• Journal of Advanced Navigation Technology
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• v.12 no.6
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• pp.548-553
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• 2008

While in the past map-making process by field survey devices such as MicroStation needs more time relatively, we can make more precise map effectively with airbone LiDAR and GPS devices. Also the data, captured by LiDAR, are very large in size and so it needs to use Relational DBMS to manage and process LiDAR data. In this study we propose how to store and manage LiDAR data using RDBMS.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.345-352
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• 2022

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.74-88
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• 2010

In this study, the points of LiDAR were modified in order to generate various DEM resolutions by applying LiDAR data in Ulsan. Since the LiDAR data have points with 1m intervals, the number of points for each resolution was modified to the size of 1, 5, 10, 30, 50, 100m by uniformly eliminating the points. A runoff analysis was performed on Taehwa river and its tributary, Dongcheon, with 200 year rainfall exceedance probability. 2-dimensional inundation analysis was performed based on the density of LiDAR data using FLUMEN, which was used to establish domestic flood risk map. Once DEM data obtained from LiDAR survey are used, it is expected that the study results can be used as data in determining optimal grid spacing, which is economical, effective and accurate in establishing flood defence plans including the creation of flood risk map.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.179-190
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• 2017

A terrestrial LiDAR survey was conducted and unmanned aerial vehicle(UAV) images were taken for target cultural properties to present the utilization measures of terrestrial LiDAR and UAV in three-dimensional modeling of cultural properties for the identification of the status and restoration of cultural properties. Then the accuracy of the point clouds generated through this process was compared, an overlap analysis of the 3D model was conducted, and a convergence model was created. According to the results, the modeling with terrestrial LiDAR is more appropriate for precise survey because 3D modeling for the detection of displacement and deformation of cultural properties requires an accuracy of mm units. And UAV model has limitation as the impossibility of detailed expression of parts with sharp unevenness such as cracks of bricks. However, it is found that the UAV model has a wide range of modeling and has the advantage of modeling of real cultural properties. Finally, the convergence model created in this study using the advantages of the terrestrial LiDAR model and the UAV model could be efficiently utilized for the basic data development of cultural properties.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1859-1867
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• 2021

Multi LiDAR sensors are being mounted on autonomous vehicles, and a system to multi LiDAR sensors data is required. When sensors data is transmitted or processed to the main processor, a huge amount of data causes a load on the transport network or data processing. In order to minimize the number of load overhead into LiDAR sensor processors, only semantic data is transmitted through data comparison between frames in LiDAR data. When data from 4 LiDAR sensors are processed in a static environment without moving objects and a dynamic environment in which a person moves within sensor's field of view, in a static experiment environment, the transmitted data reduced by 89.5% from 232,104 to 26,110 bytes. In dynamic environment, it was possible to reduce the transmitted data by 88.1% to 29,179 bytes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.217-228
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• 2024

LiDAR(Light Detection And Ranging) sensors, which play a pivotal role among cameras, RADAR(RAdio Detection And Ranging), and ultrasonic sensors for the safe operation of autonomous vehicles, can recognize and detect objects in 360 degrees. However, since LiDAR sensors use lasers to measure distance, they are vulnerable to attackers and face various security threats. In this paper, we examine several security threats against LiDAR sensors: relay, spoofing, and replay attacks, analyze the possibility and impact of physical jamming attacks, and analyze the risk these attacks pose to the reliability of autonomous driving systems. Through experiments, we show that jamming attacks can cause errors in the ranging ability of LiDAR sensors. With vehicle-to-vehicle (V2V) communication, multi-sensor fusion under development and LiDAR anomaly data detection, this work aims to provide a basic direction for countermeasures against these threats enhancing the security of autonomous vehicles, and verify the practical applicability and effectiveness of the proposed countermeasures in future research.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.287-291
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• 2005

LiDAR 자료로부터 3차원 공간 정보체계를 구축하기 위하여 LiDAR 포인트를 지면과 비지면 포인트로 분리하고 비지면 포인트를 각각의 개체(건물, 수목, 기타 인공 구조물 등)별로 분리하는 과정이 필수적이다. 그러나 LiDAR 자료는 불규칙한 분포의, 방대한 양의 포인트로 구성되어 있어 이를 처리하기 위한 특별한 형태의 자료 구조 체계의 구축이 필요하다. 본 연구에서는 유사한 고도를 갖는 인접한 포인트들로 클래스를 형성하여, 새로운 포인트에 대하여 기존 클래스 포인트들과의 인접성 및 고도 유사성을 검토함으로써 분류를 수행하였다. 이를 위하여 원 LiDAR 자료 구조를 이용하였으며 결과적으로 지면과 비지면의 분리 및 각 비지면 개체간의 분리를 동시에 수행할 수 있었다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.13-15
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• 2008

LiDAR(Light Detection and Ranging)는 3차원공간정보를 신속하게 구축할 수 있는 최신 측량 기술로써 최근 그 활용도와 중요성이 높아지고 있다. 그러나 LiDAR 관측성과는 시스템 특성상 높은 수직 정확도를 제공하고 있으나 항공사진과 같이 정확한 평면위치를 측정하여 조정할 수 없으므로 상대적으로 낮은 수평 정확도를 가지고 있다. 본 연구에서는 LiDAR 관측에 의한 건물의 벽면 반사파를 이용하여 건물모서리의 평면 좌표(x, y)를 추출하고, 이를 항공삼각측량에 의한 평면좌표와 비교분석하였다. 그 결과 LiDAR의 평면좌표가 항공삼각측량에 의한 평면좌표에 비해 상대적으로 이동되어 있음을 확인할 수 있었다. 따라서, 2차원 좌표변환을 수행하여 LiDAR의 평면좌표를 보정하여 정확도를 향상시킬 수 있었고, 이를 이용하여 향후 LiDAR 관측성과 품질 향상에 도움이 될 것이라 기대한다.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.119-124
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• 2004

LiDAR 자료를 이용한 지형 및 공간 정보 자료를 구축하기 위해서는 LiDAR 자료의 오차 보정, 건물영역 및 지면 분리, 건물 및 지형의 재구성 등의 과정이 필요하다. 그 중에서 건물영역 분리 과정은 막대한 양의 LiDAR 자료에 대한 직, 간접적인 처리를 필요로 하며 결과물의 품질에도 큰 영향을 미친다. 본 연구에서는 LiDAR 자료로부터 건물 영역을 분리해 내기 위하여 LiDAR 원 자료를 그대로 활용하는 방식을 제안하였다. 항공레이저측량은 스캔라인을 따라 취득되는 포인트정보를 순서대로 저장하여 제공하므로 LiDAR 자료로부터 연속적으로 입력되는 포인트들은 서로 인접할 가능성이 높다. 이와 같은 특성을 이용하여 유사한 고도 값을 갖는 인접 포인트들로 클래스를 형성하고 새로운 포인트가 속할 클래스를 검색하여 편입시킴으로써 건물영역을 분리해 낸다. 아울러 각 건물 클래스에 대한 레이블링도 자동적으로 수행하며 새로운 포인트가 편입될 클래스를 검색하는 방법에 있어서도, 클래스의 검색 순서와 클래스의 자료 구조를 효율적으로 운용함으로써 성능 향상을 도모하였다.