• Tunnel and Underground Space
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• v.30 no.4
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• pp.417-431
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• 2020

In this study, a fundamental investigation was made on how to use LiDAR technology to determine the degree of weathering and alteration of rock mass. The purpose of the study was to identify the affecting parameters to LiDAR intensity and to quantitatively assess the relations among them through laboratory-scale experiment. A few potential affecting parameters were selected including scanning distance, incidence angle, surface roughness, surface color, mineral composition, and water saturation. In the experiment, FARO LiDAR unit was used for twelve different types of specimen. It was observed that the intensity was affected by, in the order of importance, surface color, incidence angle, scanning distance, property of rock, water condition, and surface roughness.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.547-554
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• 2010

This study intends to analyze how long the landfill site will be available by estimating maximum volume of landfill. Preestimated volume was calculated using digital maps and scheme drawings. The latest reclamation volume was measured using the state-of-the-art airborne LiDAR technology. Based on these data. landfill volume of now, carries in volume of past a few years and subsidence rate were calculated. As a result of study, the remaining capacity of this landfill site was estimated that it would be available till 2045.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.183-189
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• 2019

Researches utilizing the fourth industrial revolution technology are being conducted as a breakthrough for improving the earthworker productivity. In order to make the earthwork site smarter, it is necessary to digitize the construction site topography at first. For this purpose, photogrammetry using drones and LiDAR on MMS have been recently used. The purpose of this study is to analyze the accuracy of LiDAR by installation angles for verifying the application of MMS in the construction site. As a result of comparing the coordinates measured by the total station and the LiDAR, a small error of about 1-2 centimeters was shown. It is confirmed that MMS could be well applied to the earthwork site. In addition, there was no significant difference in the accuracy of the acquired coordinates according to the installation angle of the LiDAR, but the shape of the point clouds was different. The larger the installation angle, the better the shape of the site terrain is measured.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.192-197
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• 2020

Recently, the technologies related to autonomous drive has studying the goal for safe operation and prevent accidents of vehicles. There is radar and camera technologies has used to detect obstacles in these autonomous vehicle research. Now a day, the method for using LiDAR sensor has considering to detect nearby objects and accurately measure the separation distance in the autonomous navigation. It is calculates the distance by recognizing the time differences between the reflected beams and it allows precise distance measurements. But it also has the disadvantage that the recognition rate of object in the atmospheric environment can be reduced. In this paper, point cloud data by triangular functions and Line Regression model are used to implement measurement algorithm, that has improved detecting objects in real time and reduce the error of measuring separation distances based on improved reliability of raw data from LiDAR sensor. It has verified that the range of object detection errors can be improved by using the Python imaging library.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.259-268
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• 2012

This paper aims to estimate the carbon dioxide stocks in forests using airborne LiDAR data with a density of approximate 4.4 points per meter square. To achieve this goal, a processing chain consisting of bare earth Digital Terrain Model(DTM) extraction and individual tree top detection has been developed. As results of this experiment, the reliable DTM with type-II errors of 3.32% and tree positions with overall accuracy of 66.26% were extracted in the study area. The total estimated carbon dioxide stocks in the study area using extracted 3-D forests structures well suited with the traditional method by field measurements upto 7.2% error level. This results showed that LiDAR technology is highly valuable for replacing the existing forest resources inventory.

• Economic and Environmental Geology
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• v.49 no.4
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• pp.281-290
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• 2016

Coastal areas, used as human utilization areas like leisure space, medical care, ports and power plants, etc., are regions that are continuously changing and interconnected with oceans and land. Regular monitoring of coastal changes is essential at key locations with such volatility. But the survey method of terrestial LiDAR(Light Detection and Ranging) system has much time consuming and many restrictions. For effective monitoring coastal changes, KIOST(Korea Institute of Ocean Science & Technology) has constructed a shipborne mobile LiDAR system. The shipborne mobile LiDAR system, installed in a research vessel, comprised a land based LiDAR(RIEGL LMS-420i), an IMU(MAGUS Inertial+), a RTKGNSS(LEICA GS15 GS25), and a fixed platform. The shipborne mobile LiDAR system is much more effective than a land based LiDAR system in the measuring of fore shore areas without shadow zone. Because the vessel with the shipborne mobile LiDAR system is continuously moved along the shoreline, it is possible to efficiently survey a large area in a relatively short time. We conducted test measurements in the Anmok-Songjung beach around the Gangneung port. Effective monitoring of the changes using the constructed shipborne mobile LiDAR system for seriously eroded coastal areas will be able to contribute to coastal erosion management and response.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.233-244
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• 2021

This study investigated the application of terrestrial light detection and ranging (LiDAR) to inspect the defects of the vegetated levee. The accuracy of vegetation filtering techniques was compared by applying filtering techniques on photogrammetric point clouds of a vegetated levee generated by terrestrial LiDAR. Representative 10 vegetation filters such as CIVE, ExG, ExGR, ExR, MExG, NGRDI, VEG, VVI, ATIN, and ISL were applied to point cloud data of the Imjin River levee. The accuracy order of the 10 techniques based on the results was ISL, ATIN, ExR, NGRDI, ExGR, ExG, MExG, VVI, VEG, and CIVE. Color filters show certain limitations in the classification of vegetation and ground and classify grass flower image as ground. Morphological filters show a high accuracy of the classification, but they classify rocks as vegetation. Overall, morphological filters are superior to color filters; however, they take 10 times more computation time. For the improvement of the vegetation removal, combined filters of color and morphology should be studied.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.23-30
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• 2015

A shoreline mapping is essential for describing coastal areas, estimating coastal erosions and managing coastal properties. This study has planned to map the 3D shorelines with the airborne LiDAR(Light Detection and Ranging) data and the KOMPSAT-2 imagery, acquired in Uljin, Korea. Following to the study, the DSM(Digital Surface Model) is generated firstly with the given LiDAR data, while the NDWI(Normalized Difference Water Index) imagery is generated by the given KOMPSAT-2 imagery. The classification method is employed to generate water and land clusters from the NDWI imagery, as the 2D shorelines are selected from the boundaries between the two clusters. Lastly, the 3D shorelines are constructed by adding the elevation information obtained from the DSM into the generated 2D shorelines. As a result, the constructed 3D shorelines have had 0.90m horizontal accuracy and 0.10m vertical accuracy. This statistical results could be concluded in that the generated 3D shorelines shows the relatively high accuracy on classified water and land surfaces, but relatively low accuracies on unclassified water and land surfaces.

• Spatial Information Research
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• v.20 no.1
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• pp.27-38
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• 2012

The recent development of CFD techniques are being involved w ith Environmental Impact Assessment and Environmental DesignroThey are being applied to the Site Planning and Engineering Design works as a new trendroHowever, CFD laboratory works are not extended to the field works in Industrial Project due to inaccuracy of the data input process that is cause by absence of regional height informationsroHence, in this study, we promote to build a new initial input data processing steps and algorithms for CFD Model generation. ENVI-met model is very popular, efficient, and freely downloadable CFD model. Light Detection And Ranging (LiDAR) are well known state of art technology and dataset proving a reliable accuracy for CFD. We use LiDAR data as a input source for CFD input producing process and algorithm development and evaluation. CFD initial input data generation process and results derived from am development and set is very useful and efficient for rapid CFD input data producing and maklomore reliable CFD Model forec st for atmospheric and climatic analysis for planning and design engineering industry.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.3-9
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• 2007

Recently, the efforts of systematic understanding and utilization of geographic phenomenon for human life as a important factor among activity of mankind are increasing. It is necessary to express topography connected with space. Especially, the technology of geographic analysis using DEM can supply the information rapidly and accurately about elevation and terrain slope of the subject area under the necessity of high 3D quality geographic information. In this study, creating more precise DEM derived from LiDAR data, quantitative analysis on the subject area about elevation and terrain slope is done under comparison with Digital Topographic map Scale 1:1000. LiDAR data is more detailed than Digital Topographic map to express the elevation of the subject area ($39.89{\sim}77.48m$), and terrain slope by analysis using DEM derived from LiDAR data come out minutely about 90%. It can be concluded that the LiDAR data is very applicable and accurate for 3D topographic terrain slope analysis.