• Title/Summary/Keyword: Drone LiDAR

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Roughness Analysis of Paved Road using Drone LiDAR and Images (드론 라이다와 영상에 의한 포장 노면의 평탄성 분석)

  • Jung, Kap Yong;Park, Joon Kyu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.1
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    • pp.55-63
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    • 2021
  • The roughness of the road is an important factor directly connected to the ride comfort, and is an evaluation item for functional evaluation and pavement quality management of the road. In this study, data on the road surface were acquired using the latest 3D geospatial information construction technology of ground LiDAR, drone photogrammetry, and drone LiDAR, and the accuracy and roughness of each method were analyzed. As a result of the accuracy evaluation, the average accuracy of terrestrial LiDAR were 0.039m, 0.042m, 0.039m RMSE in X, Y, Z direction, and drone photogrammetry and drone LiDAR represent 0.072~0.076m, 0.060~0.068m RMSE, respectively. In addition, for the roughness analysis, the longitudinal and lateral slopes of the target section were extracted from the 3D geospatial information constructed by each method, and the design values were compared. As a result of roughness analysis, the ground LiDAR showed the same slope as the design value, and the drone photogrammetry and drone LiDAR showed a slight difference from the design value. Research is needed to improve the accuracy of drone photogrammetry and drone LiDAR in measurement fields such as road roughness analysis. If the usability through improved accuracy can be presented in the future, the time required for acquisition can be greatly reduced by utilizing drone photogrammetry and drone LiDAR, so it will be possible to improve related work efficiency.

Accuracy Evaluation of Earthwork Volume Calculation According to Terrain Model Generation Method (지형모델 구축 방법에 따른 토공물량 산정의 정확도 평가)

  • Park, Joon Kyu;Jung, Kap Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.1
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    • pp.47-54
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    • 2021
  • Calculation of quantity at construction sites is a factor that has a great influence on construction costs, and it is important to calculate accurate values. In this study, topographic model was created by using drone photogrammetry and drone LiDAR to estimate earthwork volume. ortho image and DSM (Digital Surface Model) were constructed for the study area by drone photogrammetry, and DEM (Digital Elevation Model) of the target area was established using drone LiDAR. And through accuracy evaluation, accuracy of each method are 0.034m, 0.35m in horizontal direction, 0.054m, 0.25m in vertical direction. Through the research, the usability of drone photogrammetry and drone LiDAR for constructing geospatial information was presented. As a result of calculating the volume of the study site, the UAV photogrammetry showed a difference of 1528.1㎥ from the GNSS (Global Navigation Satellite System) survey performance, and the 3D Laser Scanner showed difference of 160.28㎥. The difference in the volume of earthwork is due to the difference in the topographic model, and the efficiency of volume calculation by drone LiDAR could be suggested. In the future, if additional research is conducted using GNSS surveying and drone LiDAR to establish topographic model in the forest area and evaluate its usability, the efficiency of terrain model construction using drone LiDAR can be suggested.

Development of LiDAR Drone-based Point Cloud Data Accuracy Verification Technology (드론 LiDAR를 활용한 점군 데이터 정확도 검증 기술 개발)

  • Jae-Woo Park;Dong-Jun Yeom
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.6_3
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    • pp.1233-1241
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    • 2023
  • This paper investigates the efficient application of drone LiDAR technology for acquiring precise point cloud data in construction and civil engineering. A structured workflow encompassing data acquisition, processing, and accuracy verification is introduced. Practical testing on a construction site affirms that drone LiDAR surveying yields accurate and reliable data across various applications. With a focus on accuracy and verification, the results contribute to the progression of surveying methodologies in construction and civil engineering. The findings provide valuable insights into the dynamic technological landscape of these fields, establishing a foundation for more effective and precise surveying techniques. This study underscores the transformative potential of drone LiDAR technology in shaping the future of construction and civil engineering survey practices.

Comparison of Characteristics of Drone LiDAR for Construction of Geospatial Information in Large-scale Development Project Area (대규모 개발지역의 공간정보 구축을 위한 드론 라이다의 특징 비교)

  • Park, Joon-Kyu;Lee, Keun-Wang
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.1
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    • pp.768-773
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    • 2020
  • In large-scale land development for the rational use and management of national land resources, the use of geospatial information is essential for the efficient management of projects. Recently, drone LiDAR (Light Detection And Ranging) has attracted attention as an effective geospatial information construction technique for large-scale development areas, such as housing site construction and open-pit mines. Drone LiDAR can be classified into a method using SLAM (Simultaneous Localization And Mapping) technology and a GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit) method. On the other hand, there is a lack of analytical research on the application of drone LiDAR or the characteristics of each method. Therefore, in this study, data acquisition, processing, and analysis using SLAM and GNSS/IMU type drone LiDAR were performed, and the characteristics and utilization of each were evaluated. As a result, the height direction accuracy of drone LiDAR was -0.052~0.044m, which satisfies the allowable accuracy of geospatial information for mapping. In addition, the characteristics of each method were presented through a comparison of data acquisition and processing. Geospatial information constructed through drone LiDAR can be used in several ways, such as measuring the distance, area, and inclination. Based on such information, it is possible to evaluate the safety of large-scale development areas, and this method is expected to be utilized in the future.

Efficient method for acquirement of geospatial information using drone equipment in stream (드론을 이용한 하천공간정보 획득의 효율적 방안)

  • Lee, Jong-Seok;Kim, Si-Chul
    • Journal of Korea Water Resources Association
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    • v.55 no.2
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    • pp.135-145
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    • 2022
  • This study aims to verify the Drone utilization and the accuracy of the global navigation satellite system (GNSS), Drone RGB (Photogrammetry) (D-RGB), and Drone LiDAR (D-LiDAR) surveying performance in the downstream reaches of the local stream. The results of the measurement of Ground Control Point (GCP) and Check Point (CP) coordinates confirmed the excellence. This study was carried out by comparing GNSS, D-RGB, and D-LiDAR with the values which the hydraulic characteristics calculated using HEC-RAS model. The accuracy of three survey methods was compared in the area of the study which is the ownership station, to 6 GCP and 3 CP were installed. The comparison results showed that the D-LiDAR survey was excellent. The 100-year frequency design flood discharge was applied in the channel sections of the small stream. As a result of D-RGB surveying 2.30 m and D-LiDAR 1.80 m in the average bed elevation, and D-RGB surveying 4.73 m and D-LiDAR 4.25 m in the average flood condition. It is recommended that the performance of D-LiDAR surveying is efficient method and useful as the surveying technique of the geospatial information using the drone equipment in stream channel.

Utilization of Drone LiDAR for Field Investigation of Facility Collapse Accident (붕괴사고 현장조사를 위한 드론 LiDAR 활용)

  • Yonghan Jung ;Eontaek Lim ;Jaewook Suk;Seul Koo;Seongsam Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_2
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    • pp.849-858
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    • 2023
  • Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.

Development of Pointcloud Data Integration Technology in Construction Sites via Drone Photogrammetry and MMS LiDAR (드론 및 MMS를 활용한 건설현장 점군 데이터 통합 기술 개발)

  • Jae-Woo Park;Dong-Jun Yeom
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.6_2
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    • pp.1145-1153
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    • 2023
  • This study presents the development of pointcloud data integration technology in construction sites via drone photogrammetry and MMS LiDAR. The integration of pointcloud data from drones and MMS technology can provide precise and accurate 3D digital maps of construction sites, which can benefit the development of smart construction and BIM. The advantages of using both drones and MMS technology for pointcloud data acquisition in construction sites are discussed, along with the limitations and challenges of using drone photogrammetry and MMS LiDAR for pointcloud data integration. The results of this study can contribute to the advancement of pointcloud data integration technology in construction sites and improve the efficiency and accuracy of construction projects.

Usability Evaluation of the Drone LiDAR Data for River Surveying (하천측량을 위한 드론라이다 데이터의 활용성 평가)

  • Park, Joon-Kyu;Um, Dae-Yong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.5
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    • pp.592-597
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    • 2020
  • Currently, river survey data is mainly performed by acquiring longitudinal and cross-sectional data of rivers using total stations or the GNSS(Global Navigation Satellite System). There is not much research that addresses the use of LiDAR(Light Detection and Ranging)systems for surveying rivers. This study evaluates the applicability of using LiDAR data for surveying rivers The Ministry of Land, Infrastructure and Transport recently launched a drone-based river fluctuation survey. Pilot survey projects were conducted in major rivers nationwide. Studies related to river surveying were performed using the ground LiDAR(Light Detection And Ranging)system.Accuracy was ensured by extracting the linearity of the object and comparing it with the total station survey performance. Data on trees and other features were extracted to generate three-dimensional geospatial information for the point-cloud data on the ground.Deviations were 0.008~0.048m. and compared with the results of surveying GNSS and the use of drone LiDAR data. Drone LiDAR provided accurate three-dimensional spatial information on the entire target area. It was able to reduce the shaded area caused by the lack of surveying results of the target area. Analyses such as those of area and slope of the target sites are possible. Uses of drones may therefore be anticipated for terrain analyses in the future.

Study on Applicability of Cloth Simulation Filtering Algorithm for Segmentation of Ground Points from Drone LiDAR Point Clouds in Mountainous Areas (산악지형 드론 라이다 데이터 점군 분리를 위한 CSF 알고리즘 적용에 관한 연구)

  • Seul Koo ;Eon Taek Lim ;Yong Han Jung ;Jae Wook Suk ;Seong Sam Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_2
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    • pp.827-835
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    • 2023
  • Drone light detection and ranging (LiDAR) is a state-of-the-art surveying technology that enables close investigation of the top of the mountain slope or the inaccessible slope, and is being used for field surveys in mountainous terrain. To build topographic information using Drone LiDAR, a preprocessing process is required to effectively separate ground and non-ground points from the acquired point cloud. Therefore, in this study, the point group data of the mountain topography was acquired using an aerial LiDAR mounted on a commercial drone, and the application and accuracy of the cloth simulation filtering algorithm, one of the ground separation techniques, was verified. As a result of applying the algorithm, the separation accuracy of the ground and the non-ground was 84.3%, and the kappa coefficient was 0.71, and drone LiDAR data could be effectively used for landslide field surveys in mountainous terrain.

An Automatic Collision Avoidance System for Drone using a LiDAR sensor (LiDAR 센서를 이용한 드론 자동 충돌방지 시스템)

  • Chong, Ui-Pil;An, Woo-Jin;Kim, Yearn-Min;Lee, Jung-Chul
    • Journal of the Institute of Convergence Signal Processing
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    • v.19 no.2
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    • pp.54-60
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    • 2018
  • In this paper, we propose an efficient automatic control method for the collision avoidance of drones. In general, the drones are controlled by transmitting to the flight control (FC) module the received PWM signals transmitted from a RC controller which transduce movements of the knob into PWM signal. We implemented the collision avoidance module in-between receiver and FC module to monitor and change the throttle, pitch and roll control signals to avoid drone collision. In order to avoid the collision, a LiDAR distance sensor and a servo-motor are installed and periodically measure the obstacle distance within -45 degrees from 45 degrees in flight direction. If the collision is predicted, the received PWM signal is changed and transmitted to the FC module to prevent the collision. We applied our proposed method to a hexacopter and the experimental results show that the safety is improved because it can prevent the collision caused by the inadvertency or inexperienced maneuver.