• International Journal of Contents
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• v.5 no.3
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• pp.19-23
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• 2009

Laser scanning technology is a maturing measurement technology which is capable of obtaining 3D measurement data of objects with high-accuracy, high-resolution and in a short time. Laser scanners are used more and more as surveying instruments for various applications. This paper describes the procedure of 3D data acquirement using terrestrial LiDAR and section drawing extraction through a series of processing for remodeling the interior of a department building. Accurate drawings are needed for improvement construction of building interior. However if the design drawings of that time of construction work were lost or damaged or actual dimensions of drawings differ from those of design drawings, the interior should be resurveyed. In this study, the extraction process of interior plane figures were suggested through using laser scanning and related reverse engineering software

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2009.04a
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• pp.115-117
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• 2009

Terrestrial Laser Scanner and Airborne Laser Scanning is one of the state of art surveying equipments. So This study deals with the combined use of mobile TLS(Terrestrial Laser Scanner) with ALS(Airborne Laser Scanning) to extract shoreline's topography information. These two systems have their own pros and cons. Mobile TLS can capture the facades of a low story building along the shoreline fast and quickly. Meanwhile, Due to viewpoint restrictions of ALS data collection, the amount of detail, which is available for the building facades is very limited. Therefore, it is recommended that the co-registration and geo-referencing methods of both two should be developed and the application of both system for shoreline mapping also should be investigated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.4
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• pp.505-513
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• 2009

Recently, researches on the construction information for construction of high-tech cities are under performed. RTLS(Real-Time location system) for gathering the dynamic location information of construction resources in construction sites, such as workers, materials and equipments, is one of the developments. Especially, construction resources can be managed efficiently with the dynamic location information and the improvement of safety and the reduction of cost are expected. To introduce the RTLS to the construction sites, the installation location of AP(Access Point) must be simulated using the 3-dimensional visibility analysis considering the propagation distance of AP. In this research, 3-dimensional signal simulation software based on the spatial data using surveying terrestrial LiDAR is developed. The simulated results are compared with the signal strength of field experiments for 4 test sites. As a result, the signal strength from the propagation model is most similar to that of field experiment at the front of the main building and the maul playground of Konkuk University. The visibilities in that sites are higher than other sites. among 4 test sites.

• The Journal of Engineering Geology
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• v.25 no.1
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• pp.83-91
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• 2015

Few studies have investigated soil management policy and soil erosion measurement, whereas the occurrence of climate change requires the establishment of robust soil management systems and appropriate control of soil erosion. In this study, we developed a smart sensor for real-time quantitative measurements of soil erosion at the watershed scale. The smart sensor consists of an ultrasonic sensor, a rainfall meter, a solar cell, an RTU (remote terminal unit),and a CDMA (code division multiple access) and it was programmed to take a measurement every 30 minutes. The depths measured by the smart sensor were compared with data from terrestrial LiDAR. Experimental results showed a strong correlation in the depth of soil erosion between LiDAR and the ultrasonic sensor for the period from 22 August to 11 October 2013. Furthermore, the correlation coefficient between soil erosion depth (mm) and soil erosion volume (m³) was 0.9063 in the lower region of the watershed and is 0.9868 in the upper region. The proposed ultrasonic sensor technique can provide high-quality data for soil conservation and management systems in the future.

• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.3-11
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• 2014

Recently, rapid urbanization has necessitated continuous updates in digital map to provide the latest and accurate information for users. However, conventional aerial photogrammetry has some restrictions on periodic updates of small areas due to high cost, and as-built drawing also brings some problems with maintaining quality. Alternatively, this paper proposes a scheme for efficient and accurate update of digital map using point cloud data acquired by Terrestrial Laser Scanner (TLS). Initially, from the whole point cloud data, the building sides are extracted and projected onto a 2D image to trace out the 2D building footprints. In order to register the footprint extractions on the digital map, 2D Affine model is used. For Affine parameter estimation, the centroids of each footprint groups are randomly chosen and matched by means of a modified RANSAC algorithm. Based on proposed algorithm, the experimental results showed that it is possible to renew digital map using building footprint extracted from TLS data.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.529-534
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• 2004

The increasing need and use of 3D GIS particularly in urban areas has produced growing attention on building reconstruction. Nowadays, the use of close-range data for building reconstruction has been intensively emphasized since they can provide higher resolution and more complete coverage than airborne sensory data. We developed a fusion approach for building reconstruction from both points and images. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1291-1302
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• 2020

To verify the field-effectiveness of Terrestrial Laser Scanner (TLS), a terrestrial LiDAR was deployed to examine the damage properties of woods in forest fire area, then the data was compared with the results surveyed by a forestry expert. Four sample plots (30 m × 50 m, 0.15 ha) were set from the foot to the top of the mountain, and DBH, height, clear length, burned height, and crown length were investigated. Next, TLS collected information on damage characteristics found in the sample plots. This information was then compared with that amassed by the expert. The expert and the TLS survey results showed 30.8 cm and 29.9 cm for DBH, 15.8 m and 17.5 m for tree height, 8.4 m and 8.4 m for clear length, 4.0 m, 3.5 m for burned height, and 7.4 cm and 9.1 cm for crown length. With the exceptions of height and clear length, no notable discrepancy was observed between two methods. H/D ratio, CL/H ratio, and BH/CL ratio, all of which contribute to stability and decay rate of the stand, from the two methods were also compared. The human survey rated each ratio (H/D, CL/H, BH/CL in order) 51.3%, 47.1%, and 53.6%, while the TLS presented the results of 58.8%, 52.0%, and 38.7%.

• 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.

• 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.