• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.11-20
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• 2010

In situation that carbon dioxide emissions are being increased as urbanization, urban green space is being promoted as an alternative to find solution for these problems. In urban areas, trees have the ability to reduce carbon dioxide as well as to be aesthetic effect. In this study, we proposed the methodology which uses only LIDAR data in order to extract these trees information effectively. To improve the operational efficiency according to the extraction of trees, the proposed methodology was carried out using multiple data processing such as point, polygon and raster. Because the existing NDSM(Normalized Digital Surface Model) contains both the building and tree information, it has the problems of high complexity of data processing for extracting trees. Therefore, in order to improve these problems, this study used modified NDSM which was removed estimate regions of building. To evaluate the performance of the proposed methodology, three different zones which coexist buildings and trees within urban areas were selected and the accuracy of extracted trees was compared with the image taken by digital camera.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.383-387
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• 2003

최근 고해상도의 영상의 출현과 더불어 도심지역의 지물ㆍ지모에 대한 상세한 묘사가 가능해지고 있다. 하지만 도심지역의 지물ㆍ지모의 복잡성으로 인하여 그 추출이 쉽지 않다, 특히, 건물에 의한 가림, 그림자에 의한 정보 왜곡 등의 발생으로 추출의 어려움을 겪고 있다. 건물에 의한 폐색은 다른 위치에서 촬영을 하므로서 보정을 할 수 있지만 그림자에 의한 영향은 촬영위치에 상관없이 항상 발생한다. 본 연구에서는 도심지역에서 촬영한 컬러항공사진에서 그림자에 의한 정보 왜곡을 보정하여 그 판독력을 증대하고자 한다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.497-500
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• 2008

3차원 오브젝트의 위치 및 정보 획득을 위한 레이저레이더 시뮬레이션의 성능을 향상시키기 위해서는 시뮬레이션의 결과로 획득되는 공간의 범위와 해당 사물의 정보를 정확하고 빠르게 획득해야 한다. 본 연구에서는 이러한 레이더 시뮬레이션의 성능을 향상시키기 위해서 3차원 공간 데이터를 공간DB에 저장하고, 질의를 수행하여 해당 3차원 오브젝트의 정보를 효과적으로 추출해내는 방법론을 제시하였다. 이를 위해 본 연구에서는 시뮬레이션에서 사용되는 3차원 지형지물(지형, 건물 사물 등) 모델의 정보를 데이터모델링을 통해 토폴로지 형태를 갖도록 하였으며, 이를 공간DB에 저장하고, 레이저 신호와의 연산 쿼리를 시행하는 과정을 예시하였다. 이러한 과정을 구현하기 위하여 OGC 기반의 공간 데이터 타입, 함수, 인덱스들을 제공하는 PostgreSQL과 PostGIS를 사용하였다. 지형, 건물, 탱크 등 이렇게 세 가지의 범주의 사물로 나누어 각각을 공간DB로 구현, 쿼리를 실시하였다. 지형정보는 TIN을 사용하였고, 건물의 좌표 값들은 도화원도에서 추출하였으며, 탱크와 같은 사물은 VRML 모델의 좌표 값을 사용하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.1
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• pp.19-26
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• 2003

As recently, high-resolution satellite images of 1m spatial resolution are opened to the public and able to be used commercially, the studies that make ortho-images using them and apply to digital mapping and database of geo-spatial information system are having been progressed actively. Therefore, the purposes of this study are to establish the auto-extraction methods and to develope algorithms for automatically extracting buildings out of man-made structures, after making the IKONOS ortho-image. As the result of this study, we can extract buildings automatically at 72% out of the whole buildings. And we have analyzed the error trend by means of the comparison with ortho-image, digital map and drawing result, then we could know that obtain the good result for extraction of the building through the methods and algorithms of this study.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.127-132
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• 2007

위성영상 기술의 발달과 고해상도 위성영상의 해상도 규제가 완화됨에 따라 건물의 높이 정보를 획득하는데 있어 고해상도 위성영상의 그림자 정보를 이용하는 연구들이 활발히 수행되어지고 있다. 그림자 정보를 이용하여 건물 높이 정보를 획득하는 연구의 정확도를 높이기 위해서는 정확한 건물의 그림자 탐지가 선행되어야 한다. 따라서 본 논문에서는 단영상을 이용한 그림자 탐지기법인 임계값법(Thresholding), 영상분류법, 영역확장법(Region Growing)을 건물의 그림자 탐지에 적용하여 각 기법의 장단점과 정확도를 평가하였다. 영상에서 수동으로 건물의 그림자를 디지타이징한 참조 자료와 기법들을 적용하여 탐지한 결과 영상을 시각적으로 비교하였고, 오차행렬(Confusion Matrix)을 이용한 전체정확도(Accuracy), F-measure, AOR(Area Overlap Ratio)을 이용하여 정량적인 정확도평가를 수행하였다. 실험결과 영역확장법을 적용한 경우 시각적 정량적으로 가장 높은 정확도를 보였으며, 영상분류법을 적용한 경우 시각적으로는 임계값을 적용한 경우보다 좋은 결과를 보였으나 정량적으로는 가장 낮은 정확도를 보였다.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.97-106
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• 2020

The factory information provided by the Industrial Location Information System (ILIS) is provided as raw data by the Korea Industrial Complex Corporation and registered after a filtering process, so the new factory information update is slow. In this study, to solve the problem of updating factory information of industrial location information system, using building data of road name address with relatively fast renewal cycle and building data of real estate, we compared the factory information of existing ILIS and extracted new factory information. In the process of comparison, a method was proposed to compare spatial objects of different types with point data and polygon data. Attribute information matching and object matching were performed, and attribute values of new factory information were extracted. The accuracy evaluation of the proposed spatial analysis method showed 79% accuracy, and the above matching technique was used to confirm the possibility of convergence of road name address data, real estate data and factory information of ILIS.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.2
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• pp.163-172
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• 2009

BIM technologies based on three-dimensional parametric solid modeling can provide building industries with a wide range of information, and then enable not only to automate architectural drawings, detect clashes between building components, and estimate building materials, but also to manage effectively architectural and engineering information about building spaces, structures, energy, just-in-time delivery, facility management, and code checking. This paper presents an implementation to extract geometric data from IFC files, and validates the system with simple and complex buildings.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.685-694
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• 2022

Building information is essential for various urban spatial analyses. For this reason, continuous building monitoring is required, but it is a subject with many practical difficulties. To this end, research is being conducted to extract buildings from satellite images that can be continuously observed over a wide area. Recently, deep learning-based semantic segmentation techniques have been used. In this study, a part of the structure of the context-based ResU-Net was modified, and training was conducted to automatically extract a building from a 30 cm Worldview-3 RGB image using SpaceNet's building v2 free open data. As a result of the classification accuracy evaluation, the f1-score, which was higher than the classification accuracy of the 2nd SpaceNet competition winners. Therefore, if Worldview-3 satellite imagery can be continuously provided, it will be possible to use the building extraction results of this study to generate an automatic model of building around the world.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.3-11
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• 2014

Recently, rapid urbanization has necessitated continuous updates in digital map to provide the latest and accurate information for users. However, conventional aerial photogrammetry has some restrictions on periodic updates of small areas due to high cost, and as-built drawing also brings some problems with maintaining quality. Alternatively, this paper proposes a scheme for efficient and accurate update of digital map using point cloud data acquired by Terrestrial Laser Scanner (TLS). Initially, from the whole point cloud data, the building sides are extracted and projected onto a 2D image to trace out the 2D building footprints. In order to register the footprint extractions on the digital map, 2D Affine model is used. For Affine parameter estimation, the centroids of each footprint groups are randomly chosen and matched by means of a modified RANSAC algorithm. Based on proposed algorithm, the experimental results showed that it is possible to renew digital map using building footprint extracted from TLS data.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1217-1232
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• 2009

In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.