• Title/Summary/Keyword: Drone image

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Estimation of Paddy CH4 Emissions through Drone-Image-Based Identification of Paddy Rice Straw Application & Winter Crop Cultivation (Drone 영상을 이용한 논 필지 볏짚 환원-동계 재배 확인 및 CH4 배출량 산정)

  • Jang, Seongju;Park, Jinseok;Hong, Rokgi;Hong, Joopyo;Kwon, Chaelyn;Song, Inhong
    • Journal of Korean Society of Rural Planning
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    • v.27 no.3
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    • pp.21-33
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    • 2021
  • Rice straw management and winter crop cultivation are crucial components for the accurate estimation of paddy methane emissions. Field-based extensive investigation of paddy organic matter management requires enormous efforts however it becomes more feasible as drone technology advances. The objectives of this study were to identify paddy fields of straw application and winter crop cultivation using drone images and to apply for the estimation of yearly methane emission. Total 35 sites of over 150ha in area were selected nationwide as the study areas. Drone images of the study sites were taken twice during summer and winter in 2018 through 2019: Summer images were used to identify paddy cultivation areas, while winter images for straw and winter crop practices. Drone-image-based identification results were used to estimate paddy methane emission and compared with conventional method. As the result, mean areas for paddy, straw application and winter crop cultivation were 118.9ha, 12.0ha, and 11.3ha, respectively. Overall rice straw application rate were greater in Gyeonggi-do(20%) and Chungcheongnam-do(12%), while winter crop cultivation was greatest in Gyeongsangnam-do(30%) and Jeolla-do(27%). Yearly mean methane emission was estimated to be 226.2kg CH4/ha/yr in this study and about 32% less when compared to 331.8kg CH4/ha/yr estimated with the conventional method. This was primarily because of the lower rice straw application rate observed in this study, which was less than quarter the rate of 55.62% used for the conventional method. This indicates the necessity to use more accurate statistics of rice straw application as well as winter crop practices into paddy methane emission estimation. Thus it is recommended to further study to link drone technology with satellite image analysis in order to identify organic management practices at a paddy field level over extensive agricultural area.

Production and Accuracy Analysis of Topographic Status Map Using Drone Images (드론영상을 이용한 지형 현황도 제작 및 정확도 분석)

  • Kim, Doopyo;Back, Kisuk;Kim, Sungbo
    • Journal of the Korean GEO-environmental Society
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    • v.22 no.2
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    • pp.35-39
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    • 2021
  • Photogrammetry using drone can produce high-resolution ortho image and acquire high-accuracy 3D information, which is useful. Therefore, this study attempted to determine the possibility of using drone-photogrammetry in park construction by producing a topographic map using drone-photogrammetry and analyzing the problems and accuracy generated during production. For this purpose, we created ortho image and DSM (digital surface model) using drone images and created topographic status map by vectorizing them. Accuracy was compared based on topographic status map by GPS (global positioning system) and TS (total station). The resulting of analyzing mean of the residuals at check points showed that 0.044 m in plane and 0.066 m in elevation, satisfying the tolerance range of 1/1,000 numerical maps, and result of compared lake size showed a difference of about 4.4%. On the other hand, it was difficult to obtain accurate height values for terrain in which existed vegetation when producing the topographic map, and in the case of underground buried objects, it is not possible to confirm it in the image, so direct spatial information acquisition was necessary. Therefore, it is judged that the topographic status map using drone photogrammetry can be efficiently constructed if direct spatial data acquisition is achieved for some terrain.

Improved Image Matching Method Based on Affine Transformation Using Nadir and Oblique-Looking Drone Imagery

  • Jang, Hyo Seon;Kim, Sang Kyun;Lee, Ji Sang;Yoo, Su Hong;Hong, Seung Hwan;Kim, Mi Kyeong;Sohn, Hong Gyoo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.5
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    • pp.477-486
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    • 2020
  • Drone has been widely used for many applications ranging from amateur and leisure to professionals to get fast and accurate 3-D information of the surface of the interest. Most of commercial softwares developed for this purpose are performing automatic matching based on SIFT (Scale Invariant Feature Transform) or SURF (Speeded-Up Robust Features) using nadir-looking stereo image sets. Since, there are some situations where not only nadir and nadir-looking matching, but also nadir and oblique-looking matching is needed, the existing software for the latter case could not get good results. In this study, a matching experiment was performed to utilize images with differences in geometry. Nadir and oblique-looking images were acquired through drone for a total of 2 times. SIFT, SURF, which are feature point-based, and IMAS (Image Matching by Affine Simulation) matching techniques based on affine transformation were applied. The experiment was classified according to the identity of the geometry, and the presence or absence of a building was considered. Images with the same geometry could be matched through three matching techniques. However, for image sets with different geometry, only the IMAS method was successful with and without building areas. It was found that when performing matching for use of images with different geometry, the affine transformation-based matching technique should be applied.

Analysis of Drone Target Search Performance According to Environment Change

  • Lim, Jong-Bin;Ha, Il-Kyu
    • Journal of Korea Multimedia Society
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    • v.22 no.10
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    • pp.1178-1186
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    • 2019
  • In recent years, interest in drones has grown, and many countries are developing them into a strategic industry of the future. Drones are not only used in industries such as logistics and agriculture but also in various public sectors such as life rescue, disaster investigation, traffic control, and firefighting. One of the most important tasks of a drone is to accurately identify targets in these applications. Target recognition may vary depending on the search environment of the drone. Therefore, this study tests and analyzes the drone's target recognition performance according to changes in the search environment such as the search altitude and the search angle. In addition, we propose a new algorithm that improves upon the disadvantages of the Haar cascade method, which is the existing algorithm that recognizes the target by analyzing a captured image.

Gimbal System Control for Drone for 3D Image (입체영상 촬영을 위한 드론용 짐벌시스템 제어)

  • Kim, Min;Byun, Gi-Sig;Kim, Gwan-Hyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.11
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    • pp.2107-2112
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    • 2016
  • This paper is designed to develop a Gimbal control stabilizer for drones Gimbal system control for drone for 3D image to make sure clean image in the shaking and wavering environments of drone system. The stabilizer is made of tools which support camera modules and IMU(Inertial Measurement Unit) sensor modules follow exact angles, which can brock vibrations outside of the camera modules. It is difficult for the camera modules to get clean image, because of irregular movements and various vibrations produced by flying drones. Moreover, a general PID controller used for the movements of rolling, pitching and yawing in order to control the various vibrations of various frequencies needs often to readjust PID control parameters. Therefore, this paper aims to conduct the Intelligent-PID controller as well as design the Gimbal control stabilizer to get clean images and to improve irregular movements and various vibrations problems referenced above.

Development of Surface Velocity Measurement Technique without Reference Points Using UAV Image (드론 정사영상을 이용한 무참조점 표면유속 산정 기법 개발)

  • Lee, Jun Hyeong;Yoon, Byung Man;Kim, Seo Jun
    • Ecology and Resilient Infrastructure
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    • v.8 no.1
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    • pp.22-31
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    • 2021
  • Surface image velocimetry (SIV) is a noncontact velocimetry technique based on images. Recently, studies have been conducted on surface velocity measurements using drones to measure a wide range of velocities and discharges. However, when measuring the surface velocity using a drone, reference points must be included in the image for image correction and the calculation of the ground sample distance, which limits the flight altitude and shooting area of the drone. A technique for calculating the surface velocity that does not require reference points must be developed to maximize spatial freedom, which is the advantage of velocity measurements using drone images. In this study, a technique for calculating the surface velocity that uses only the drone position and the specifications of the drone-mounted camera, without reference points, was developed. To verify the developed surface velocity calculation technique, surface velocities were calculated at the Andong River Experiment Center and then measured with a FlowTracker. The surface velocities measured by conventional SIV using reference points and those calculated by the developed SIV method without reference points were compared. The results confirmed an average difference of approximately 4.70% from the velocity obtained by the conventional SIV and approximately 4.60% from the velocity measured by FlowTracker. The proposed technique can accurately measure the surface velocity using a drone regardless of the flight altitude, shooting area, and analysis area.

An Education Plan for Camera Drone (촬영용 드론 교육 방안)

  • Park, Sung-Dae;Han, Kun-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1206-1213
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    • 2021
  • A drone invented for the military has been increased the range of application with the development of relevant technology, and it influences to include the private area. Currently, the use of drone has been increasing in many areas, such as agriculture, unmanned parcel service, production of image contents, and architecture. In 2021, South of Korea, a drone certificate system for drone flight is introduced and on operation. In case of drone flight with the maximum takeoff weight as 2kg or up, the flight experience and practical examination are required, whereas in case of drone lighter than 2kg, the online education qualification is enough to operate it without the flight experience and practical examination. Recently, the drone related accidents have been increasing with the rapidly supply of camera drones with the maximum takeoff weight as less than 2kg. This paper introduces the characteristics of the camera drone to meet burgeoning demand, and discusses an education plan for the camera drone.

A Study on the Analysis of the Current Situation of the Target Site Using the Image of Unmanned Aircraft in the Environmental Impact Assessment

  • Ki-Sun Song;Sun-Jib Kim
    • International Journal of Advanced Culture Technology
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    • v.11 no.2
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    • pp.381-388
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    • 2023
  • Small-scale environmental impact assessments have limitations in terms of survey duration and evaluation resources, which can hinder the assessment and analysis of the current situation. In this study, we propose the use of drone technology during the environmental impact assessment process to supplement these limitations in the current situation analysis. Drone photography can provide rapid and accurate high-resolution images, allowing for the collection of various information about the target area. This information can include different types of data such as terrain, vegetation, landscape, and real-time 3D spatial information, which can be collected and processed using GIS software to understand and analyze the environmental conditions. In this study, we confirmed that terrain and vegetation analysis and prediction of the target area using drone photography and GIS analysis software is possible, providing useful information for environmental impact assessments.

Crack detection system for exterior wall in a drone camera image using YOLO deep learning technique (YOLO 딥러닝 기법을 이용한 드론카메라 영상 내 건물 외벽 균열 검출 시스템)

  • Yun, Tae-Jin;Jeon, Jin-Woo;Ko, Byung-Yoon;Woo, Hyun-Koo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.01a
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    • pp.303-304
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    • 2019
  • 본 논문에서는 자연재해나 노후화로 인해 많은 건물의 외벽에 균열(Crack)이 생기고 있고, YOLO 딥러닝 기법을 이용하여 텐서플로우(Tensorflow)기반 균열 데이터의 학습 과정을 거쳐 가중치 파일을 획득하고, 이를 기반으로 효율적으로 건물 관리를 할 수 있는 드론(Drone)에 장착된 카메라를 이용한 실시간 영상으로 건물 외벽 균열을 촬영하고 균열을 감지하여 사용자 모니터에 감지된 균열을 경계 상자를 통해 검출하고, 검출 사진과 위치를 기록하도록 시스템을 개발하였다.

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Disaster Prevention Technology in Response to Flooded Areas Using Drone Image-Based Inundation Monitoring and Prefabricated Rainwater Penetration Storage Block Structure (드론영상 기반 침수 모니터링 및 조립식 빗물 침투 저류블록 구조를 활용한 상습 침수지역 대응 방재기술)

  • Choi, Hee-Yong;Choi, Hyeong-Gil;Ryu, Jung-Rim;Kim, Won-Chang;Lee, Tae-Gyu
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2023.05a
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    • pp.411-412
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    • 2023
  • The purpose of this research and development is to develop a structure module that improves the efficiency and constructability of the layout structure as well as the design development of rainwater permeable storage tank blocks using inorganic binders and aggregates with the aim of reducing greenhouse gas (CO2) with eco-friendly materials. In addition, for the efficient response to flooding of the developed permeable storage structure, we present a technical solution for combining drone mapping technology and flood monitoring technology that can analyze topographical factors in detail.

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