• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.369-376
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• 2003

정보화사회에서 필수적인 사회간접자본으로 간주되고 있는 지리정보체계는 국토공간의 효율적인 이용 및 관리, 재해예방 등 다양한 분야에서 활용되고 있다. 특히, 전 국토의 2/3 이상을 차지하고 있는 산림은 환경적 가치의 확산에 따라 산림정보의 체계적인 관리를 위해 지리정보체계의 활용이 급증하고 있다. 본 연구에서는 수치사진측량 방법을 이용하여 수치임상도의 효율적인 수정 및 갱신방법을 제시하였고, 이를 실제작업에 적용함으로서 적합성을 검증하였다. 이를 위해 연구 대상지역의 항공사진 영상과 IKONOS 위성영상을 이용하여 수치임상도를 갱신함으로서 임상의 판독정확도, 임상의 위치 정확도, 에피폴라영상 제작과정에서 소요되는 제작시간 및 제작 숙련도, 제작비용 등을 비교, 분석함으로서 사용되는 수치영상의 적합성 여부를 판단하였다. 이러한 비교 결과를 토대로 위성영상을 이용하는 방법이 기존의 방법이나 항공사진을 이용한 방법에 비해 보다 효과적인 방법임을 판단할 수 있었으며, 고해상도 위성영상을 이용한 임상도 제작 및 갱신방법이 항공사진이 갖는 판독상의 문제점과 제작과정의 복잡함을 보완할 수 있는 방안이 될 수 있을 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.351-361
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• 2024

Satellite imagery contains various elements such as clouds, cloud shadows, and terrain shadows. Accurately identifying and eliminating these factors that complicate satellite image analysis is essential for maintaining the reliability of remote sensing imagery. For this reason, satellites such as Landsat-8, Sentinel-2, and Compact Advanced Satellite 500-1 (CAS500-1) provide Usable Data Masks(UDMs)with images as part of their Analysis Ready Data (ARD) product. Precise detection of clouds and their shadows is crucial for the accurate construction of these UDMs. Existing cloud and their shadow detection methods are categorized into threshold-based methods and Artificial Intelligence (AI)-based methods. Recently, AI-based methods, particularly deep learning networks, have been preferred due to their advantage in handling large datasets. This study aims to analyze the applicability of constructing UDMs for high-resolution satellite images through deep learning-based cloud and their shadow detection using open-source datasets. To validate the performance of the deep learning network, we compared the detection results generated by the network with pre-existing UDMs from Landsat-8, Sentinel-2, and CAS500-1 satellite images. The results demonstrated that high accuracy in the detection outcomes produced by the deep learning network. Additionally, we applied the network to detect cloud and their shadow in KOMPSAT-3/3A images, which do not provide UDMs. The experiment confirmed that the deep learning network effectively detected cloud and their shadow in high-resolution satellite images. Through this, we could demonstrate the applicability that UDM data for high-resolution satellite imagery can be constructed using the deep learning network.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.145-154
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• 2009

High spatial resolution satellite image classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, the extraction of the spatial information is one of the most important steps in high resolution satellite image classification. This study proposes a new spatial feature extraction method, named SSI(Shape-Size Index). SSI uses a simple region-growing based image segmentation and allocates spatial property value in each segment. The extracted feature is integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a SVM(Support Vector Machines) classifier. In order to evaluate the proposed feature extraction method, KOMPSAT-2 and QuickBird-2 data are used for experiments. It is demonstrated that proposed SSI algorithm leads to a notable increase in classification accuracy.

• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.32.6-33
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• 2010

현재 우리나라에서는 고해상도 광학관측위성인 다목적실용위성 3호(EO), 3A호(EO/IR)를 개발 중에 있으며, 이들의 개발 현황과 앞으로의 발전 방향에 대한 소개를 하고자 함. 지구표면의 정밀/광역 관측에 큰 장점을 지닌 관측위성은 많은 기술적 난관이 있으며, 이를 극복하기 위한 위성 본체 및 대구경 광학계 기술을 소개하고자 한다. 일반 천문 망원경용 광학계와의 차이점을 위주로 다목적실용위성 3호, 3A호의 위성광학계 설계의 특징과 현재 개발 중인 위성용 카메라의 조립 시험에 대한 현황을 위주로 향후 우리가 나아가야할 방향에 대한 고찰이 있을 예정이다. 또한 위성의 운영 특성과 운영 시 필요한 검보정 (Cal/Val) 과정에 대한 준비 상황도 소개하고자 한다.

• 한국지형공간정보학회:학술대회논문집
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• 2001.04a
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• pp.77-83
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• 2001

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2002.10a
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• pp.187-190
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• 2002

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.185-188
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• 2004

• Proceedings of the Optical Society of Korea Conference
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• 2001.08a
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• pp.216-217
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• 2001

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.61-72
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• 2003

Recently, demands with practical applications using high resolution imagery are increasing, according to addressing new sensor data. Since late 1990s, attempts for application to transportation problems of satellite imagery data have been intensively carried out in US, and these kinds of studies are being categorized into the name of RS-T(remote sensing in transportation). Further, this study is also linked with GIS-T(GIS for transportation), being in the matured stage, and then it contributes to wide uses of remotely sensed imagery. In this study, RS-T is briefly summarized. Later, in order to apply urban transportation analysis with satellite imagery as ancillary data, implementation, as prototyped extension program, for extraction of gravity-typed accessibility indices of transportation geography is performed in the ArcView-GIS environment. It is thought that applied results by two models among implemented models in this study can be utilized to characterize transportation accessibility in a region and to apply as useful statistics related to urban transportation status for regional transportation planning, if time series data are used.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.563-569
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• 2021

With the launch of Compact Advanced Satellite 500 series of various characteristics and the operation of KOMPSAT-3/3A, uses of high-resolution satellite images have been continuously increased. Especially, in order to provide satellite images in the form of ARD (Analysis Ready Data), various pre-processing such as geometric correction and radiometric correction have been developed. For pre-processing of high spatial satellite imagery, auxiliary information, such as solar zenith, solar azimuth and offnadir angle, should be required. However, most of the high-resolution satellite images provide the solar zenith and nadir angle for the entire image as a single variable. In this paper, the solar zenith and offnadir angle corresponding to each pixel of the image were calculated using RFM (Rational Function Model) and auxiliary information of the image, and the quality of extracted information were evaluated. In particular, for the utilization of pixel-based solar zenith and offnadir angle, pixel-based auxiliary data were applied in calculating the top of atmospheric reflectance, and comparative evaluation with a single constant-based top of atmospheric reflectance was performed. In the experiments using various satellite imagery, the pixel-based solar zenith and offnadir angle information showed a similar tendency to the auxiliary information of satellite sensor, and it was confirmed that the distortion was reduced in the calculated reflectance in the top of atmospheric reflectance.