• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.500-503
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• 2011

본 연구에서는 Terrestrial Laser Scanning (TLS)를 이용한 보 구조물의 변위 및 응력 추정에 대한 기법을 개발하였다. TLS는 Geographic Informatio Systems (GIS) 분야에서 처음 도입된 시스템으로, 레이저 펄스를 통해 원격으로 목적물의 3차원 좌표 정보를 획득 할 수 있는 시스템이다. 그러나 이러한 TLS로부터 획득한 대상물의 3차원 좌표 데이터는 10mm 내외의 오차를 포함하고 있다. 이에 건축 구조분야에 적용 가능한 변형 정보를 획득하기 위해서는 보다 정밀한 데이터 획득을 위한 데이터 처리 기법이 필요하다. 또한 구조물의 응력의 경우 획득된 형상 위의 각 지점의 곡률로 인해 발생하기 때문에 구조물의 변형 추정시 보다 미세한 오차에도 크게 영향을 받아 심한 왜곡을 가져오게 된다. 그러므로 응력 추정시 추가적인 데이터 처리 기법이 필요하다. 이에 본 연구에서는 보 구조물의 응력을 추정할 수 있는 기법을 제시한다.

• 한국방재학회:학술대회논문집
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• 2010.02a
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• pp.34.1-34.1
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• 2010

TLS(Terrestrial Laser Scanning)는 레이저를 이용하여 물체의 3차원 위치 정보를 원격으로 획득할 수 있는 시스템이다. 그러나 TLS로부터 획득한 3차원 위치 정보는 처짐 또는 응력 평가 등에 있어서 구조 정보로서 사용하기에는 한계가 있다. 따라서 정밀한 형상정보의 획득을 위해서는 3차원 형상 좌표 정보에 대한 적절한 데이터 처리가 필요하다. 본 연구에서는 구조물에 작용하는 하중 또는 지점 조건에 대한 정보 없이 회기분석의 중첩을 이용하여 TLS로부터 얻은 대상물의 이산화 된 위치 정보로 부터 구조물의 정밀한 변형 형상을 추정할 수 있는 방법을 제시한다.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.605-616
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• 2020

The construction quality control of hull blocks is of great significance for shipbuilding. The total station device is predominantly employed in traditional applications, but suffers from long measurement time, high labor intensity and scarcity of data points. In this paper, the Terrestrial Laser Scanning (TLS) device is utilized to obtain an efficient and accurate comprehensive construction information of hull blocks. To address the registration problem which is the most important issue in comparing the measurement point cloud and the design model, an automatic registration approach is presented. Furthermore, to compare the data acquired by TLS device and sparse point sets obtained by total station device, a method for key point extraction is introduced. Experimental results indicate that the proposed approach is fast and accurate, and that applying TLS to control the construction quality of hull blocks is reliable and feasible.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.195-208
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• 2023

This study aimed to use three-dimensional point cloud data (PCD) obtained from Terrestrial Laser Scanning (TLS) and Mobile Laser Scanning (MLS) to evaluate a deep learning-based species classification model for two tree species: Pinus koraiensis and Larix kaempferi. Sixteen models were constructed based on the three conditions: LiDAR platform (TLS and MLS), down-sampling intensity (1024, 2048, 4096, 8192), and deep learning model (PointNet, PointNet++). According to the classification accuracy evaluation, the highest kappa coefficients were 93.7% for TLS and 96.9% for MLS when applied to PCD data from the PointNet++ model, with down-sampling intensities of 8192 and 2048, respectively. Furthermore, PointNet++ was consistently more accurate than PointNet in all scenarios sharing the same platform and down-sampling intensity. Misclassification occurred among individuals of different species with structurally similar characteristics, among individual trees that exhibited eccentric growth due to their location on slopes or around trails, and among some individual trees in which the crown was vertically divided during tree segmentation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.329-336
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• 2010

This study deals with the measurement of reflectivity as well as the distance accuracy with Terrestrial Laser Scanner(TLS) using time of flight methods and near infrared wave length, for a variety of user-made targets. Especially, point clouds' reflection to several targets was measured with Gretag Macbeth il spectrophotometer in the office. And the distance accuracy in comparison to reference distance for TLS performance evaluation, was tested after scanning the user-made targets and measuring the inter-pillars distances over the precise EDM calibration baseline. The results of test was shown that except white resin objects, with approx. 10m and 170m inter-pillar distances, other targets achieved the distance accuracy of several millimeters(mm) with respect to standard distances. Future work should be concentrate on a few parameters influencing on the distance accuracy such as atmospheric correction, instrument correction, the additive constant or zero/index correction, etc.

• The Journal of Engineering Geology
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• v.25 no.2
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• pp.227-235
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• 2015

In recent years, owing to the frequent occurrence of natural disasters, the inspection and maintenance of structures have become increasingly important on a national scale. However, because most structural inspections are carried out manually, and due to the lack of objectivity in data acquisition, quantitative data are not always available. As a result, researchers are seeking ways to collect and standardize survey data using terrestrial laser scanning, thereby bypassing the limitations associated with visual investigations. However, field data acquired using a laser scanner have been required to measure changes in structure geometry resulting from passive deterioration. In this study, we demonstrate that it is possible to identify the processes of structural deterioration (e.g., efflorescence, leakage, delamination) using intensity data from terrestrial laser scanning. Additionally, we confirm the viability of automated classification of alteration type and objectification of the polygon area by establishing intensity characteristics. Finally, we show that our method is effective for structural inspection and maintenance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.571-581
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• 2020

Vegetation affects water level change and flow resistance in rivers and impacts waterway ecosystems as a whole. Therefore, it is important to have accurate information about the species, shape, and size of any river vegetation. However, it is not easy to collect full vegetation data on-site, so recent studies have attempted to obtain large amounts of vegetation data using terrestrial laser scanning (TLS). Also, due to the complex shape of vegetation, it is not easy to obtain accurate information about the canopy area, and there are limitations due to a complex range of variables. Therefore, the physical structure of vegetation was analyzed in this study by reconfiguring high-resolution point cloud data collected through 3-dimensional terrestrial laser scanning (3D TLS) in a voxel. Each physical structure was analyzed under three different conditions: a simple vegetation formation without leaves, a complete formation with leaves, and a patch-scale vegetation formation. In the raw data, the outlier and unnecessary data were filtered and removed by Statistical Outlier Removal (SOR), resulting in 17%, 26%, and 25% of data being removed, respectively. Also, vegetation volume by voxel size was reconfigured from post-processed point clouds and compared with vegetation volume; the analysis showed that the margin of error was 8%, 25%, and 63% for each condition, respectively. The larger the size of the target sample, the larger the error. The vegetation surface looked visually similar when resizing the voxel; however, the volume of the entire vegetation was susceptible to error.

• 전자공학회논문지 IE
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• v.46 no.1
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• pp.7-15
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• 2009

In this paper, automatic structure boundary extraction is proposed using terrestrial LIDAR (Light Detection And Ranging) in 3-dimensional data. This paper describes an algorithm which does not use pictures and pre-processing. In this algorithm, an efficient decimation method is proposed, considering the size of object, the amount of LIDAR data, etc. From these decimated data, object points and non-object points are distinguished using distance information which is a major features of LIDAR. After that, large and small values are extracted using local variations, which can be candidate for boundary. Finally, a boundary line is drawn based on the boundary point candidates. In this way, the approximate boundary of the object is extracted.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.663-666
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• 2008

For a fill dam, when a long time has passed since its completion, it is very hard to judge its safety and to maintain effectively it due to limitation and restriction in data showing safety status. Conventional method based on a specific point data by surface settlement gauge is commonly used to define deformation characteristic of dam. However, point data-based deformation analysis cannot provide deformation data of the entire dam. In this study a state-of-the-art terrestrial laser scanning technology is introduced to analyze the entire deformation of dam. As a result, it is known that 3D scanning technique can also be effectively used in evaluating dam safety and then establishing adequate maintain plan.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.561-569
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• 2008

Currently, satellite image, aerial image and airborne laser scanning data are mostly used to build 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. When making 3D image models, the model is first built and textures from terrestrial photos are applied to add realistic features to the model. This study analyzed techniques to use photogrammetry and laser scanning data to create a 3D image models with topography, building and statue that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. 3D image models with spatial accuracy and photographic texture were built to be served via 3D image map services systems on the internet. The 3D image models can be used for various purposes, such as daylight and view right analysis, landscape analysis, facility management system.