• Title/Summary/Keyword: UAV 원격탐사

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A Study on Data Acquisition in the Invisible Zone of UAV through LTE Remote Control (LTE 원격관제를 통한 UAV의 비가시권 데이터 취득방안)

  • Jeong, HoHyun;Lee, Jaehee;Park, Seongjin
    • Korean Journal of Remote Sensing
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    • v.35 no.6_1
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    • pp.987-997
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    • 2019
  • Recently the demand for drones is rapidly increasing, as developing Unmanned Aerial Vehicle (UAV) and growing interest in them. Compared to traditional satellite and aerial imagery, it can be used for various researches (environment, geographic information, ocean observation, and remote sensing) because it can be managed with low operating costs and effective data acquisition. However, there is a disadvantage in that only a small area is acquired compared to the satellite and an aircraft, which is a traditional remote sensing method, depending on the battery capacity of the UAV, and the distance limit between Ground Control System (GCS) and UAV. If remote control at long range is possible, the possibility of using UAV in the field of remote sensing can be increased. Therefore, there is a need for a communication network system capable of controlling regardless of the distance between the UAV and the GCS. The distance between UAV and GCS can be transmitted and received using simple radio devices (RF 2.4 GHz, 915 MHz, 433 MHz), which is limited to around 2 km. If the UAV can be managed simultaneously by improving the operating environment of the UAV using a Long-Term Evolution (LTE) communication network, it can make greater effects by converging with the existing industries. In this study, we performed the maximum straight-line distance 6.1 km, the test area 2.2 ㎢, and the total flight distance 41.75 km based on GCS through LTE communication. In addition, we analyzed the possibility of disconnected communication through the base station of LTE communication.

Method to Extract Coastline Changes Using Unmanned Aerial Vehicle (무인항공기를 이용한 해안선 변화 추출에 관한 연구)

  • Lee, Kangsan;Choi, Jinmu;Joh, Chang-Hyeon
    • Journal of the Korean Geographical Society
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    • v.50 no.5
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    • pp.473-483
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    • 2015
  • In a coastal area, a plenty of research has adopted remotely sensed data. This is because longterm interaction between land and ocean makes continuous geographical changes in a broad extent and unaccessible areas. However, conventional remote sensing platforms such as satellite or airplane has several disadvantages including limited temporal resolution and high operational costs. Hence, this study uses a UAV system to detect a coastline and its movement. Result of coastline detection shows how the coastline moves in a day. Time-series coastlines were derived from UAV aerial images through digital image processing. There is a drawback in the stability of UAV compared to the conventional remote sensing platform, but the advantage appears on the economical efficiency. Since the latest studies shows an improvement of UAV for a variety of purposes in many fields, a UAV can also be utilized for regional study and spatial data acquisition platform. geography can also utilize a UAV as a spatial data acquisition platform for regional study.

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Analysis of Cropland Spectral Properties and Vegetation Index Using UAV (UAV를 이용한 농경지 분광특성 및 식생지수 분석)

  • LEE, Geun-Sang;CHOI, Yun-Woong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.4
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    • pp.86-101
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    • 2019
  • Remote sensing technology has been continuously developed both quantitatively and qualitatively, including platform development, exploration area, and exploration functions. Recently, the use cases and related researches in the agricultural field are increasing. Also, since it is possible to detect and quantify the condition of cropland and establish management plans and policy support for cropland and agricultural environment, it is being studied in various fields such as crop growth abnormality determination and crop estimation based on time series information. The purpose of this study was to analyze the vegetation index for agricultural land reclamation area using a UAV equipped with a multi-spectral sensor. In addition, field surveys were conducted to evaluate the accuracy of vegetation indices calculated from multispectral image data obtained using UAV. The most appropriate vegetation index was derived by evaluating the correlation between vegetation index calculated by field survey and vegetation index calculated from UAV multispectral image, and was used to analyze vegetation index of the entire area.

Development of Brightness Correction Method for Mosaicking UAV Images (무인기 영상 병합을 위한 밝기값 보정 방법 개발)

  • Ban, Seunghwan;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1071-1081
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    • 2021
  • Remote Sensing using unmanned aerial vehicles(UAV) can acquire images with higher time resolution and spatial resolution than aerial and satellite remote sensing. However, UAV images are photographed at low altitude and the area covered by one image isrelatively narrow. Therefore multiple images must be processed to monitor large area. Since UAV images are photographed under different exposure conditions, there is difference in brightness values between adjacent images. When images are mosaicked, unnatural seamlines are generated because of the brightness difference. Therefore, in order to generate seamless mosaic image, a radiometric processing for correcting difference in brightness value between images is essential. This paper proposes a relative radiometric calibration and image blending technique. In order to analyze performance of the proposed method, mosaic images of UAV images in agricultural and mountainous areas were generated. As a result, mosaic images with mean brightness difference of 5 and root mean square difference of 7 were avchieved.

Comparative Evaluation of UAV NIR Imagery versusin-situ Point Photo in Surveying Urban Tributary Vegetation (도심소하천 식생조사에서 현장사진과 UAV 근적외선 영상의 비교평가)

  • Lee, Jung-Joo;Hwang, Young-Seok;Park, Seong-Il;Um, Jung-Sup
    • Journal of Environmental Impact Assessment
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    • v.27 no.5
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    • pp.475-488
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    • 2018
  • Surveying urban tributary vegetation is based mainly on field sampling at present. The tributary vegetation survey integrating UAV NIR(Unmanned Aerial Vehicle Near Infrared Radiance) imagery and in-situ point photo has received only limited attentions from the field ecologist. The reason for this could be the largely undemonstrated applicability of UAV NIR imagery by the field ecologist as a monitoring tool for urban tributary vegetation. The principal advantage of UAV NIR imagery as a remote sensor is to provide, in a cost-effective manner, information required for a very narrow swath target such as urban tributary (10m width or so), utilizing very low altitude flight, real-time geo-referencing and stereo imaging. An exhaustive and realistic comparison of the two techniques was conducted, based on operational customer requirement of urban tributary vegetation survey: synoptic information, ground detail and quantitative data collection. UAV NIR imagery made it possible to identify area-wide patterns of the major plant communities subject to many different influences (e.g. artificial land use pattern), which cannot be acquired by traditional field sampling. Although field survey has already gained worldwide recognition by plant ecologists as a typical method of urban tributary vegetation monitoring, this approach did not provide a level of information that is either scientifically reliable or economically feasible in terms of urban tributary vegetation (e.g. remedial field works). It is anticipated that this research output could be used as a valuable reference for area-wide information obtained by UAV NIR imagery in urban tributary vegetation survey.

Development of Image Acquisition System based on a R/C helicopter (원격조종헬기를 이용한 영상획득시스템 구축)

  • Oh, Tae-Wan;Kim, Seong-Joon;Lee, Im-Pyeong;Ahn, Heung-Kyu
    • Proceedings of the KSRS Conference
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    • 2009.03a
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    • pp.305-308
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    • 2009
  • 최근 카메라와 같은 센서가 장착된 UAV(Unmanned Aerial Vehicle, 무인항공기)를 이용하는 분야는 방재, 농업, 군사 분야 등 매우 다양해지고 있다. 그러나 고품질의 영상데이터를 취득하기 위해서는 가벼우면서도 우수한 성능을 지닌 고가의 MEMS 센서 그리고 센서가 안정적으로 데이터를 획득할 수 있도록 안정적인 비행이 가능한 대형 UAV플랫폼으로 구성된 시스템이 필요하기 때문에 시스템 구축비용이 클 수밖에 없다. 본 연구에서는 저비용으로 영상 데이터를 취득할 수 있는 UAV시스템을 구축하여 취득된 영상데이터의 처리를 통해 얻어지는 영상의 품질을 살펴보고 그 효용성을 시험해보았다. 이를 위해서 고가인 UAV를 대신해 비교적 가격이 저렴한 R/C헬기(Remote Control, 원격조종 헬기)를 플랫폼으로 선정하고, 영상데이터를 수집하는 카메라센서를 탑재하였다. 그리고 탑재된 센서가 안정적으로 데이터를 취득할 수 있도록, 센서와 플랫폼 사이에 Gimbal을 장착하였다. 이렇게 구축된 시스템을 이용하여 시험비행을 해보았으며, 그 결과 플랫폼에 탑재된 센서로부터 비교적 안정적이고 양질의 이미지를 획득할 수 있었다. 본 연구에서 구축한 R/C 헬리콥터 시스템을 통하여 저비용/고효율의 영상데이터를 취득할 수 있음을 확인하였다. 구축된 시스템은 근접한 거리에서 대상물의 영상을 취득하기 때문에 고품질의 3차원 모델데이터 생성에 매우 도움이 될 것으로 생각한다.

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Correction of UAV's Position/Altitude through Aerial Triangulation (Aerial Triangulation을 이용한 UAV의 위치/자세 보정)

  • Choi, Kyoung-Ah;Lee, Im-Pyeong
    • Proceedings of the KSRS Conference
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    • 2009.03a
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    • pp.61-65
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    • 2009
  • 매년 재난/재해의 발생 빈도와 피해 규모가 증가하고 있다. 그 피해를 최소화하기 위해 주기적인 모니터링을 수행하여 위기 상황을 사전에 대비하고 긴급 대응 체계를 구축하여 상황 발생 시 피해 상황을 신속하게 파악할 수시스템에 있어야 한다. 모니터링의 용이성과 신속성을 확보하기 위해 UAV에 기반한 긴급 매핑 대한 관심이 증가하고 있다. 그러나 이러한 시스템으로부터 획득된 센서 데이터가 Georeferencing되었을 때 이로부터 다양한 공간 정보를 도출할 수 있다 본 논문에서는 UAV 기반의 매핑 시스템으로부터 획득된 센서 데이터를 시뮬레이션 해보고 시뮬레이션 데이터에 대하여 Aerial Triangulation을 수행하여 영상을 Georeferncing하고 위치/자세 정보를 보정하고자 한다. 실험은 (1) 시뮬레이션 데이터 생성, (2) 초기값 생성, (3) AT 수행을 통한 위치/자세 조정의 3단계로 구성된다. 800m 길이의 1개 스트립, 500m 길이의 2개 스트립으로 나눠 비행경로를 정하고 200m, 400m, 600m의 비행고도에 대하여 다양한 실험을 수행하였다. 실험 결과 위치/자세의 초기값 RMSE에서 90% 이상 개선된 RMSE를 얻을 수 있었으며, 비행고도가 높아질수록 RMSE의 향상도는 반비례하였다. 향후에는 Sequential 알고리즘을 적용하여 연산 속도를 향상시킬 수 있고 궁극적으로 실시간 영상 Georeferencing을 가능하게 할 것으로 기대된다.

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Estimation of Surface Layer Heat Flux Using the UHF Sensor Installed on UAV (UHF 센서 탑재 UAV를 이용한 지표층 열 플럭스 산출)

  • Kim, Min-Seong;Kwon, Byung Hyuk;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.1
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    • pp.265-276
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    • 2018
  • Observation and data analysis techniques have been developed for observational blind areas in the lower atmosphere that are difficult to be monitored with fixed equipment on the ground. The vertical data of temperature and relative humidity are remotely collected by the UHF radiosonde installed on UAV and compared with the data measured in the 10 m weather tower. From the validated vertical profile, extrapolated surface temperature and the bulk transfer method were used to estimate the sensible heat flux depending on the atmospheric stability. Compared with the sensible heat flux measured by the 3-dimensional ultrasonic anemometer on the ground, the error of the sensible heat flux estimated was 23% that is less than the range of 30% allowed in the remote sensing. Estimated atmospheric boundary layer height from UAV sensible heat fluxes can provide useful data for air pollution diffusion models in real time and economically.

A study on evaluation of levee crack based on ORS (광학원격탐사 기반의 제방 균열 평가에 관한 연구)

  • Kim, Jong Tae;Lee, Chang Hun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.224-224
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    • 2021
  • 광학원격탐사를 통해 취득할 수 있는 초분광 영상은 관련 기술의 발전으로 다양하게 활용이 되고 있다. 특히 초경량 UAV를 기반으로 초분광 센서를 적용한 광학원격탐사는 광범위하게 분포하는 국내 제방의 불안정 요소를 탐지하는데 보다 효과적일 것으로 판단되며 대상에 대한 광역모니터링을 통해 많은 자료를 얻을 수 있고, 고해상도 영상 자료를 활용한 세밀한 분광 및 공간정보 분석이 가능하다. 본 연구에서는 제방 균열 평가를 위해 UAV를 활용하여 안동댐 하류 제방 균열을 대상으로 고해상도 초분광 영상을 취득하였으며, 기 개발된 제방 균열 평가 소프트웨어를 이용하여 조도와 최대강도 데이터에 따른 제방 균열 평가를 실시하였다. 연구지역의 지질은 중생대 백악기의 일직층으로써 적색이암, 셰일, 역질사암 등이 주를 이루고 있으며 제방 내 토양은 대부분 입도가 균일하며 일부 역암이 관찰되는 지역으로 조립토가 주를 이루고 있다. 기 개발된 소프트웨어의 특징은 측정된 데이터를 바탕으로 균열 여부를 판별할 수 있는 프로그램으로써 측정지점마다 별도의 조도와 최대강도 데이터가 주어졌을때, 해당 데이터에 대한 균열 여부를 판별할 수 있다. 주요기능은 제방 균열 여부 판단, 데이터 입력 및 판단을 출력하기 위한 GUI 인터페이스를 제공한다. 연구 결과 제방 균열 평가 소프트웨어를 적용하여 균열과 비균열에 대한 탐지가 가능한 것으로 나타났다. 특히 비균열 포인트의 경우 암석이나 토양의 성질, 빛의 반사에 따라 일부 차이가 있지만 균열은 매우 유사한 반사율 정보를 보이는 것으로 나타났다.

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Semantic Segmentation of Heterogeneous Unmanned Aerial Vehicle Datasets Using Combined Segmentation Network

  • Ahram, Song
    • Korean Journal of Remote Sensing
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    • v.39 no.1
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    • pp.87-97
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    • 2023
  • Unmanned aerial vehicles (UAVs) can capture high-resolution imagery from a variety of viewing angles and altitudes; they are generally limited to collecting images of small scenes from larger regions. To improve the utility of UAV-appropriated datasetsfor use with deep learning applications, multiple datasets created from variousregions under different conditions are needed. To demonstrate a powerful new method for integrating heterogeneous UAV datasets, this paper applies a combined segmentation network (CSN) to share UAVid and semantic drone dataset encoding blocks to learn their general features, whereas its decoding blocks are trained separately on each dataset. Experimental results show that our CSN improves the accuracy of specific classes (e.g., cars), which currently comprise a low ratio in both datasets. From this result, it is expected that the range of UAV dataset utilization will increase.