• 대한공간정보학회지
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• 제14권1호
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• pp.37-47
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• 2006

시시각각으로 변화하는 도시지역의 변화 모니터링이나 신속한 피해현황 정보 취득이 필요한 재난지역을 관측하기 위하여 저고도 항공촬영기술이 개발되고 있다. 저고도 촬영시스템은 대상지역을 보다 상세하게 촬영할 수 있고 관측시기를 자율적으로 조절할 수 있는 장점을 갖고 있다. 특히 성능, 안전성, 내구성, 휴대성 측면에서 기능이 향상되고 있는 회전익 무인헬기는 이동성과 접근성이 뛰어나고 안전하게 근접촬영이 가능하여 근거리 사진측량용 탑재체로 각광받고 있다. 본 연구에서는 대상지역을 신속하고 경제적으로 관측할 수 있는 저고도촬영시스템을 개발하여 영상자료를 취득하고, 기하보정과 영상모자이크 기법을 적용하여 영상지도를 제작하는 방안을 제시하였다.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2017년도 춘계공동학술대회
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• pp.42-42
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• 2017

Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.

• 한국산업융합학회 논문집
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• 제23권2_2호
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• pp.209-218
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• 2020

Various studies and business investments have been performed on UAV in the field of spatial information industry, and it is judged that this industry has being evolved into an expansion stage as a legalization progresses. In addition, public institutions such as Korea Land and Geospatial Information Corporation, Korea Expressway Corporation, and Korea Land and Housing Corporation which have relatively much utilized spatial information work have entered into the stage of settling with active introduction for reasons of work efficiency and business management. However, surveying drones are still classified as expensive equipment, which is a burden on general business application and technology popularization. Moreover, the stabilization of reliability of various location information acquired from UAV is a part of ongoing research and supplementation. Therefore, in this study, to use image information acquired from low-cost UAV as reliable spatial information data, the flight altitude was changed and compared with the result of double transverse flight with conventional photographing technique. As a result, there was no change in the result value at low altitude, but the result showed more than 30% accuracy and accuracy improvement for the X, Y value at the altitude of 130m or higher than the conventional method.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.249-250
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• 2010

The study aims to propose a method that shall rapidly acquire 3D spatial information of the frequently changing city areas by using the low altitude aerial images taken by the UAV. The artificial 3D model of the artificial structures was constructed using the aerial image data photographed at the test area, calibration data of the non-metric camera and the results of the ground control point survey. Also, the digital surface model was created for areas that were changed due to a number of civil works. Through the above studies, the possibilities of constructing a 3D virtual city model, renewal of 3D GIS database, abstraction of changed information in geographic features and on-demand updating of the digital map were suggested.

• International Journal of Advanced Culture Technology
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• 제7권4호
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• pp.327-333
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• 2019

Wind speed data constitute important weather information for aircrafts flying at low altitudes, such as drones. Currently, the accuracy of low altitude wind predictions is much lower than that of high-altitude wind predictions. Deep neural networks are proposed in this study as a method to improve wind speed forecast information. Deep neural networks mimic the learning process of the interactions among neurons in the brain, and it is used in various fields, such as recognition of image, sound, and texts, image and natural language processing, and pattern recognition in time-series. In this study, the deep neural network model is constructed using the wind prediction values generated by the numerical model as an input to improve the wind speed forecasts. Using the ground wind speed forecast data collected at the Boseong Meteorological Observation Tower, wind speed forecast values obtained by the numerical model are compared with those obtained by the model proposed in this study for the verification of the validity and compatibility of the proposed model.

• International Journal of Contents
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• 제13권3호
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• pp.1-8
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• 2017

Rice plant numbers and density are key factors for yield and quality of rice grains. Precise and properly estimated rice plant numbers and density can assure high yield from rice fields. The main objective of this study was to automatically detect and count rice plants using images of usual field condition from an unmanned aerial vehicle (UAV). We proposed an automatic image processing method based on morphological operation and boundaries of the connected component to count rice plant numbers after transplanting. We converted RGB images to binary images and applied adaptive median filter to remove distortion and noises. Then we applied a morphological operation to the binary image and draw boundaries to the connected component to count rice plants using those images. The result reveals the algorithm can conduct a performance of 89% by the F-measure, corresponding to a Precision of 87% and a Recall of 91%. The best fit image gives a performance of 93% by the F-measure, corresponding to a Precision of 91% and a Recall of 96%. Comparison between the numbers of rice plants detected and counted by the naked eye and the numbers of rice plants found by the proposed method provided viable and acceptable results. The $R^2$ value was approximately 0.893.

• 대한원격탐사학회지
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• 제36권2_2호
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• pp.337-349
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• 2020

본 연구에서는 저고도 원격탐사 기구인 Helikite를 이용하여 연안지역의 영상을 획득하였다. 그리고 획득된 영상에서 4 종류의 영역 분할 알고리즘을 이용하여 육지와 수괴의 영역을 분할해 낸 후 경계 검출법을 이용해 수륙경계선을 추출하였다. 실측데이터의 부재로 정량적인 비교는 불가능했으나, 수괴와 육지의 구분이 비교적 명확한 적외선(Infrared band) 영역의 영상을 기준으로 각 알고리즘들에 의해 추출된 수륙경계선을 비교하였다. 그 결과, 영상에서 수괴와 육지의 구분이 모호한 부분에서 각각의 알고리즘의 결과가 크게 차이가 나는 것을 발견할 수 있었다. 이는 각 알고리즘이 영역을 구분하는데 사용되는 영상의 수치값(Digital number)의 임계치를 선정하는 과정에서 생긴 차이라고 판단된다. 이와 같이 다양한 알고리즘을 통한 수륙경계선의 추출은 향후 연속 모니터링이 가능한 자동 관측시스템과 함께 활용하여 고정지역에서 얻은 수년의 장기간의 데이터를 통해 연안 지역 형태의 급격한 변화를 설명하는데 도움을 줄 것으로 기대된다.

• 대한공간정보학회지
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• 제16권4호
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• pp.79-87
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• 2008

위성측량이나 기존의 항공측량에 비해 경제적이면서 기상영향을 덜 받는 저고도 고해상 영상의 취득과 항공사진측량의 많은 수요를 충족하기 위해 신속한 맵핑을 위한 UAV(Unmanned Aerial Vehicle) 기술 개발이 요구되고 있으며, 특히 효율적인 지형보정에 관한 연구가 중요한 이슈로 부각되고 있다. 그러나, 민간분야 활용을 위한 UAV의 높은 잠재력에 비해 최근까지 직접 지형보정과 같은 사진측량측면에서의 기술개발은 초기 단계에 머물고 있으며, 지속적인 연구와 추가적인 기술개발 노력이 필요하다. 본 연구에서는 최소한의 지상기준점 정보를 이용하여 간편한 부등각사상변환식과 부등각사상변환의 블록조정에 의해 자동으로 저고도 UAV 영상을 기하보정하는 기법을 제안하였으며, 상용 프로그램 처리결과와 비교를 통하여 UAV 정지영상 기하모형식으로서의 적용가능성을 평가하였다.

• 한국산업융합학회 논문집
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• 제26권5호
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• pp.775-784
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• 2023

Drone images are being used more and more actively in the fields of surveying and spatial information, and are rapidly replacing existing aerial and satellite images. The technology of quickly acquiring real-time data at low cost and processing it is now being applied to actual industries beyond research. However, there are also problems encountered as this progresses. When high-resolution spatial information is acquired using a general 2D flight plan for a terrain with sever undulations, problems arise due to the difference in resolution of the data. In particular, when a low-altitude high-resolution image is taken using a drone in a mountainous or steep terrain, there may be a problem in image matching due to a resolution difference caused by terrain undulations. This problem occurs because a drone acquires data while flying on a 2D plane at a fixed altitude, just like conventional aerial photography. In order to acquire high-quality 3D data using a drone, the scale difference for the shooting distance should be considered. In addition, in order to obtain facade images of large structures, it is necessary to take images in 3D space. In this study, in order to improve the disadvantages of the 2D flight method, a 3D flight plan was established for the study area, and it was confirmed that high-quality 3D spatial information could be obtained in this way.

• 한국환경복원기술학회지
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• 제23권5호
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• pp.59-71
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• 2020

Using high-resolution stereoscopic aerial images (in 2008, 2012 and 2016), we conducted to analyze the spatial characteristics affecting evergreen coniferous die-off in the northwestern ridge (major distribution area such as Abies nephrolepis), Seoraksan National Park. The detected number of dead trees at evergreen coniferous forest (5.24㎢) was 1,223 in 2008, was 2,585 in 2012 and was 3,239 in 2016. The number of cumulated dead trees was 7,047 in 2016. In recent years, the number of dead trees increased relatively in the northwest ridge, Seoraksan National Park. Among the analysed spatial factor (altitude, aspect, slope, solar radiation and topographic wetness index), the number of dead trees was increased in the conditions with high altitude, steep slope and dry soil moisture. A spatial distribution of dead tree was divided into 2 groups largely (high altitude with high solar radiation, low altitude with steep slope). In conclusion, the dead trees of evergreen coniferous were concentrated at spatial distribution characteristics causing dryness in the northwestern ridge, Seoraksan National Park.