• Title/Summary/Keyword: Terrestrial LiDAR

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Monitoring of non-point Pollutant Sources: Management Status and Load Change of Composting in a Rural Area based on UAV (UAV를 활용한 농촌지역 비점오염원 야적퇴비 관리상태 및 적재량 변화 모니터링)

  • PARK, Geon-Ung;PARK, Kyung-Hun;MOON, Byung-Hyun;SONG, Bong-Geun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.2
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    • pp.1-14
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    • 2019
  • In rural areas, composting is a source of non-point pollutants. However, as the quantitative distribution and loading have not been estimated, it is difficult to determine the effect of composting on stream water quality. In this study, composting datum acquired by unmanned aerial vehicle(UAV) was verified by using terrestrial LiDAR, and the management status and load change of the composting was investigated by UAV with manual control flight, thereby obtaining the basic data to determine the effect on the water system. As a result of the comparative accuracy assessment based on terrestrial LiDAR, the difference in the digital surface model(DSM) was within 0.21m and the accuracy of the volume was 93.24%. We expect that the accuracy is sufficient to calculate and utilize the composting load acquired by UAV. Thus, the management status of composting can be investigated by UAV. As the total load change of composting were determined to be $1,172.16m^3$, $1,461.66m^3$, and $1,350.53m^3$, respectively, the load change of composting could be confirmed. We expect that the results of this study can contribute to efficient management of non-point source pollution by UAV.

Monitoring of the Natural Terrain Behavior Using the Terrestrial LiDAR (지상라이다 자료를 이용한 자연사면의 변위 모니터링)

  • Park, Jae Kook;Lee, Sang Yun;Yang, In Tae;Kim, Dong Moon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.2D
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    • pp.191-198
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    • 2010
  • The displacement of slope is a key factor in predicting the risk of a landslide. Therefore, the slope displacement should be continuously observed with high accuracy. Recently, high-tech equipment such as optical fiber sensor, GPS, total station and measuring instrument have been used. However, such equipment is poorly used in fields due to economics, environment, convenience and management. Because of this, development of substantial observational techniques for varied slope observation and field applications is needed. This study analyzed the possibility of terrestrial LiDAR for slope monitoring and suggested it as information-obtaining technique for slope investigation and management. For that, this study evaluated the monitoring accuracy of terrestrial LiDAR and performed GRID analysis to read the displacement area with the naked eye. In addition, it suggested a methodology for slope monitoring.

Definition of 3D Modeling Level of Detail in BIM Regeneration Through Reverse Engineering - Case Study on 3D Modeling Using Terrestrial LiDAR - (역설계를 통해 BIM 구축시에 3D 모델링에 대한 세밀도(LoD) 정립 - 지상 LiDAR 활용한 3D 모델링 연구 중심 -)

  • Chae, Jae-Hyun;Lee, Ji-Yeong
    • Journal of KIBIM
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    • v.7 no.4
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    • pp.8-20
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    • 2017
  • When it comes to set up the BIM through the reverse engineering, the level of detail(LoD) required for finalized outcomes is different from each purpose. Therefore, it is necessary to establish some concrete criteria which describe the definition of LoDs on 3D modeling for the purpose of each reverse engineering. This research shows the criteria of the 1) positional accuracy, 2) generalization level, 3) scale level, 4) scope of description, and 5) the area available for application by classifying LoD from 1 to 6 on 3D modeling for each purpose of reverse engineering. Moreover, through applying those criteria for the 3D point cloud dataset of building made by terrestrial LiDAR, this research finds out the working hour of 3D modeling of reverse engineering by each LoDs according to defined LoD criteria for each level. It is expected that those findings, how those criteria of LoD on reverse engineering are utilized for modeling-workers to decide whether the outcomes can be suitable for their budget, applicable fields or not, would contribute to help them as a basic information.

Assessment Model for the Safety and Serviceability of Structures using Terrestrial LiDAR (지상라이다를 이용한 구조물의 안전 및 사용성 평가 모델)

  • Lee, Hong-Min;Park, Hyo-Seon
    • Journal of the Korean Society of Hazard Mitigation
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    • v.6 no.3 s.22
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    • pp.17-28
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    • 2006
  • Structural health monitoring is important to maintain the safety and serviceability of the structures. The displacement in the structure should be precisely and frequently monitored because it is a direct assessment index indicating its stiffness. However, no practical method has been developed to monitor such displacement precisely, particularly for high-rise buildings and long span bridges because they cannot be easily accessible. To overcome such difficult accessibility, we propose to use a LIDAR system that remotely samples the surface of an object using laser pulses and generates the coordinates of numerous points on the surface. In this study, using terrestrial LiDAR, we develop a novel displacement measuring model for structural health monitoring and perform an indoor experiment to prove its performance.

Planar Patch Extraction from LiDAR Data Using Optimal Parameter Selection (최적 매개변수 선정을 이용한 라이다 데이터로부터 3차원 평면 추출)

  • Shin, Sung-Woong;Bang, Ki-In;Cho, Woo-Sug
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.1
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    • pp.97-103
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    • 2011
  • LiDAR system has become a popular tool for generating 3D surface data such as Digital Surface Model. Extraction of valuable information, such as digital building models, from LiDAR data has been an attractive research subject. This research addresses to extract planar patches from LiDAR data. Planar patches are important primitives consisting of man-made objects such as buildings. In order to determine the best fitted planes, this research proposed a method to reduce/eliminate the impact of the outliers and the intersection areas of two planes. After finishing plane fitting, planar patches are segmented by pseudo color values which are calculated by determined three plane parameters for each LiDAR point. In addition, a segmentation procedure is conducted using the pseudo color values to find planar patches. This paper evaluates the feasibility of the proposed method using both airborne and terrestrial LiDAR data.

A Study on Damage factor Analysis of Slope Anchor based on 3D Numerical Model Combining UAS Image and Terrestrial LiDAR (UAS 영상 및 지상 LiDAR 조합한 3D 수치모형 기반 비탈면 앵커의 손상인자 분석에 관한 연구)

  • Lee, Chul-Hee;Lee, Jong-Hyun;Kim, Dal-Joo;Kang, Joon-Oh;Kwon, Young-Hun
    • Journal of the Korean Geotechnical Society
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    • v.38 no.7
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    • pp.5-24
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    • 2022
  • The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.

An Accuracy Assessment of the Terrestrial LiDAR for Landslide Monitoring (산사태 모니터링을 위한 지상라이다 자료의 정확도 평가)

  • Park, Jae-Kook;Lee, Sang-Yun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.2
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    • pp.117-127
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    • 2008
  • Korea has a large number of landslides due to localized torrential downpours and typhoons in summer, causing great human damage and economic losses. In particular, most roads in the Gangwon area are located in mountains, making them expose to a great risk of landslide. Therefore, it is urgent to prepare countermeasures to prevent these landslides. Necessary for that are various slope investigation and high-tech observation techniques for slope maintenance. Recently there have been slope observation techniques using optical fiber sensors, GPS, CCD cameras, Total Station and satellite images; however, these are not used much due to poor economic feasibility, low accuracy and efficiency. This study evaluated accuracy of displacement extraction of model slopes using terrestrial LiDAR to determine its application to landslide monitoring. As a result, it can measure several mm of minute displacement with high accuracy and help to rapidly obtain geographical features of slope.

Classification of Terrestrial LiDAR Data Using Factor and Cluster Analysis (요인 및 군집분석을 이용한 지상 라이다 자료의 분류)

  • Choi, Seung-Pil;Cho, Ji-Hyun;Kim, Yeol;Kim, Jun-Seong
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.139-144
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    • 2011
  • This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.

A Filtering Technique of Terrestrial LiDAR Data on Sloped Terrain (사면지형에서 지상라이다 자료의 필터링 기법)

  • Shin, Yoon Su;Choi, Seung Pil;Kim, Jun Seong;Kim, Uk Nam
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.6_1
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    • pp.529-538
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    • 2012
  • By using an algorithm derived by a multiple linear regression analysis, a technique for filtering was developed; and by using the developed technique, the results of conducting filtering of the raw data collected via scanning with a terrestrial LiDAR the actual sloped terrain was analyzed. As such, when filtering was applied by dividing the observation areas into two areas with the topographical line as a reference in order to improve the filtering accuracy, it was seen that the filtering accuracy improved by about 8.73% as compared to when filtering was applied without dividing the observation area. In addition, considering the fact that the accuracy improved by 5~7% when the sloped sides of a multicurvature topography were divided and a complex filtering applied as compared to when filtering was applied for the entire area or by regions, it can be asserted that the accuracy was higher when a complex filtering was conducted by dividing the sloped areas where the slope is not constant due to the multi-curvature of topography.

Experiment of 3D LOS Analysis of Gridded Terrestrial LiDAR Data (격자화된 지상라이다 자료의 3차원 가시선 분석 실험)

  • Hong, Tae-Min;Pyeon, Mu-Wook;Kang, Nam-Gi;Lee, Byoung-Kil;Kim, Chang-Jae
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.3
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    • pp.357-365
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    • 2009
  • RTLS(Real-Time location system) for Location tracking of personnel and equipment of a construction site is now in development, among these techniques the wireless LAN-based techniques are being considered. To introduce these techniques to the construction site, the 3-dimensional visibility analysis prior to the installation location of AP must be simulated. At this time, three-dimensional visibility analysis considering the propagation distance of RTLS signal of AP(Access Point) should be performed. In this research, two processing methods LOS boundary are tested to various grid size of gridded terrestrial LiDAR data, and the results were compared. In evaluations of visible area, the Scanline Fill-Method shows approximately 7.4% more visible area than the Shadow Clipping-Method, but the Shadow Clipping-Method shows stable results for the grid size. About the processing time, the Scanline Fill-Method is about 2 times faster compared to the Shadow Clipping-Method.