• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.455-461
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• 2010

It is one among very important works to detect change in urban area for effectively maintaining city. But, recently it is become more difficult to extract various changes using traditional method based on orthophotos because objects in urban area get higher and become more complex. To resolve these problems, we introduce new digital imagining system Pictometry which can acquire images of five directions (oblique and nadir). In this study, we compared the digital interpretation results based on Pictometry to the results from traditional method. As a result, Pictometry showed the good results in change detection of urban area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.621-629
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• 2011

According to the development of technologies for generating the 3D spatial information, the needs for producing and updating the precise 3D objects with LoD 4 level are increased. On the other hand, the needs for real-time updating of 2D digital maps are expanded, based on the execution of various GIS projects. These 2D informations can be extracted from precisely constructed 3D spatial information, to do this the feasibility studies on extraction of the 2D information from the 3D spatial information is needed. In this study, 3D objects are modeled using multi-oblique images, and the objects are stereo-plotted using digital airborne images, as well. Then the two data sets are compared and analyzed. The results show that the accuracy assessments fulfill the 1/1,000 digital map accuracy standard of regulations for photogrametric surveying of National Geographic Information Institute, but the shapes and the areas of building objects are different between two data sets because of the portrayal standards. Consequently, researchers can conclude that it is possible to generate the building layer of large scale topographic map using multi-oblique images, but additional researches is needed to resolve the problems on differences of the portrayal standards.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.138-141
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• 2005

본 연구에서는 위성영상으로부터 정사투영 영상을 제작하고, 지상의 기준점 측량을 GCP를 이용하여 실시하여 경도, 위도 고도의 참조좌표를 정확히 수집하였다. 1:5,000 지형도를 디지타이징하여 만들어진 등고선도를 DEM으로 변환하여 고도별 RGB영상으로 화면에 보여지도록 하고, 각각의 경우에 대하여 제작된 정사투영 영상에 중첩해 봄으로써 제작된 정사투영영상의 정확도를 점검하여 수치지형도를 대신할 수 있는 3차원 영상지도를 제작하였다. 대상지역의 입체지형분석을 위한 3차원 입체 영상지도를 제작과 더불어 DEM을 이용한 지형의 경사도 분석과 방향분석, 지형표고모델, 다방향 입체영상을 생성할 수 있도록 하였다. 장차 국토계획 및 건설분야에서의 지형분석과 각종 구조물의 배치 및 관리, 하천 수계의 분포에 대한 댐 건설 최적지 선정, 도로계획선에 따른 각 방향의 조감도 제작, 토지 피복분류에 의한 토지이용과 지역개발계획 등 지역환경을 종합적으로 진단해 볼 수 있는 활용방안을 도출할 수 있는 적용실험을 하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.