vegetation, it is not easy to obtain accurate information about the canopy area, and there are limitations due to a complex range of variables. Therefore, the physical structure of vegetation was analyzed in this study by reconfiguring high-resolution point cloud data collected through 3-dimensional terrestrial laser scanning (3D TLS) in a voxel. Each physical structure was analyzed under three different conditions: a simple vegetation formation without leaves, a complete formation with leaves, and a patch-scale vegetation formation. In the raw data, the outlier and unnecessary data were filtered and removed by Statistical Outlier Removal (SOR), resulting in 17%, 26%, and 25% of data being removed, respectively. Also, vegetation volume by voxel size was reconfigured from post-processed point clouds and compared with vegetation volume; the analysis showed that the margin of error was 8%, 25%, and 63% for each condition, respectively. The larger the size of the target sample, the larger the error. The vegetation surface looked visually similar when resizing the voxel; however, the volume of the entire vegetation was susceptible to error.

Introduction and Application of 3D Terrestrial Laser Scanning for Estimating Physical Structurers of Vegetation in the Channel (하도 내 식생의 물리적 구조를 산정하기 위한 3차원 지상 레이저 스캐닝의 도입 및 활용)

  • Jang, Eun-kyung;Ahn, Myeonghui;Ji, Un
    • Ecology and Resilient Infrastructure
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    • v.7 no.2
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    • pp.90-96
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    • 2020
  • Recently, a method that applies laser scanning (LS) that acquires vegetation information such as the vegetation habitat area and the size of vegetation in a point cloud format has been proposed. When LS is used to investigate the physical shape of vegetation, it has the advantage of more accurate and rapid information acquisition. However, to examine uncertainties that may arise during measurement or post-processing, the process of adjusting the data by the actual data is necessary. Therefore, in this study, the physical structure of stems, branches, and leaves of woody vegetation in an artificially formed river channel was manually investigated. The obtained results then compared with the information acquired using the three-dimensional terrestrial laser scanning (3D TLS) method, which repeatedly scanned the target vegetation in various directions to obtain relevant information with improved precision. The analysis demonstrated a negligible difference between the measurements for the diameters of vegetation and the length of stems; however, in the case of branch length measurement, a relatively more significant difference was observed. It is because the implementation of point cloud information limits the precise differentiation between branches and leaves in the canopy area.

Evaluation of Airborne LiDAR Data using Field Surveyed Ground Control Points (현지 측량기준점을 이용한 LiDAR 데이터의 정확도 검증)

  • Wie, Gwang-Jae;Yang, In-Tae;Suh, Young-Woon;Sim, Jung-Min
    • Journal of Korean Society for Geospatial Information Science
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    • v.14 no.4 s.38
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    • pp.11-18
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    • 2006
  • In this paper, airborne LiDAR data were evaluated in horizontal and vertical accuracy. By using zigzag scanning type of LiDAR, GCPs are not tested directly. So points around GCPs were used in this evaluation. Building corner points were made from LiDAR's building planar and compared with ground surveyed GCPs, in horizontal accuracy test. Its accuracy shows 19cm average and 21cm RMSE and 15 points were within 20cm among 16 points. In vertical accuracy test, 41 GCPs were used and it shows 11cm average and 14cm RMSE and 75% of GCPs were within 15cm. This could be a criterion in topographic map modification and basic geographic DB and 3D data construction using airborne LiDAR data.

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