• 한국측량학회지
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• 제33권1호
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• pp.11-21
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• 2015

정사영상은 DSM(Digital Surface Model; 수치표면모델)을 이용하여 항공영상의 왜곡과 기복변위 등으로 발생하게 되는 기하학적 변위를 제거함으로써 제작된다. 따라서 원영상의 해상도와 DSM의 정확도는 정사영상의 정확도에 큰 영향을 미치게 된다. 최근 제공되고 있는 DMCII250 항공영상은 GSD 5cm급 고해상도의 영상을 제공함으로써 고밀도 점군자료의 생성과 함께 정사영상의 품질 향상을 기대할 수 있을 것으로 예상된다. 이에 본 연구에서는 DMCII250 항공영상으로부터 고밀도의 점군자료를 추출하여 DSM을 제작하고 이를 이용하여 정사영상을 생성함으로써 고밀도 DSM 제공에 따른 고품질 정사영상의 제작 가능성과 그 정확도를 검토하고자 하였다. 연구결과 기존 수치지형도 또는 DSM정보를 이용하여 제작한 정사영상에 비하여 높은 정도의 위치정확도와 고품질의 정사영상의 확보가 가능함을 확인할 수 있었다.

• 대한원격탐사학회지
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• 제25권3호
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• pp.233-242
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• 2009

This paper presents two different types of supervised classifiers such as support vector machine (SVM) and spectral angle mapper (SAM). The Compact Airborne Spectrographic Imager (CASI) high resolution aerial image was classified with the above two classifier. The image was classified into eight land use /land cover classes. Accuracy assessment and Kappa statistics were estimated for SVM and SAM separately. The overall classification accuracy and Kappa statistics value of the SAM were 69.0% and 0.62 respectively, which were higher than those of SVM (62.5%, 0.54).

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.515-517
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• 2007

In this study we attempted to estimate damage scope such as bridges destruction, farmland deformation, forest damage, etc occurred by typhoon using two digital aerial images for future high-resolution Kompsat-3 applications. The process procedures are followings: First, image registration between time-different aerial images was implemented. In this process one image was geometrically corrected by image-to-image registration. Second, image classification was done according to 4 classes. Finally through the comparison of classified two images the area of damage by flood and storm was approximately calculated. These results showed that it is possible to estimate the damage scale relatively rapidly using high-resolution images.

• 대한원격탐사학회지
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• 제18권6호
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• pp.327-336
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• 2002

다양한 분야에서 고해상도 위성영상의 활용도가 높아짐에 따라 많은 고해상도 인공위성이 발사되고 있으며 발사예정에 있다. 본 논문은 DEM과 항공사진영상을 이용하여 임의의 궤도정보와 자세정보를 가지는 인공위성에 대하여 모의위성영상을 제작할 수 있는 두 가지 방법을 제안하였다. 제작된 모의위성영상의 센서모델에서 자세는 변화가 없는 것으로 가정하였고, 투영중심의 위치는 위성의 진행방향에 따라 변화하는 모델을 사용하였다. 또한 자세와 위치에 변화를 준 모의위성영상을 제작하여 입체시 가능성을 실험하였으며, 제작된 모의위성영상의 정확도를 검증하기 위해 공간전방 교회를 이용하여 검증하였다.

• 한국측량학회지
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• 제21권1호
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• pp.1-7
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• 2003

최근 항공사진 정사영상의 활용이 증가하고 있으며, 이에 맞추어 고해상도 위성영상을 이용한 지리정보시스템 구축을 위한 많은 연구가 진행 중에 있다. 또한 공간해상도가 6.6m급인 아리랑 1호 위성영상을 이용한 많은 연구가 시행중인 이즈음, 항공사진과 위성영상간의 판독성에 대한 평가가 필요하다. 이 연구에서는 항공사진을 스캔한 영상, 그 항공사진을 이용하여 아리랑 1호와 동일한 해상도로 재배열한 영상, 그리고 아리랑 1호 위성영상을 실험 영상으로 이용하여 각각 정사영상을 제작하고, 판독하려는 지형지물을 분류하였으며, 각각의 정사영상에서 그 분류항목에 대한 판독이 어느 수준까지 가능한지에 대한 평가를 하였다. 판독 분석결과, 판독을 위해 분류한 지형지물 중 항공사진을 이용한 정사영상에서 판독할 수 있는 지형지물의 양에 비해 항공사진 영상을 재배열한 영상의 정사영상에서는 대략 61%, 아리랑 1호 위성영상의 정사영상에서는 대략 41%를 판독할 수 있었으며, 이와 같은 실험연구를 통해 아리랑 1호 위성 영상은 지도갱신, 비접근지역에 대한 지형정보 획득, 환경감시 등의 분야에 활용할 수 있을 것으로 판단하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.453-454
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• 2003

Most research materials (data), which are used for the study of digital mapping and digital elevation model (DEM) in the field of Remote Sensing and Aerial Photogrammetry are aerial photographs and satellite images. Additionally, they are also used for National land mapping, National land management, environment management, military purposes, resource exploration and Earth surface analysis etc. Although aerial photographs have high resolution, the data, which they contain, are not used for environment exploration that requires continuous observation because of problems caused by its coastline, as well as single - spectral and long-term periodic image. In addition to this, they are difficult to interpret precisely because Satellite Images are influenced by atmospheric phenomena at the time of photographing, and have by far much lower resolution than existing aerial photographs, while they have a great practical usability because they are mulitispectral images. The PKNU 2 is an aerial photographing system that is made to compensate with the weak points of existing aerial photograph and satellite images. It is able to take pictures of very high resolution using a color digital camera with 6 million pixels and a color infrared camera, and can take perpendicular photographs because PKNU 2 system has equipment that makes the cameras stay level. Moreover, it is very cheap to take pictures by using super light aircraft as a platform. It has much higher resolution than exiting aerial photographs and satellite images because it flies at a low altitude about 800m. The PKNU 2 can obtain multispectral images of visible to near infrared band so that it is good to manage environment and to make a classified diagram of vegetation.

• 한국측량학회지
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• 제33권3호
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• pp.173-179
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• 2015

In this paper, object-based classification of urban areas based on a combination of information from lidar and aerial images is introduced. High resolution images are frequently used in automatic classification, making use of the spectral characteristics of the features under study. However, in urban areas, pixel-based classification can be difficult since building colors differ and the shadows of buildings can obscure building segmentation. Therefore, if the boundaries of buildings can be extracted from lidar, this information could improve the accuracy of urban area classifications. In the data processing stage, lidar data and the aerial image are co-registered into the same coordinate system, and a local maxima filter is used for the building segmentation of lidar data, which are then converted into an image containing only building information. Then, multiresolution segmentation is achieved using a scale parameter, and a color and shape factor; a compactness factor and a layer weight are implemented for the classification using a class hierarchy. Results indicate that lidar can provide useful additional data when combined with high resolution images in the object-oriented hierarchical classification of urban areas.

• 한국산업융합학회 논문집
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• 제26권6_2호
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• pp.1063-1071
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• 2023

Unmanned aerial vehicles (UAVs, drones) are becoming increasingly useful in a variety of fields. Advances in UAV and camera technology have made it possible to equip them with ultra-high resolution sensors and capture images at low altitudes, which has improved the reliability and classification accuracy of object identification on the ground. The distinctive contribution of this study is the derivation of sensor-specific performance metrics (GRD/GSD), which shows that as the GSD increases with altitude, the GRD value also increases. In this study, we identified the characteristics of various onboard sensors and analysed the image quality (discrimination resolution) of aerial photography results using UAVs, and calculated the shooting conditions to obtain the discrimination resolution required for reading ground objects.

• 환경영향평가
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• 제18권5호
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• pp.281-291
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• 2009

In Total Water Pollutant Load Management System of Korea, unit load approach based on land register data is currently used for the estimation of non-point pollutant load. However, a problem raised that land register data could not always reflect the actual land surface coverages which determine runoff characteristics of non-point pollution sources. As a way to overcome this, we tried to establish quantitative relationships between the aerial images (0.4m resolution) which reflect actual land surface coverages and the land registration maps according to the 19 major designated land-use categories in Kyeongan watershed. Analyses showed different relationships according to the land-use categories. Only a few land-use categories including forestry, road and river showed essentially identical and some categories such as orchard, parking lot and sport utility site showed no relationships at all between image data and land register data. Except for the two cases, all the other categories showed statistically significant linear relationships between image data and land register data. The analyses indicate that using high resolution aerial maps is a better way to estimate non-point pollutant load. If the aerial maps are not available, application of the linear relationships as conversion factors of land register data to image data could be an possible option to estimate non-point pollutant loads for the specific land-use categories in Kyeongan watershed.

• 대한원격탐사학회지
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• 제23권5호
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• pp.409-420
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• 2007

Since 1988, pine wilt disease has spread over rapidly in Korea. It is not easy to detect the damaged pine trees by pine wilt disease from conventional remote sensing skills. Thus, many possibilities were investigated to detect the damaged pines using various kinds of remote sensing data including high spatial resolution satellite image of 2000/2003 IKONOS and 2005 QuickBird, aerial photos, and digital airborne data, too. Time series of B&W aerial photos at the scale of 1:6,000 were used to validate the results. A local maximum filtering was adapted to determine whether the damaged pines could be detected or not at the tree level from high resolution satellite images, and to locate the damaged trees. Several enhancement methods such as NDVI and image transformations were examined to find out the optimal detection method. Considering the mean crown radius of pine trees, local maximum filter with 3 pixels in radius was adapted to detect the damaged trees on IKONOS image. CIR images of 50 cm resolution were taken by PKNU-3(REDLAKE MS4000) sensor. The simulated CIR images with resolutions of 1 m, 2 m, and 4 m were generated to test the possibility of tree detection both in a stereo and a single mode. In conclusion, in order to detect the pine tree damaged by pine wilt disease at a tree level from satellite image, a spatial resolution might be less than 1 m in a single mode and/or 1 m in a stereo mode.