• Title/Summary/Keyword: Drone Survey

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Introduction of River Space Survey and Output Data using Drone (드론을 활용한 하천공간조사 및 산출물 소개)

  • Kim, Tae-Jeong;Kim, Chang-Sung;Kim, Sung-Hoon;Lee, Sung-Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.229-229
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    • 2020
  • 최근 광학이미지 및 레이저를 활용한 계측 기술이 발전됨에 따라서 수공학 분야의 지리정보시스템(Geographic Information System, GIS) 및 원격탐사(Remote Sensing, RS) 기술의 활용 분야가 증가하고 있다. 광범위한 하천공간의 조사결과를 가시화하고 품질 및 활용성 제고를 위하여 GIS 및 RS 기술과 같은 고도화된 조사기술 및 장비의 도입하고 많이 활용하고 있다. 우리나라의 하천은 지형학적 특성으로 하천연장이 길고 접근성이 매우 불리하다. 하천정비 사업을 통하여 하천에 근접하게 접근할 수 있는 조건이 있다 하더라도 교목이나 지형지물에 의하여 시야 확보가 어려운 조사구간이 많다. 하천공간조사를 위한 드론 활용의 장점은 차량 및 도보로 접근이 어려운 조사대상에 접근하여 다양한 각도로 촬영하여 조사 목적에 부합하는 성과물 획득이 가능하다. 한국수자원조사기술원은 하도특성(평면, 사행 및 종횡단 조사)을 사전에 하천기본계획 보고서에서 곡률반경과 만곡도, 유심편향축, 최심하상경사 및 평균하상경사 등을 수집하고 현장에서 드론을 활용하여 접근조사가 어려운 항목에 대하여 드론을 적극적으로 활용하여 조사하고 있다. 드론을 활용할 경우 인력 및 소요시간이 대폭 절감되며 조사목적에 부합하는 다양한 조사 성과물을 얻을 수 있은 장점이 있다. 최종적으로 촬영된 영상자료는 넓은 범위의 하천공간을 고해상도 수치 지도화가 가능해 하천특성을 정량적으로 평가할 수 있을 것으로 판단된다.

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A Study on R&D Strategies of Personal Air Vehicle based on Demand Factors (수요요인을 반영한 개인용 항공기 개발전략 연구)

  • Byun, Sangkyu;Kang, Beom-Soo
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.29 no.3
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    • pp.15-23
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    • 2021
  • Personal Air Vehicle is expected to be a promising solution to relieve traffic congestion using urban airspace. The development of related technologies such as materials or batteries has been accelerated. In addition, commercial transportation services are being prepared. When fierce competition begins in the PAV market, even technologically superior products will disappear without choices by consumers. Therefore, demand factors should be reflected in PAV development to enhance competitiveness. In the paper, values were estimated for the major technological attributes of PAV. Stated preference data were collected through a survey, and the conjoint method and ordered probit model were adopted. Thereafter, it was confirmed that the value would be high in the order of dual mode, drone-type appearance, and noise reduction. Some R&D strategies were proposed based on this.

Survey on Identification and Authentication Technology Using the Unique Characteristics of Drone Hardware (드론 하드웨어 고유특성을 이용한 식별 및 인증 기술 연구 동향)

  • Jung-Hun Kang;Seung-Hyun Seo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.203-205
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    • 2023
  • 최근 성장하고 있는 드론 산업에 맞추어 전세계적으로 드론 운용을 위한 식별 및 인증 규정을 마련하고 있는 추세이다. 대표적으로, 미국 FAA 에서 채택한 Remote ID 기반의 식별방식이 있다. 그러나, ID 기반의 인증 방식은 해당 ID 가 탈취 혹은 위조될 경우 다른 드론으로 위장하여 여러 심각한 사회 문제를 일으킬 위험성이 있다. 따라서 드론에 탑재된 여러 센서나 모터와 같은 하드웨어의 고유한 특성을 이용하여 Remote ID 를 대체하거나 이중 인증에 이용하려는 연구가 이루어지고 있다. 본 논문에서는 드론에 탑재된 하드웨어의 고유특성을 이용한 다양한 식별 및 인증시스템에 대한 연구에 대하여 살펴본다.

A Survey on Hardware Characteristic-based Drone Identification and Authentication Technology (하드웨어적 고유 특성 기반 드론 식별 및 인증 기술 연구 동향 분석)

  • Sungbin Park;Hoon Ji;Yeonjoon Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.1181-1184
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    • 2023
  • 최근 드론은 군사 작전, 물류 운송, 인명 구조 등 다양한 분야에서 활용되고 있으며 관련 산업의 규모는 증가하는 추세이다. 이에 따라, GPS 스푸핑, 조종사 비익명화 등의 드론을 향한 공격 기법들 또한 발달하고 있다. 이런 공격들은 드론에 대한 인증을 도입함으로써 대비할 수 있는 공격들이다. 이에, 학계에서는 강건한 인증을 위해 드론 하드웨어의 고유 특성을 활용할 수 있는 RF 신호, 소리 신호, 드론 내부 센서 신호 등에 기반한 인증 기술들이 연구되어온 바 있다. 본 논문에서는 지금까지의 드론 인증 기술 연구 동향을 분석하고, 이를 기반으로 향후 연구 방향을 제시한다.

Estimating the Stand Level Vegetation Structure Map Using Drone Optical Imageries and LiDAR Data based on an Artificial Neural Networks (ANNs) (인공신경망 기반 드론 광학영상 및 LiDAR 자료를 활용한 임분단위 식생층위구조 추정)

  • Cha, Sungeun;Jo, Hyun-Woo;Lim, Chul-Hee;Song, Cholho;Lee, Sle-Gee;Kim, Jiwon;Park, Chiyoung;Jeon, Seong-Woo;Lee, Woo-Kyun
    • Korean Journal of Remote Sensing
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    • v.36 no.5_1
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    • pp.653-666
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    • 2020
  • Understanding the vegetation structure is important to manage forest resources for sustainable forest development. With the recent development of technology, it is possible to apply new technologies such as drones and deep learning to forests and use it to estimate the vegetation structure. In this study, the vegetation structure of Gongju, Samchuk, and Seoguipo area was identified by fusion of drone-optical images and LiDAR data using Artificial Neural Networks(ANNs) with the accuracy of 92.62% (Kappa value: 0.59), 91.57% (Kappa value: 0.53), and 86.00% (Kappa value: 0.63), respectively. The vegetation structure analysis technology using deep learning is expected to increase the performance of the model as the amount of information in the optical and LiDAR increases. In the future, if the model is developed with a high-complexity that can reflect various characteristics of vegetation and sufficient sampling, it would be a material that can be used as a reference data to Korea's policies and regulations by constructing a country-level vegetation structure map.

Development of Deep Learning Model for Detecting Road Cracks Based on Drone Image Data (드론 촬영 이미지 데이터를 기반으로 한 도로 균열 탐지 딥러닝 모델 개발)

  • Young-Ju Kwon;Sung-ho Mun
    • Land and Housing Review
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    • v.14 no.2
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    • pp.125-135
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    • 2023
  • Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

Evaluation for applicability of river depth measurement method depending on vegetation effect using drone-based spatial-temporal hyperspectral image (드론기반 시공간 초분광영상을 활용한 식생유무에 따른 하천 수심산정 기법 적용성 검토)

  • Gwon, Yeonghwa;Kim, Dongsu;You, Hojun
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.235-243
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    • 2023
  • Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

A Study on the Shapes of Twin Curvy Sail for Unmanned Sail Drone (무인세일드론의 트윈커브세일 형상에 관한 연구)

  • Ryu, In-Ho;Kim, Bu-Gi;Yang, Changjo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.7
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    • pp.1059-1066
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    • 2021
  • In Korea, the importance of marine activities is great, and automatic weather observation facilities are operating on land to investigate abnormal weather phenomena caused by industrialization; however, the number of facilities at sea is insufficient. Marine survey ships are operated to establish marine safety information, but there are many places where marine survey ships are difficult to access and operating costs are high. Therefore, a small, unmanned vessel capable of marine surveys must be developed. The sail has a significant impact on the sailing performance, so much research has been conducted. In this study, the camber effect, which is a design variable of the twin curvy sail known to have higher aerodynamic performance than existing airfoil shapes, was investigated. Flow analysis results for five cases with different camber sizes show that the lift coefficient is highest when the camber size is 9%. Curvy twin sails had the highest lift coefficient at an angle of attack of 23° because of the interaction of the port and starboard sails. The port sail had the highest lift coef icient at an angle of attack of 20°, and the starboard sail had the lowest lift coef icient at an angle of attack of 15°. In addition, the curvy twin sail had a higher lift coefficient than NACA 0018 at all angles of attack.

A Study on Precision of 3D Spatial Model of a Highly Dense Urban Area based on Drone Images (드론영상 기반 고밀 도심지의 3차원 공간모형의 정밀도에 관한 연구)

  • Choi, Yeon Woo;Yoon, Hye Won;Choo, Mi Jin;Yoon, Dong Keun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.2
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    • pp.69-77
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    • 2022
  • The 3D spatial model is an analysis framework for solving urban problems and is used in various fields such as urban planning, environment, land and housing management, and disaster simulation. The utilization of drones that can capture 3D images in a short time at a low cost is increasing for the construction of 3D spatial model. In terms of building a virtual city and utilizing simulation modules, high location accuracy of aerial survey and precision of 3D spatial model function as important factors, so a method to increase the accuracy has been proposed. This study analyzed location accuracy of aerial survey and precision of 3D spatial model by each condition of aerial survey for urban areas where buildings are densely located. We selected Daerim 2-dong, Yeongdeungpo-gu, Seoul as a target area and applied shooting angle, shooting altitude, and overlap rate as conditions for the aerial survey. In this study, we calculated the location accuracy of aerial survey by analyzing the difference between an actual survey value of CPs and a predicted value of 3D spatial Model. Also, We calculated the precision of 3D spatial Model by analyzing the difference between the position of Point cloud and the 3D spatial Model (3D Mesh). As a result of this study, the location accuracy tended to be high at a relatively high rate of overlap, but the higher the rate of overlap, the lower the precision of 3D spatial model and the higher the shooting angle, the higher precision. Also, there was no significant relationship with precision. In terms of baseline-height ratio, the precision tended to be improved as the baseline-height ratio increased.

Analysis of Seabottom and Habitat Environment Characteristics based on Detailed Bathymetry in the Northern Shore of the East Sea(Gyeongpo Beach, Gangneung) (정밀 해저지형 자료 기반 동해 북부 연안(강릉 경포) 서식지 해저면 환경 특성 연구)

  • Lee, Myoung Hoon;Rho, Hyun Soo;Lee, Hee Gab;Park, Chan Hong;Kim, Chang Hwan
    • Economic and Environmental Geology
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    • v.53 no.6
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    • pp.729-742
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    • 2020
  • In this study, we analyze seabottom conditions and characteristics integrated with topographic data, seafloor mosaic, underwater images and orthophoto(drone) of soft-hard bottom area around the Sib-Ri rock in the northern shore of the East Sea(Gyeongpo Beach, Gangneung). We obtained field survey data around the Sib-Ri rock(about 600 m × 600 m). The Sib-Ri rock is formed by two exposed rocks and surrounding reef. The artificial reef zone made by about 200 ~ 300 structures is shown the western area of the Sib-Ri rock. The underwater rock region is extended from the southwestern area of the exposed the Sib-Ri rock with 9 ~ 11 m depth range. The most broad rocky seabottom area is located in the southwestren area of the Sib-Ri rock with 10 ~ 13 m depth range. The study area were classified into 4 types of seabottom environment based on the analysis of bathymetric data, seafloor mosaics, composition of sediments and images(underwater and drone). The underwater rock zones(Type I) are the most distributed area around the Sib-Ri Rock(about 600 m × 600 m). The soft seabottom area made by sediments layer showed 2 types(Type II: gS(gravelly Sand), Type III: S(Sand)) in the areas between underwater rock zones and western part of the Sib-Ri rock(toward Gyeongpo Beach). The artificial reef zone with a lot of structures is located in the western part of the Sib-Ri rock. Marine algae(about 6 species), Phylum porifera(about 2 species), Phylum echinodermata(about 3 species), Phylum mollusca(about 3 species) and Phylum chordata(about 2 species) are dominant faunal group of underwater image analysis area(about 10 m × 10 m) in the northwestern part of the Sib-Ri rock. The habitat of Phylym mollusca(Lottia dorsuosa, Septifer virgatus) and Phylum arthropoda(Pollicipes mitella, Chthamalus challengeri hoek) appears in the intertidal zone of the Sib-Ri rock. And it is possible to estimate the range and distribution of the habitat based on the integrated study of orthphoto(drone) and bathymetry data. The integrated visualization and mapping techniques using seafloor mosaic images, sediments analysis, underwater images, orthophoto(drone) and topographic data can provide and contribute to figure out the seabottom conditions and characteristics in the shore of the East Sea.