• Journal of Korean Society of Forest Science
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• v.78 no.1
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• pp.30-34
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• 1989

Effects on noise attenuation of the hedge species, Thuja orientalis L. and Euonymus japonicus Thunb., widely used as road side hedges, were analysed at the frequencies of 1,000, 2,000 and 3,150 Hz., respectively. The present experiments were carried out both in the field and in a Semianechoic Chamber. As increasing the distances from the noise source, attenuation rates of noise level were increased at high frequencies. But the attenuation rates of the noise level at low frequencies showed varied as the distances increased, and this trend appeared to be caused by the influence of ground waves. Generally, in this experiment, Thuja orientalis L., which is a coniferous species, showed more effective on the abilities of noise attenuation than that of Euonymus japonicus Thunb., which is a broad-leaved evergreen species.

• Journal of Korea Water Resources Association
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• v.40 no.7
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• pp.571-583
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• 2007

The effects of climatic changes owing to urbanization, geographical and topographical conditions on Penman-Monteith reference evapotranspiration, and energy and aerodynamic terms of Penman-Monteith reference evapotranspiration have been studied. In this study, 56 climatological stations including the Seoul metropolis in South Korea have been selected, and the area of study site was set at $314\;km^2$. The climatological station is centrally located In the study area with a 10 km radius. The geographical and topographical characteristics of these sites were examined using GIS analysis. Land use status of the study area was also examined to estimate the extent of urbanization. The study results indicated that the variation of reference evapotranspiration rate is closely related to urbanization in most climatological stations. The level of change in reference evapotranspiration was higher in areas with higher urbanization rates. The change in reference evapotranspiration appears to be caused by temperature rises following heat island phenomena due to urbanization, and by the decrease in humidity, wind speed and sunshine duration due to the Increase in residential areas in urban districts. Especially, the humidity decrease causes a significant decrease in evapotranspiration rate. The study results showed that climatic change due to urbanization and proximity to the coast had the greatest effect on reference evapotranspiration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.296-301
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• 2021

GPR is used for non-destructive investigations, ground investigations, and underground facilities exploration at construction sites. In this study, the applicability to GPR exploration of water pipes linked to Network RTK was presented. Data on the water supply pipes in the study site were acquired using GPR, and the location and depth of buried water pipes could be measured. The accuracy was evaluated from the GNSS observation performance and showed a deviation of -0.16m ~ 0.15m. This satisfied the equipment performance of the public survey work regulation, suggesting that the exploration of water pipes using GPR is possible. Because GPR does not require grounding installation, as in conventional metal pipe detectors, it will increase the efficiency of work for underground facility exploration. Exploration using GPR can acquire the location and depth of metallic and non-metallic underground facilities, so it can be utilized in the construction of a GIS system. If a comparison of the exploration characteristics is carried out, it will be possible to present various uses of underground facility exploration using GPR.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.427-433
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• 2022

Obstacle detection, collision recognition, and avoidance technologies are required the collision avoidance technology for UAVs. In this paper, considering collinear multiple static obstacle, we propose an obstacle detection algorithm using LiDAR and a collision recognition and avoidance algorithm based on CPA. Preprocessing is performed to remove the ground from the LiDAR measurement data before obstacle detection. And we detect and classify obstacles in the preprocessed data using the K-means clustering algorithm. Also, we estimate the absolute positions of detected obstacles using relative navigation and correct the estimated positions using a low-pass filter. For collision avoidance with the detected multiple static obstacle, we use a collision recognition and avoidance algorithm based on CPA. Information of obstacles to be avoided is updated using distance between each obstacle, and collision recognition and avoidance are performed through the updated obstacles information. Finally, through obstacle location estimation, collision recognition, and collision avoidance result analysis in the Gazebo simulation environment, we verified that collision avoidance is performed successfully.