• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.541-550
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• 2021

While open-air compost has value as a source of nutrients for crops in agricultural land, it acts as a pollution that adversely affects the environment during rainfall, and management is required. In this study, it was intended to analyze the accuracy of calculating open-air compost volume using fixed-wing UAV (unmanned aerial vehicle) capable of acquiring a wide range of images and automatic path flights and to identify the possibility of utilization. In order to evaluate the accuracy of calculating the three open-air compost volume, ground LiDAR surveys and precision surveys using a rotary UAV were performed. and compared with the open-air compost volume acquired through a fixed-wing UAV. As a result of comparing the calculation of open-air compost volume based on the ground LiDAR, the error rate of the rotary-wing was estimated to be ±5%, and the error rate of fixed-wing was -15 ~ -4%. one of three open-air compost volume calculated by fixed-wing was underestimated as about -15 %, but the deviation of the open-air compost volume was 2.9 m3, which was not significant. In addition, as a result of periodic monitoring of open-air compost using fixed-wing UAV, changes in the volume of open-air compost with time could be confirmed. These results suggested that efficient open-air compost monitoring and non-point pollutants in agricultural for a wide range using fixed-wing UAV is possible.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.397-406
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• 2022

Recently, research and development to revitalize smart construction are being actively carried out. Accordingly, 3D mapping technology that digitizes construction site is drawing attention. To create a 3D digital map for construction site a point cloud generation method based on LiDAR(Light detection and ranging) using MMS(Mobile mapping system) is mainly used. The purpose of this study is to analyze the accuracy of MMS LiDAR-based point cloud data. As a result, accuracy of MMS point cloud data was analyzed as dx = 0.048m, dy = 0.018m, dz = 0.045m on average. In future studies, accuracy comparison of point cloud data produced via UAV(Unmanned aerial vegicle) photogrammetry and MMS LiDAR should be studied.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.232-238
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• 2020

In this paper, we study on aerial objects detection and position estimation algorithm for the safety of UAV that flight in BVLOS. We use the vision sensor and LiDAR to detect objects. We use YOLOv2 architecture based on CNN to detect objects on a 2D image. Additionally we use a clustering method to detect objects on point cloud data acquired from LiDAR. When a single sensor used, detection rate can be degraded in a specific situation depending on the characteristics of sensor. If the result of the detection algorithm using a single sensor is absent or false, we need to complement the detection accuracy. In order to complement the accuracy of detection algorithm based on a single sensor, we use the Kalman filter. And we fused the results of a single sensor to improve detection accuracy. We estimate the 3D position of the object using the pixel position of the object and distance measured to LiDAR. We verified the performance of proposed fusion algorithm by performing the simulation using the Gazebo simulator.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.111-112
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• 2022

모든 도시가 발전하고 번창하기 위해서는 핵심기반시설의 재난 및 안전이 선제적으로 확보되어야 한다. 본 논문에서는 환경핵심기반시설을 중심으로 지역사회가 지속 가능한 녹색도시로 거듭나기 위해 재난준비태세 증진에 실제 활용 가능한 위험지도를 드론에 장착한 LiDAR 센서를 통해 수집한 고도 데이터를 바탕으로 제작하였다. 나아가 지진과 같은 재난 발생 시 시설에서부터 확산하는 관리 오염물의 경로 및 범위를 시범 모의하여, 기능 연속성 계획 및 재난대응 가이드와 연계를 하는 방안을 제시함으로 지자체 중심의 통합적 지역사회의 노력이 발현될 수 있도록 기초적 연구를 진행하고, 전략적 활성화 방안을 제시하였다. 본 연구는 끊임없는 성장과 거듭되는 개발로 인해 변화하는 도시의 형상에 따라 리스크를 최신화하여 대응력을 높이고, 이해관계자들에게 시각화된 재난 범위 모의를 제시함으로써 지역사회와 지자체 역량에 따른 협력적 재난대응태세에 필요한 프레임워크 도출 및 계획수립을 가능하게 한다는 점에서 큰 의의를 지닌다. 또한, 각 영역별 전문가들의 자문을 통하여 본 논문에서 제시된 확산 모의의 방법론이 타당함을 확인하였다. 무엇보다 모호한 "가능한 신속한 자원관리"와 같은 추상적인 대응계획이 아닌, 객관적인 재난자원관리계획을 수립할 수 있게 함으로써 추후 국가적 재난 및 안전역량을 계량화시킬 수 있을 것으로 사료된다.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.111-124
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• 2021

Recently, Interest in the restoration and 3D reconstruction of cultural properties due to the fire of Notre Dame Cathedral on April 15, 2019 has been focused once again after the 2008 Sungnyemun fire incident in South Korea. In particular, research to restore and reconstruct the actual measurement of cultural properties using LiDAR(Light Detection and ranging) and conventional surveying, which were previously used, using various 3D reconstruction technologies, is being actively conducted. This study acquires data using unmanned aerial imagery of UAV(Unmanned Aerial Vehicle), which has recently established itself as a core technology in the era of the 4th industrial revolution, and the existing CRP(Closed Range Photogrammetry) and terrestrial LiDAR scanning for the Recumbent Buddha of Unju Temple. Then, the 3D reconstruction was performed with three fusion models based on SfM(Structure-from-Motion), and the reproducibility and accuracy of the models were compared and analyzed. In addition, using the best fusion model among the three models, the relationship with the Polar Star(Polaris) was confirmed based on the real world coordinates of the Recumbent Buddha, which contains the astronomical history of Buddhism in the early 11th century Goryeo Dynasty. Through this study, not only the simple external 3D reconstruction of cultural properties, but also the method of reconstructing the historical evidence according to the type and shape of the cultural properties was sought by confirming the historical evidence of the cultural properties in terms of spatial information.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.27-35
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• 2019

The purpose of this study is to analyze the displacement characteristics in slow-moving landslide area using digital elevation model and airborne LiDAR when unpredictable disaster such as slow-moving landslide occurred. We also aimed to provide basic data for establishing a rapid, reasonable and effective restoration plan. In this study, slow-moving landslide occurrence cracks were selected through the airborne LiDAR data, and the topographic changes and the scale of occurrence were quantitatively analyzed. As a result of the analysis, the study area showed horseshoe shape similar to the general form of slow-moving landslide occurrence in Korea, and the direction of movement was in the north direction. The total area of slow-moving landslide damage was estimated to about 2.5ha, length of landsldie scrap 327.3m, average width 19.3m, and average depth 8.6m. The slow-moving landslides did not occur on a large scale but occurred on the adjacent slope where roads were located, caused damage to retaining walls and roads. The field survey of slow-moving landslides was limited by accessibility and safety issues, but there was an advantage that accurate analysis was possible through the airborne LiDAR. However, because airborne LiDAR has costly disadvantages, it has proposed a technique to mount LiDAR on UAV for rapidity, long-term monitoring. In a slow-moving landslide damage area, information such as direction of movement of cracks and change of scale should be acquired continuously to be used in restoration planning and prevention of damage.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1325-1332
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• 2023

Recently, much research is being conducted based on point cloud data for the growth of innovations such as construction automation in the transportation field and virtual national space. This data is often measured through remote control in terrain that is difficult for humans to access using devices such as UAVs and UGVs. Drones, one of the UAVs, are mainly used to acquire point cloud data, but photogrammetry using a vision camera, which takes a lot of time to create a point cloud map, is difficult to apply in construction sites where the terrain changes periodically and surveying is difficult. In this paper, we developed a point cloud mapping system by adopting non-repetitive scanning LiDAR and attempted to confirm improvements through field application. For accuracy analysis, a point cloud map was created through a 2 minute 40 second flight and about 30 seconds of software post-processing on a terrain measuring 144.5 × 138.8 m. As a result of comparing the actual measured distance for structures with an average of 4 m, an average error of 4.3 cm was recorded, confirming that the performance was within the error range applicable to the field.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.6
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• pp.1-14
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• 2019

Carbon storage is one of the regulating ecosystem services provided by urban street trees. It is important that evaluating the economic value of ecosystem services accurately. The carbon storage of street trees was calculated by measuring the morphological parameter on the field. As the method is labor-intensive and time-consuming for the macro-scale research, remote sensing has been more widely used. The airborne Light Detection And Ranging (LiDAR) is used in obtaining the point clouds data of a densely planted area and extracting individual trees for the carbon storage estimation. However, the LiDAR has limitations such as high cost and complicated operations. In addition, trees change over time they need to be frequently. Therefore, Structure from Motion (SfM) photogrammetry with unmanned Aerial Vehicle (UAV) is a more suitable method for obtaining point clouds data. In this paper, a UAV loaded with a digital camera was employed to take oblique aerial images for generating point cloud of street trees. We extracted the diameter of breast height (DBH) from generated point cloud data to calculate the carbon storage. We compared DBH calculated from UAV data and measured data from the field in the selected area. The calculated DBH was used to estimate the carbon storage of street trees in the study area using a regression model. The results demonstrate the feasibility and effectiveness of applying UAV imagery and SfM technique to the carbon storage estimation of street trees. The technique can contribute to efficiently building inventories of the carbon storage of street trees in urban areas.