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- 저자 : Eontaek Lim (검색결과 4 건)
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화학물질사고 피해영역 산출을 위한 드론맵핑 기반의 정규식생지수 활용방안 연구
임언택,정용한,김성삼,Lim, Eontaek,Jung, Yonghan,Kim, Seongsam 대한원격탐사학회 2022 大韓遠隔探査學會誌 Vol.38 No.6
The annual increase in chemical accidents is causing damage to life and the environment due to the spread and residual of substances. Environmental damage investigation is more difficult to determine the geographical scope and timing than human damage investigation. Considering the reality that there is a lack of professional investigation personnel, it is urgent to develop an efficient quantitative evaluation method. In order to improve this situation, this paper conducted a chemical accidents investigation using unmanned aerial vehicles(UAV) equipped with various sensors. The damaged area was calculated by Ortho-image and strength of agreement was calculated using the normalized difference vegetation index image. As a result, the Cohen's Kappa coefficient was 0.649 (threshold 0.7). However, there is a limitation in that analysis has been performed based on the pixel of the normalized difference vegetation index. Therefore, there is a need for a chemical accident investigation plan that overcomes the limitations.
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드론센싱자료와 식생지수를 활용한 환경피해범위 산출 정확도 평가
임언택,정용한,김성삼,Eontaek Lim,Yonghan Jung,Seongsam Kim 대한원격탐사학회 2023 大韓遠隔探査學會誌 Vol.39 No.5
In this study, we explored a method for assessing the extent of damage caused by chemical substances at an accident site through the use of a vegetation index. Data collection involved the deployment of two different drone types, and the damaged area was determined using photogrammetry technology from the 3D point cloud data. To create a vegetation index image, we utilized spectral band data from a multi-spectral sensor to generate an orthoimage. Subsequently, we conducted statistical analyses of the accident site with respect to the damaged area using a predefined threshold value. The Kappa values for the vegetation index, based on the near-infrared band and the green band, were found to be 0.79 and 0.76, respectively. These results suggest that the vegetation index-based approach for analyzing damage areas can be effectively applied in investigations of chemical accidents.
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정용한,임언택,석재욱,구슬,김성삼,Yonghan Jung,Eontaek Lim,Jaewook Suk,Seul Koo,Seongsam Kim 대한원격탐사학회 2023 大韓遠隔探査學會誌 Vol.39 No.5
Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.
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조사로봇의 재난현장 활용을 위한 다중센서모듈 개발 및 성능평가에 관한 연구
정용한,홍준우,한수희,신동윤,임언택,김성삼,Jung, Yonghan,Hong, Junwooh,Han, Soohee,Shin, Dongyoon,Lim, Eontaek,Kim, Seongsam 대한원격탐사학회 2022 大韓遠隔探査學會誌 Vol.38 No.6
Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.
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