• Korean Security Journal
• /
• no.53
• /
• pp.11-33
• /
• 2017

Terrorism has existed in the entire human history and has become a significant topic in criminology while prior studies has focused on North Korea as the perpetrator, and this prevents an in-depth discussion of the international trends of terrorism. As soft targets are the main target of new terrorism and because we never ignore the significance of the consequences, there are needs for more studies on the topic. This study conducted a case study of major terrorism attacks and surveyed professionals in the field via an AHP analysis in order to find the characteristics of terrorism and its potential patterns in South Korea. As a result, we found that North Korea or the left-wing may utilize homemade bomb, motor vehicle or drone for the purpose of attacking multi-use facilities in South Korea. For policy implications, we insist developing a better CPTED approach on those facilities, improving professionalism of cyber-watchdog via more training and education, stricter control on drone permit, and operation of counseling centers for preventing radicalization.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.1055-1066
• /
• 2018

Vegetation indices on the basis of optical characteristics of vegetation can represent various conditions such as canopy biomass and physiological activity. Those have been mostly developed with the large-scaled applications of multi-band optical sensors on-board satellites. However, the sensitivity of vegetation indices for detecting vegetation features will be different depending on the spatial scales. Therefore, in this study, the investigation of photochemical reflectance index (PRI), known as one of useful vegetation indices for detecting photosynthetic ability and vegetation stress, under the three spatial scales was conducted using multi-spectral camera installed in unmanned aerial vehicle (UAV),field spectrometer, and leaf reflectometer. In the leaf scale, diurnal PRI had minimum values at different local-time according to the compass direction of leaf face. It meant that each leaf in some moment had the different degree of light use efficiency (LUE). In early growth stage of crop, $PRI_{leaf}$ was higher than $PRI_{stands}$ and $PRI_{canopy}$ because the leaf scale is completely not governed by the vegetation cover fraction.In the stands and canopy scales, PRI showed a large spatial variability unlike normalized difference vegetation index (NDVI). However, the bias for the relationship between $PRI_{stands}$ and $PRI_{canopy}$ is lower than that in $NDVI_{stands}$ and $NDVI_{canopy}$. Our results will help to understand and utilize PRIs observed at different spatial scales.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.1098-1099
• /
• 2023

다중객체 분석 모델 Yolo를 기반으로 물체를 감지하기 위해서 학습을 진행하고 학습을 통해서 얻어낸 모델을 기반으로 드론을 통해서 얻어낸 영상을 통해 컨테이너 파손이 된 부분을 감지하는 프로젝트를 진행했다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2020.07a
• /
• pp.697-700
• /
• 2020

고위험의 재난 상황에서 사람이 상황을 판단하고, 요구조자를 탐색하며, 구조하는 것은 추가 피해를 발생시킬 수 있다. 따라서 재난 상황에서도 이동과 접근이 용이한 무인항공에 관한 연구와 개발이 활발히 이루어지고 있다. 재난 상황에서 신속하게 대처하기 위해서는 선제적 상황인지 기술이 필요하다. 이에 본 논문은 구조 및 대피를 위해 사람, 자동차, 자전거 등의 객체를 인식하고 중복 인식을 피하기 위해 추적하는 딥러닝 기반 다중 객체 추적 시스템을 제안한다. 2019 인공지능 R&D 그랜드 챌린지 상황인지 부문에서의 대회 결과로 실험 성능을 증명한다.

• Korean Journal of Remote Sensing
• /
• v.35 no.2
• /
• pp.203-215
• /
• 2019

As hyperspectral sensors that can be mounted on drones are developed, it is possible to acquire hyperspectral imagery with high spatial and spectral resolution. Although the importance of atmospheric correction has been reduced since imagery of drones were acquired at a low altitude,studies on the conversion process from raw data to spectral reflectance should be done for studies such as estimating the concentration of surface materials using hyperspectral imagery. In this study, a vicarious radiometric calibration and an atmospheric correction algorithm based on atmospheric radiation transfer model were applied to hyperspectral data of drone and the results were compared and analyzed. The vicarious calibration method was applied to an empirical line calibration using the spectral reflectance of a tarp made of uniform material. The atmospheric correction algorithm used ATCOR-4 based Modran-5 that was widely used for the atmospheric correction of aerial hyperspectral imagery. As a result of analyzing the RMSE of the difference between the reference reflectance and the correction, the vicarious calibration using the tarp in a single period of hyperspectral image was the most accurate, but the atmospheric correction was possible according to the application purpose of using hyperspectral imagery. If the correction process of normalized spectral reflectance is carried out through the additional vicarious calibration for imagery from multiple periods in the future, accurate analysis using hyperspectral drone imagery will be possible.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.4
• /
• pp.136-150
• /
• 2022

In this study, a comparative review was conducted on how to use RGB images to obtain river topographic information, which is one of the most essential data for eco-friendly river management and flood level analysis. In terms of the topographic information of river zone, to obtain the topographic information of flow section is one of the difficult topic, therefore, this study focused on estimating the river topographic information of flow section through RGB images. For this study, the river topography surveying was directly conducted using ADCP and RTK-GPS, and at the same time, and orthomosiac image were created using high-resolution images obtained by drone photography. And then, the existing developed regression equations were applied to the result of channel topography surveying by ADCP and the band values of the RGB images, and the channel bathymetry in the study area was estimated using the regression equation that showed the best predictability. In addition, CCHE2D flow modeling was simulated to perform comparative verification of the topographical informations. The modeling result with the image-based topographical information provided better water depth and current velocity simulation results, when it compared to the directly measured topographical information for which measurement of the sub-section was not performed. It is concluded that river topographic information could be obtained from RGB images, and if additional research was conducted, it could be used as a method of obtaining efficient river topographic information for river management.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.2
• /
• pp.69-78
• /
• 2024

Recently, the use of CCTV to prevent crowd accidents has been promoted, but research is needed to compensate for the spatial limitations of CCTV. In this study, pedestrian density was measured using drone footage, and based on a review of existing literature, a threshold of 6.7 people/m² was selected as the cutoff risk level for crowd accidents. In addition, we conducted a preliminary study to determine drone parameters and found that the pedestrian recognition rate was high at a drone altitude of 20 meters and an angle of 60°. Based on a previous study, we selected a target area with a high concentration of pedestrians and measured pedestrian density, which was found to be 0.27~0.30 per m². The study shows it is possible to measure risk levels by determining pedestrian densities in target areas using drone images. We believe drone surveillance will be utilized for crowd safety management in the near future.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.1
• /
• pp.143-149
• /
• 2018

This paper presents an implementation of a streaming system which can forward live video stream to multiple users from a Phantom4, which is a drone made by DJI. We constructed the streaming server on Raspberry Pi 3 board for high mobility. Also We implemented the system so that the video stream can be played on any devices if the HTML5 standard web browser is utilized. We compiled C codes of FFmpeg open sources and installed in the Raspberry Pi3 as the streaming server and developed a Java application to execute as the integrated server that controls the other softwares on the streaming server. Also we developed an Android application which receives the live video stream from the drone and sends the streaming server continuously. The implemented system in this paper can successfully stream the live video on 24 frames per second at the resolution of 148x112 in considering the low hardware throughput of the streaming server.

• Ecology and Resilient Infrastructure
• /
• v.6 no.3
• /
• pp.171-177
• /
• 2019

The hyperspectral images can be analyzed in more detail compared to the conventional multispectral images so they can be used for analyzing surface properties which are difficult to detect. Therefore, the purpose of this study is to obtain information on river environment by using actual depth data and drone-based images. For this purpose, this study acquired the image values for 100 points of 1 survey line using drone-based hyperspectral sensors and analyzed the correlation in comparison with the actual depth information obtained through ADCP. The ADCP measurements showed that the depth tended to get deeper toward the center and that the average water depth was 0.81 m. As a result of analyzing the hyperspectral images, the value of maximum intensity was 645 and the value of minimum intensity was 278, and the correlation between the actual depth and the results of analyzing the hyperspectral images showed that the depth increased as the value of maximum intensity decreased.

• Korean Journal of Remote Sensing
• /
• v.38 no.3
• /
• pp.237-250
• /
• 2022

In this study, we propose a method to estimate the biomass of invertebrate grazers from the videos with underwater drones by using a multi-object tracking model based on deep learning. In order to detect invertebrate grazers by classes, we used YOLOv5 (You Only Look Once version 5). For biomass estimation we used DeepSORT (Deep Simple Online and real-time tracking). The performance of each model was evaluated on a workstation with a GPU accelerator. YOLOv5 averaged 0.9 or more mean Average Precision (mAP), and we confirmed it shows about 59 fps at 4 k resolution when using YOLOv5s model and DeepSORT algorithm. Applying the proposed method in the field, there was a tendency to be overestimated by about 28%, but it was confirmed that the level of error was low compared to the biomass estimation using object detection model only. A follow-up study is needed to improve the accuracy for the cases where frame images go out of focus continuously or underwater drones turn rapidly. However,should these issues be improved, it can be utilized in the production of decision support data in the field of invertebrate grazers control and monitoring in the future.