• Korean Journal of Environment and Ecology
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• v.37 no.6
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• pp.418-428
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• 2023

This study was conducted to clarify the daily activity patterns overlap between hikers and mammals from 2015 to 2019 in the Baekdudaegan protected area. To investigate relationship behaviors between hikers and mammals, we set the camera traps on the ridge of the Baekdudaegan protected area. Daily activity patterns of yellow-throated marten (Martes flavigula) and Siberian chipmunk (Eutamias sibiricus) were highly overlapped with hiker total study periods. Moreover, daily activity patterns of Siberian roe deer (Caperohus pygargus) and water deer (Hydropotes inermis) were highly overlapped with hikers only in spring. In winter, daily activity patterns of wild boar (Sus scrofa) were overlapped with hikers. However, leopard cat (Prionailurus bengalensis), raccoon dog (Nyctereutes procyonoides), and Eurasian badger (Meles leucurus) did not significantly overlap with hikers during the study periods. The daily activity patterns of 8 mammals differed by species-specific behavior and temporal characteristics. Overlap of daily activity patterns between mammals and hikers were differed in each season. Differences in daily activity pattern overlap between mammals and humans may lead to differences in human impact on mammal populations. Information on the interaction between hikers and mammals on species-specific and temporal-specific behavior could be basic ecological data for management and conservation of mammal populations and their habitats.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.563-572
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• 2017

The purpose of the study is to investigate the effect of flight height, flight speed, exposure time of camera shutter and autofocusing on the visual resolution of the image in order to obtain ultra-high resolution images with a GSD less than 1cm. It is also aimed to evaluate the ease of recognition of various types of aerial targets. For this purpose, we measured the visual resolution using a 7952*5304 pixel 35mm CMOS sensor and a 55mm prime lens at 20m intervals from 20m to 120m above ground. As a result, with automatic focusing, the visual resolution is measured 1.1~1.6 times as the theoretical GSD, and without automatic focusing, 1.5~3.5 times. Next, the camera was shot at 80m above ground at a constant flight speed of 5m/s, while reducing the exposure time by 1/2 from 1/60sec to 1/2000sec. Assuming that blur is allowed within 1 pixel, the visual resolution is 1.3~1.5 times larger than the theoretical GSD when the exposure time is kept within the longest exposure time, and 1.4~3.0 times larger when it is not kept. If the aerial targets are printed on A4 paper and they are shot within 80m above ground, the encoded targets can be recognized automatically by commercial software, and various types of general targets and coded ones can be manually recognized with ease.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1515-1526
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• 2022

Image-based 3D reconstruction is to restore the shape and color of real-world objects, and image sensors mounted on mobile platforms are used for positioning and mapping purposes in indoor and outdoor environments. Due to the increase in accidents in underground space, the location accuracy problem of underground spatial information has been raised. Image-based location estimation studies have been conducted with the advantage of being able to determine the 3D location and simultaneously identify internal damage from image data acquired from the inside of pipeline-type underground facilities. In this study, we studied 3D reconstruction based on the images acquired inside the pipe-type underground facility and reference data. An unmanned mobile system equipped with a stereo camera was used to acquire data and image data within a pipe-type underground facility where reference data were placed at the entrance and exit. Using the acquired image and reference data, the pipe-type underground facility is reconstructed to a geo-referenced 3D shape. The accuracy of the 3D reconstruction result was verified by location and length. It was confirmed that the location was determined with an accuracy of 20 to 60 cm and the length was estimated with an accuracy of about 20 cm. Using the image-based 3D reconstruction method, the position and line-shape of the pipe-type underground facility will be effectively updated.