• 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 Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2337-2342
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• 2008

In this paper, we propose the novel approach to enhance the visual quality of the digital image with adaptively sharpening and removing the noise. Image enhancement is performed in two ways. The pixels in the high dynamics area are sharpened by the adaptive unsharp mask with the parameter, which is derived using the statistical information of the image. On the other hand, the proposed algorithm do not perform the sharpening process in the uniform area that may cause the undesired artifact due to noise amplification, rather it performs smoothing to suppress the noise in this area. The decision, which process will be applied at the pixel, is also controlled by the statistics of the pixel dynamics. The proposed algorithm enhances the visual quality almost automatically by sharpening and smoothing at the same time with less parameter selection.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.35-46
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• 2007

In the study digital imagery was used to examine asphalt concrete pavements. With digitally mastered-image information that was filmed with a video camera fixed on a car travelling on road at a consistent speed, a road surface management system that can gain road surface information (Crack, Rutting, IRI) was developed using an object-oriented language "Delphi". This system was designed to improve visualized effects by animations and graphs. After analyzing the accuracy of 3-D coordinates of road surfaces that were decided using multiple image orientation and bundle adjustment method, the average of standard errors turned out to be 0.0427m in the X direction, 0.0527m in the Y direction and 0.1539m in the Z direction. As a result, it was found to be good enough to be put to practical use for maps drawn on scales below 1/1000, which are currently producted and used in our country, and GIS data. According to the analysis of the accuracy in crack width on 12 spots using a digital video camera, the standard error was found to be ${\pm}0.256mm$, which is considered as high precision. In order to get information on rutting, the physically measured cross sections of 4 spots were compared with cross sections generated from digital images. Even though a maximum error turned out to be 10.88mm, its practicality is found in work efficiency.

• Journal of IKEEE
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• v.5 no.1 s.8
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• pp.75-84
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• 2001

The reliable data relating to the condition of road surface is of increasing importance to deliver the road condition to driver and road management authority. This paper describes the development of a new high-speed. automatic, road data collection system, which collects the longitudinal road data with ${\sim}30cm$ interval covering full width of the road at 100km/h speed. The system calculates the international roughness index (IRI) from the collected data and displays the IRI and road profile data on the screen. To develope the system, we implement an optical range finder, advanced distance and motion detectors, and signal processing and display modules. The measurement accuracy of the system at 70km/h operation speed shows ${\pm}0.1m/km$ in the IRI for the standard road. To confirm the performance of the developed system, we also measure the IRI of a deployed highway road and compare the results with a conventional system and human eye measurement results.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.1
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• pp.59-70
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• 2011

The purpose of this study is to present raw data to systematically and rationally manage the protected trees located in Changwon-si, Korea. This study investigated about the present condition and the information of location, individual, management, health and soil. The results are as follows. The protected trees were located in 26 spots, and species of trees were 9 taxa; Zelkova serrata, Celtis sinensis, Aphananthe aspera, Ginkgo biloba, Carpinus tschonoskii, Pinus densiflora for. multicaulis, Quercus variabilis, Pinus densiflora and Salix glandulosa. In protected tree types, shade trees were the most, and the majority of theirs were 200 years or more in age. The range of altitude was 14~173m, and the number of trees located in flat fields was the most. For location types, village and field and mountain were presented in the order and, in land use, land for building was the most. The range of height was 8.0~30.0m, 0.6~5.1m in crown height, 240~700cm in diameter of breast and 210~800cm in diameter of root. In case of crown area, Zelkova serrata of No.5 was most large. The status boards were mostly installed except No.23 and No.26. The sites with fence were 9 spots, and the site with stonework were 14 spots. The sites with the support beam were 5 spots, and most sites were not covered up with soil. The materials of bottom were soil, gravel and vegetation in the order. The range of withering branch rate was 0~40%, and peeled bark rate was 0~60%. The sites made holes were 23 spots, and the hole size of Aphananthe aspera of No.12 was the largest. The sites disturbed by human trampling were 7 spots, the sites by disease and insects of 2 spots, the sites by injury of 23 spots and the sites by exposed roots of 13 spots. In the results of soil analysis, there showed that acidity was pH 4.5~8.0, organic matter content of 3.5~69.8g/kg, electrical conductivity(EC) of 0.11~2.87dS/m, available $P_2O_5$ of 3.0~490.6mg/kg, exchangeable K of 0.10~1.05cmol+/kg, exchangeable Ca of 1.41~16.45cmol+/kg, exchangeable Mg of 0.37~1.96cmol+/kg, exchangeable Na of 0.25~2.41cmol+/kg and cation exchange capacity(C.E.C) of 8.35~26.55cmol+/kg.