• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.220-220
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• 2021

2020년 장마는 6월 중순부터 8월 중순까지 전국적으로 평균 687 mm의 강수가 내려, 1973년 이후 역대 2위 강수량을 기록하였으며, 연이은 태풍으로 큰 인명 및 재산 피해가 발생하였다. 특히, 섬진강 및 한탄천 등에서 계획홍수위를 초과하는 홍수로 인해 상당수의 제방이 월류로 인해 붕괴된 것으로 나타났다. 따라서, 향후 기후변화에 따른 연평균 강수량이 증가할 것으로 전망되는 가운데 집중호우로 인한 제방 붕괴 피해를 최소화하기 위한 고도화된 기술 개발을 통한 선제적 재발 방지대책이 필요한 시점이다. 한국건설기술연구원은 바이오폴리머라는 새로운 친환경 신소재를 이용하여 제방의 안정성 평가 기술 개발 연구를 수행하고 있다. 이에 안동하천연구센터에서는 실규모에 준하는 제방모형(높이 3 m, 사면경사 1:2, 길이 10 m 이상)을 제작하고, 제방 표면에 바이오폴리머 신소재를 처리하여 전방 월류 흐름 유도에 따른 실규모 제방붕괴실험을 수행하였다. 또한, 신소재 보강 및 무보강 조건에 따른 영상분석 기반 붕괴지연효과를 정량적으로 분석하여 신소재의 성능을 평가하였다. 하지만, 기존에 수행된 실험은 댐 붕괴 흐름과 같이 홍수파가 발생하여 제내지로 퍼져 나가는 형태로 진행되어, 보강공법의 검증에 있어 실제 하천에서 발생하는 횡월류 흐름을 재현하지 못한다는 한계를 가지고 있다. 본 연구에서는 횡월류 흐름(0.6 m³/s 이상)을 발생시켜 수리실험에 따른 축척효과(scale effect)를 최소화하고, 현장에 대한 충분한 자연성을 재현하는 것을 목표로 하여 실험을 수행하였다. 실험 조건은 1) 신소재가 처리된 식생 제방, 2) 신소재가 처리되지 않은 식생 제방으로 각각의 조건에 따른 횡월류 흐름 및 제방 붕괴를 유도하여 영상분석 기법(이미지 픽셀분석 및 3D 포인트 클라우드 모델링)을 통한 침식 저항에 관한 분석결과를 제시하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.507-513
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• 2021

GPR (Ground Penetrating RADAR) is a sensor that inspects the pavement state of roads, sinkholes, and underground pipes. It is widely used in road management. MMS (Mobile Mapping System) creates a detailed and accurate road map of the road surface and its surroundings. If both types of data are built in the same area, it is efficient to construct both ground and underground spatial information at the same time. In addition, since it is possible to grasp the road and important facilities around the road, the location of underground pipelines, etc. without special technology, an intuitive understanding of the site is also possible, which is a useful tool in managing the road or facilities. However, overseas equipment to which this latest technology is applied is expensive and does not fit the domestic situation. LiDAR (Light Detection And Raging) and GNSS/INS (Global Navigation Satellite System / Inertial Navigation System) were synchronized in order to replace overseas developed equipment and to secure original technology to develop domestic equipment in the future, and GPR data was also synchronized to the same GNSS/INS. We developed software that performs georeferencing using the location and attitude information from GNSS/INS at the time of acquiring synchronized GPR data. The experiments were conducted on the road site by dividing the open sky and the non-open sky. The road and surrounding facilities on the ground could be easily checked through the 3D point cloud data acquired through LiDAR. Georeferenced GPR data could also be viewed with a 3D viewer along with point cloud data, and the location of underground facilities could be easily and quickly confirmed through GPR data.

• Korean Journal of Optics and Photonics
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• v.27 no.4
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• pp.133-142
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• 2016

This paper presents the design and simulation of a three-dimensional pixel-by-pixel scanning light detection and ranging (LIDAR) system with a microelectromechanical system (MEMS) scanning mirror and direct sequence optical code division multiple access (DS-OCDMA) techniques. It measures a frame with $848{\times}480$ pixels at a refresh rate of 60 fps. The emitted laser pulse waves of each pixel are coded with DS-OCDMA techniques. The coded laser pulse waves include the pixel's position in the frame, and a checksum. The LIDAR emits the coded laser pulse waves periodically, without idle listening time to receive returning light at the receiver. The MEMS scanning mirror is used to deflect and steer the coded laser pulse waves to a specific target point. When all the pixels in a frame have been processed, the travel time is used by the pixel-by-pixel scanning LIDAR to generate point cloud data as the measured result.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.107-118
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• 2021

Scan-to-BIM can be precisely mod eled by measuring structures with Light Detection And Ranging (LiDAR) and build ing a 3D BIM (Building Information Modeling) model based on it, but has a limitation in that it consumes a lot of manpower, time, and cost. To overcome these limitations, studies are being conducted to perform semantic segmentation of 3D point cloud data applying deep learning algorithms, but studies on how segmentation result changes depending on learning data are insufficient. In this study, a parametric study was conducted to determine how the size and track type of railroad tunnels constituting learning data affect the semantic segmentation of railroad tunnels through deep learning. As a result of the parametric study, the similar size of the tunnels used for learning and testing, the higher segmentation accuracy, and the better results when learning through a double-track tunnel than a single-line tunnel. In addition, when the training data is composed of two or more tunnels, overall accuracy (OA) and mean intersection over union (MIoU) increased by 10% to 50%, it has been confirmed that various configurations of learning data can contribute to efficient learning.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.44-55
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• 2022

In order to automatically provide information on fruits in agricultural related broadcasting contents, instance image segmentation of target fruits is required. In addition, the information on the 3D pose of the corresponding fruit may be meaningfully used. This paper represents research that provides information about tomatoes in video content. A large amount of data is required to learn the instance segmentation, but it is difficult to obtain sufficient training data. Therefore, the training data is generated through a data augmentation technique based on a small amount of real images. Compared to the result using only the real images, it is shown that the detection performance is improved as a result of learning through the synthesized image created by separating the foreground and background. As a result of learning augmented images using images created using conventional image pre-processing techniques, it was shown that higher performance was obtained than synthetic images in which foreground and background were separated. To estimate the pose from the result of object detection, a point cloud was obtained using an RGB-D camera. Then, cylinder fitting based on least square minimization is performed, and the tomato pose is estimated through the axial direction of the cylinder. We show that the results of detection, instance image segmentation, and cylinder fitting of a target object effectively through various experiments.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.47-63
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• 2023

The Seoul Metropolitan Government is building and operating digital twin-based urban spatial information to solve various problems in the city and provide public services. Two essential factors to ensure the stable utilization of spatial information for the implementation of such a digital twin city are the latest and quality of the data. However, it is time-consuming and costly to maintain continuous updating of high-quality urban spatial information. To overcome this problem, we studied efficient urban spatial information construction technology and the operation, management, and update procedures of construction data. First, we demonstrated and applied automatic 3D building construction technology centered on point clouds using the latest hybrid sensors, confirmed that it is possible to automatically construct high-quality building models using high-density airborne lidar results, and established an efficient data management plan. By applying differentiated production methods by region, supporting detection of urban change areas through Seoul spatial feature identifiers, and producing international standard data by level, we strengthened the utilization of urban spatial information. We believe that this study can serve as a good precedent for local governments and related organizations that are considering activating urban spatial information based on digital twins, and we expect that discussions on the construction and management of spatial information as infrastructure information for city-level digital twin implementation will continue.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.189-194
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• 2019

Forest investigation is the basic data for forest preservation and forest resource development, and periodical data acquisition and management have been performed. However, most of the current forest investigations in Korea are surveys to grasp the current status of forests, and various applications have not been made as geospatial information. In this study, the unmanned aerial scanner was used to acquire and process data in the forest area and to present an efficient forest survey method through analysis of the results. Unmanned aerial scanners can extract ground below vegetation, effectively creating DEM for forest management. It can be used as geospatial information for forest investigation and management by generating accurate topographical data that is impossible in conventional photogrammetry. It can also be used to measure distances between power lines and vegetation or manage transmission lines in forest areas. The accurate vertical distance measurement for vegetation surveys can greatly improve the accuracy of labor measurement and work efficiency compared to conventional methods. In the future, the use of unmanned aerial scanners will improve the data acquisition efficiency in forest areas, and will contribute to improved accuracy and economic feasibility compared to conventional methods.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1151-1157
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• 2017

Street Trees is an important object for urban environment improvement. Especially the height of the trees needs to be precisely measured as a factor that greatly influences the removal of air pollutants in the Urban Street Canyons. In this study, we extracted the height of the tree based on the stereo image using the precisely adjusted UAV Images of the target area. The adjustment of UAV image was applied photogrammetric SfM (Structure from motion) based on the collinear condition. We measured the height of the trees on the Street Canyon using stereoscopic vision on stereo plotting system. We also acquired the height of the building adjacent to the street trees and the average height of the road surface was calculated for accurate measurement of the height of each object. Through the visual analysis with the plotting operation system, it was possible to measure height of the tree and to calculate the relative height difference value with building quickly. This means that the height of buildings and trees can be calculated without making a 3D point cloud of UAV and it has the advantage of being able to utilize non-experts. In the future, further studies for semiautomatic/automation of this technique should be performed. The development and research of these technologies is expected to help to understand the current status of environmental policies and roadside trees in urban areas.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.191-197
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• 2019

As the shipbuilding and offshore plant industries grow larger and more complex, their maintenance and inspection systems become more important. Recently, maintenance and inspection systems based on augmented reality have been attracting much attention for improving worker's understanding of work and efficiency, but it is often difficult to work with because accurate matching between the augmented model and reality information is not. To solve this problem, marker based AR technology is used to attach a specific image to the model. However, the markers get damaged due to the characteristic of the shipbuilding and offshore plant industry, and the camera needs to be able to detect the entire marker clearly, and thus requires sufficient space to exist between the operator. In order to overcome the limitations of the existing AR system, in this study, a markerless AR was adopted to accurately recognize the actual model of the pipe system that occupies the most processes in the shipbuilding and offshore plant industries. The matching methodology. Through this system, it is expected that the twist phenomenon of the augmented model according to the attitude of the real worker and the limited environment can be improved.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.549-554
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• 2021

Precise 3D road geospatial information is the basic infrastructure for autonomous driving and is essential data for safe autonomous driving. MMS (Mobile Mapping System) is being used as equipment for road spatial information construction, and related research is being conducted. However, there are insufficient studies to analyze the effect of the baseline reference point distance, which is an important factor in the accuracy of the MMS outcome, on the accuracy of the outcome. Therefore, in this study, the accuracy of the data acquired using MMS by reference point distance was analyzed. Point cloud data was constructed using MMS for the road in the study site. For data processing, 4 data were constructed considering the distance from the reference point for MMS data, and the accuracy was analyzed by comparing the results of 12 checkpoints for accuracy evaluation. The accuracy of the MMS data showed a difference of -0.09 m to 0.11 m in the horizontal direction and 0.04 m to 0.19 m in the height direction. The error in the vertical direction was larger than that in the horizontal direction, and it was found that the accuracy decreased as the distance from the reference point increased. In addition, as the length of the road increases, the distance from the reference point may vary, so additional research is needed. If the accuracy evaluation of the method using multiple reference points is made in the future, it will be possible to present an effective method of using reference points for the construction of precise road spatial information.