• Spatial Information Research
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• v.16 no.3
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• pp.279-290
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• 2008

Landslide, one of the serious natural disasters, has Incurred a large loss of human and material resources. Recently, many forecasting or alarm systems based on various kinds of measuring equipment have been developed to reduce the damage of landslide. However, only a few of these equipments are guaranteed to evaluate the safety of whole side of land slope with their accessibility to the slope. In this study, we performed some experiments to evaluate the applicability of a terrestrial LiDAR as a surveying tool to measure the displacement of a land slope surface far a slope collapsing protection system. In the experiments, we had applied a slope stability method to a land slope and then forced to this slope with a load increasing step by step. In each step, we measured the slope surface with both a total station and a terrestrial LiDAR simultaneously. As the result of Slope Fracturing analysis using all targets, the LiDAR system showed that three was 1cm RMSE on X-axis, irregularity errors on Y-axis and few errors on Z-axis compare with Total Station. As the result of Slope Fracturing analysis using continuous targets, the pattern of Slope Fracturing was different according to the location of continuous targets and we could detect a continuous change which couldn't be found using Total station. The accuracy of the LiDAR data was evaluated to be comparable to that of the total station data. We found that a LiDAR system was appropriate to measuring the behaviour of land slope. The LiDAR data can cover the whole surface of the land slope, whereas the total station data are available on a small number of targets. Moreover, we extracted more detail information about the behavior of land slope such as the volume and profile changes using the LiDAR data.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.111-124
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• 2021

Recently, Interest in the restoration and 3D reconstruction of cultural properties due to the fire of Notre Dame Cathedral on April 15, 2019 has been focused once again after the 2008 Sungnyemun fire incident in South Korea. In particular, research to restore and reconstruct the actual measurement of cultural properties using LiDAR(Light Detection and ranging) and conventional surveying, which were previously used, using various 3D reconstruction technologies, is being actively conducted. This study acquires data using unmanned aerial imagery of UAV(Unmanned Aerial Vehicle), which has recently established itself as a core technology in the era of the 4th industrial revolution, and the existing CRP(Closed Range Photogrammetry) and terrestrial LiDAR scanning for the Recumbent Buddha of Unju Temple. Then, the 3D reconstruction was performed with three fusion models based on SfM(Structure-from-Motion), and the reproducibility and accuracy of the models were compared and analyzed. In addition, using the best fusion model among the three models, the relationship with the Polar Star(Polaris) was confirmed based on the real world coordinates of the Recumbent Buddha, which contains the astronomical history of Buddhism in the early 11th century Goryeo Dynasty. Through this study, not only the simple external 3D reconstruction of cultural properties, but also the method of reconstructing the historical evidence according to the type and shape of the cultural properties was sought by confirming the historical evidence of the cultural properties in terms of spatial information.

• Journal of the Korea Organic Resources Recycling Association
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• v.32 no.1
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• pp.39-47
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• 2024

In this study, LiDAR-detective black material is synthesized by recycling silicon sludge (SS) that is generated from semiconductor manufacturing process, and its recognition is confirmed using two types of LiDAR sensors (MEMS and Rotating LiDAR). In detail, metal impurities on the surface of SS is removed, followed by coating of titanium dioxide (TiO₂) and subsequent chemical reduction to obtain SS-derived black TiO₂ (SS/bTiO₂) material. As-prepared SS/bTiO₂ is mixed with transparent paint to prepare hydrophilic black paints and applied to a glass substrate using a spray gun. SS/bTiO₂-based paint shows similar blackness (L^*=15.7) compared to commercial carbon black-based paint, and remarkable NIR reflectance (26.5R%, 905nm). Furthermore, MEMS and Rotating LiDAR have successfully detected the SS/bTiO₂-based paint. This is attributed to the occurrence of high reflection of light at the interface between the black TiO₂ and the silicon sludge according to the Fresnel's reflection principle. Hence, the new application field to effectively recycle silicon sludge generated in the semiconductor manufacturing process has been presented.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.179-186
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• 2010

In this research, an effective method for absolute positioning of feature points is proposed, which is applicable to geo-referencing of terrestrial LiDAR data scanned in dense urban areas. GPS positioning, common in absolute positioning, is apt to fail in the presence of signal disturbancein dense urban circumstances, while traditional surveying methods, including traversing and leveling, are generally more costly for wider areas. The idea is that reference points, marked on top of buildings, are surveyed by GPS positioning and then feature points are relatively positioned from the reference points. The present method, if laser scanning is accompanied, gets two advantages; one is that less feature points need to be surveyed because they can be substituredby reference points, and the other is that laser scanning can be more stably carried out. The present method was shown, from the experiments, to be cost-effective against traditional ones.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.79-86
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• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.41-50
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• 2008

Recent progress in state-of-the-art geospatial information technologies such as digital mapping, LiDAR(Light Detection And Ranging), and high-resolution satellite imagery provides various data sources fer Digital Elevation Model(DEM). DEMs are major source to extract elements of the hydrological terrain property that are necessary for efficient watershed management. Especially, watersheds extracted from DEM are important geospatial database to identify physical boundaries that are utilized in water resource management plan including water environmental survey, pollutant investigation, polluted/wasteload/pollution load allocation estimation, and water quality modeling. Most of the previous studies related with watershed extraction using DEM are mainly focused on the hydrological elements analysis and preprocessing without considering grid size of the DEMs. This study aims to analyze accuracy of the watersheds extracted from DEMs with various grid sizes generated by LiDAR data and digital map, and appropriate preprocessing methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.1-14
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• 2019

In rural areas, composting is a source of non-point pollutants. However, as the quantitative distribution and loading have not been estimated, it is difficult to determine the effect of composting on stream water quality. In this study, composting datum acquired by unmanned aerial vehicle(UAV) was verified by using terrestrial LiDAR, and the management status and load change of the composting was investigated by UAV with manual control flight, thereby obtaining the basic data to determine the effect on the water system. As a result of the comparative accuracy assessment based on terrestrial LiDAR, the difference in the digital surface model(DSM) was within 0.21m and the accuracy of the volume was 93.24%. We expect that the accuracy is sufficient to calculate and utilize the composting load acquired by UAV. Thus, the management status of composting can be investigated by UAV. As the total load change of composting were determined to be $1,172.16m^3$, $1,461.66m^3$, and $1,350.53m^3$, respectively, the load change of composting could be confirmed. We expect that the results of this study can contribute to efficient management of non-point source pollution by UAV.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.36-43
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• 2021

In this research, the accuracy of YOLO v3 algorithm in object detection during AGV (Automated Guided Vehicle) operation was investigated. First of all, AGV with 2D LiDAR and stereo camera was prepared. AGV was driven along the route scanned with SLAM (Simultaneous Localization and Mapping) using 2D LiDAR while front objects were detected through stereo camera. In order to evaluate the accuracy of YOLO v3 algorithm, recall, AP (Average Precision), and mAP (mean Average Precision) of the algorithm were measured with a degree of machine learning. Experimental results show that mAP, precision, and recall are improved by 10%, 6.8%, and 16.4%, respectively, when YOLO v3 is fitted with 4000 training dataset and 500 testing dataset which were collected through online search and is trained additionally with 1200 dataset collected from the stereo camera on AGV.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.27-37
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• 2023

Assessing landcreep requires long-term monitoring, because cracks and steps develop over long periods. However, long-term monitoring using wire extensometers and inclinometers is inefficient in terms of cost and management. Therefore, this study selected an area with active landcreep and evaluated the feasibility of monitoring it using imagesing from terrestrial LiDAR and drones. The results were compared with minute-by-minute data measured in the field using a wire extensometer. The comparison identified subtle differences in the accuracy of the two sets of results, but monitoring using terrestrial LiDAR and drones did generate values similar to the wire extensometer. This demonstrates the potential of basic monitoring using terrestrial LiDAR and drones, although minute-byminute field measurements are required for analyzing and predicting landcreep. In the future, precise monitoring using images will be feasible after verifying image analysis at various levels and accumulating data considering climate and accuracy.