• Title/Summary/Keyword: 건물추출

Search Result 462, Processing Time 0.029 seconds

Building Extraction and Digital Surface Models Generation from Stereo pairs of Aerial Images (입체 항공사진영상을 이용한 DSM생성 및 건물경계추출)

  • 유환희;김성우;성민규
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.16 no.2
    • /
    • pp.177-185
    • /
    • 1998
  • There is an increasing request for 3D data and outlines on building for urban planning and design. This paper describes an approach to extract building using Digital Surface Models(DSM) and stereo pairs of aerial images. DSM contain informations not only about the topographic surface like Digital Elevation Models(DEM), but also about buildings and other objects higher than the surrounding topographic surface, e.g. tees. We therefore describe our approach consisting of two step procedures. The first step of the approach is to generate DSM by stereo matching using Maximum Likelihood Estimation and Dynamic Programming. The proposed stereo matching is using the cost function for finding the disparity between the left and right image, and the Dynamic Programming for solving the stereo matching problem. The second step is to detect building outlines using the DSM and the edge informations extracted from a digital aerial image by Sobel Operator. The overlay analysis of the DSM and the edge information by Sobel Operator was efficient to detect building outlines.

  • PDF

Automatic Building Extraction Using SpaceNet Building Dataset and Context-based ResU-Net (SpaceNet 건물 데이터셋과 Context-based ResU-Net을 이용한 건물 자동 추출)

  • Yoo, Suhong;Kim, Cheol Hwan;Kwon, Youngmok;Choi, Wonjun;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.5_2
    • /
    • pp.685-694
    • /
    • 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.

Evaluation on Tie Point Extraction Methods of WorldView-2 Stereo Images to Analyze Height Information of Buildings (건물의 높이 정보 분석을 위한 WorldView-2 스테레오 영상의 정합점 추출방법 평가)

  • Yeji, Kim;Yongil, Kim
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.33 no.5
    • /
    • pp.407-414
    • /
    • 2015
  • Interest points are generally located at the pixels where height changes occur. So, interest points can be the significant pixels for DSM generation, and these have the important role to generate accurate and reliable matching results. Manual operation is widely used to extract the interest points and to match stereo satellite images using these for generating height information, but it causes economic and time consuming problems. Thus, a tie point extraction method using Harris-affine technique and SIFT(Scale Invariant Feature Transform) descriptors was suggested to analyze height information of buildings in this study. Interest points on buildings were extracted by Harris-affine technique, and tie points were collected efficiently by SIFT descriptors, which is invariant for scale. Searching window for each interest points was used, and direction of tie points pairs were considered for more efficient tie point extraction method. Tie point pairs estimated by proposed method was used to analyze height information of buildings. The result had RMSE values less than 2m comparing to the height information estimated by manual method.

Urban Area Building Reconstruction Using High Resolution SAR Image (고해상도 SAR 영상을 이용한 도심지 건물 재구성)

  • Kang, Ah-Reum;Lee, Seung-Kuk;Kim, Sang-Wan
    • Korean Journal of Remote Sensing
    • /
    • v.29 no.4
    • /
    • pp.361-373
    • /
    • 2013
  • The monitoring of urban area, target detection and building reconstruction have been actively studied and investigated since high resolution X-band SAR images could be acquired by airborne and/or satellite SAR systems. This paper describes an efficient approach to reconstruct artificial structures (e.g. apartment, building and house) in urban area using high resolution X-band SAR images. Building footprint was first extracted from 1:25,000 digital topographic map and then a corner line of building was detected by an automatic detecting algorithm. With SAR amplitude images, an initial building height was calculated by the length of layover estimated using KS-test (Kolmogorov-Smirnov test) from the corner line. The interferometric SAR phases were simulated depending on SAR geometry and changable building heights ranging from -10 m to +10 m of the initial building height. With an interferogram from real SAR data set, the simulation results were compared using the method of the phase consistency. One of results can be finally defined as the reconstructed building height. The developed algorithm was applied to repeat-pass TerraSAR-X spotlight mode data set over an apartment complex in Daejeon city, Korea. The final building heights were validated against reference heights extracted from LiDAR DSM, with an RMSE (Root Mean Square Error) of about 1~2m.

3D Building Modeling Using LIDAR Data and Digital Map (LIDAR 데이터와 수치지도를 이용한 3차원 건물모델링)

  • Kim, Heung-Sik;Chang, Hwi-Jeong;Cho, Woo-Sug
    • Journal of Korean Society for Geospatial Information Science
    • /
    • v.13 no.3 s.33
    • /
    • pp.25-32
    • /
    • 2005
  • This paper presents a method for point-based 3D building reconstruction using Lidar data and digital map. The proposed method consists of three processes: extraction of building roof points, identification of roof types, and 3D building reconstruction. After extracting points inside the polygon of building, the ground surface, wall and tree points among the extracted points are removed through the filtering process. The filtered points are then fitted into the flat plane using ODR(Orthogonal Distance Regression) in the first place. If the fitting error is within the predefined threshold, the surface is classified as a flat roof. Otherwise, the surface is fitted and classified into a gable or arch roof through RMSE analysis. Experimental results showed that the proposed method classified successfully three different types of roof and that the fusion of LIDAR data and digital map could be a feasible method of modeling 3D building reconstruction.

  • PDF

Update of Digital Map by using The Terrestrial LiDAR Data and Modified RANSAC (수정된 RANSAC 알고리즘과 지상라이다 데이터를 이용한 수치지도 건물레이어 갱신)

  • Kim, Sang Min;Jung, Jae Hoon;Lee, Jae Bin;Heo, Joon;Hong, Sung Chul;Cho, Hyoung Sig
    • Journal of Korean Society for Geospatial Information Science
    • /
    • v.22 no.4
    • /
    • pp.3-11
    • /
    • 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.

Automatic Extraction of Roof Components from LiDAR Data Based on Octree Segmentation (LiDAR 데이터를 이용한 옥트리 분할 기반의 지붕요소 자동추출)

  • Song, Nak-Hyeon;Cho, Hong-Beom;Cho, Woo-Sug;Shin, Sung-Woong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.25 no.4
    • /
    • pp.327-336
    • /
    • 2007
  • The 3D building modeling is one of crucial components in building 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes by stereoplotter compiler, which indeed take great amount of time and efforts. In addition, some automatic methods that were proposed in research papers and experimental trials have limitations of describing the details of buildings with lack of geometric accuracy. It is essential in automatic fashion that the boundary and shape of buildings should be drawn effortlessly by a sophisticated algorithm. In recent years, airborne LiDAR data representing earth surface in 3D has been utilized in many different fields. However, it is still in technical difficulties for clean and correct boundary extraction without human intervention. The usage of airborne LiDAR data will be much feasible to reconstruct the roof tops of buildings whose boundary lines could be taken out from existing digital maps. The paper proposed a method to reconstruct the roof tops of buildings using airborne LiDAR data with building boundary lines from digital map. The primary process is to perform octree-based segmentation to airborne LiDAR data recursively in 3D space till there are no more airborne LiDAR points to be segmented. Once the octree-based segmentation has been completed, each segmented patch is thereafter merged based on geometric spatial characteristics. The experimental results showed that the proposed method were capable of extracting various building roof components such as plane, gable, polyhedric and curved surface.

Building Boundary Extraction from Airborne LIDAR Data (항공 라이다자료를 이용한 건물경계추출에 관한 연구)

  • Lee, Suk Kun
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.28 no.6D
    • /
    • pp.923-929
    • /
    • 2008
  • Due to the increasing need for 3D spatial data, modeling of topography and artificial structures plays an important role in three-dimensional Urban Analysis. This study suggests a methodology for solving the problem of calculation for the extraction of building boundary, minimizing the user's intervention, and automatically extracting building boundary, using the LIDAR data. The methodology suggested in this study is characterized by combining the merits of the point-based process and the image-based process. The procedures for extracting building boundary are three steps: 1) LIDAR point data are interpolated to extract approximately building region. 2) LIDAR point data are triangulated in each individual building area. 3) Extracted boundary of each building is then simplified in consideration of its area, minimum length of building.The performance of the developed methodology is evaluated using real LIDAR data. Through the experiment, the extracted building boundaries are compared with digital map.

Assessment of Internal Pressure Fragility of Containment Buildings considering the Correlation of Structural Material Variables (구조재료 변수 상관관계를 고려한 격납건물의 내압취약도 평가)

  • Hahm, Dae-Gi;Kim, Jung-Han;Choi, In-Kil;Lee, Hong-Pyo
    • Proceedings of the Computational Structural Engineering Institute Conference
    • /
    • 2011.04a
    • /
    • pp.396-399
    • /
    • 2011
  • 격납건물의 내압취약도 평가를 위하여 격납건물 구조재료 변수 각각의 재료특성 시험 결과를 분석하여 현재상태 중앙값 및 변동계수 값을 추정하였다. 추정된 값은 최근의 가동중 검사 결과와 큰 차이를 보이지는 않는 것으로 나타났다. 또한 추출된 구조재료 변수들의 재조합을 통해 상관성을 배제시키는 방법을 적용함으로서, 변수 간의 상관성이 격납건물 취약도 평가에 미치는 영향을 기존의 방법과 대비하여 분석하였다. 본 예제의 경우에는 의도치 않은 변수간 상관성에 의해 2%가량 내압성능이 작게 평가되는 결과가 발생하는 것으로 나타났다. 일반적인 문제의 경우 구조재료 변수의 특성과 추출된 변수의 임의성에 의해 영향이 증폭될 수 있기 때문에, 보다 합리적인 내압취약도 평가를 위해서는 상관관계 영향을 고려하는 것이 바람직하다고 할 수 있다.

  • PDF

Housing Environment Type And Resident Housing Satisfaction (주거환경유형과 거주자의 주거만족)

  • 진양교;수와이드만;제임스앤더슨
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.19 no.1
    • /
    • pp.45-59
    • /
    • 1991
  • 본 연구에서는 객관적 환경지표와 그에 대한 인간의 주관적 반응간 의 인과적 관련도의 중요성이 강조된다. 좀 더 구체적으로, 거주자의 주관 적 반응인 주거만족과 객관적 환경지표의 하나인 주거환경유형들(건물유형 과 건물배치유형)과의 인과적 관련도가 본 연구에서 중점적으로 토의된다. 한국의 6개 대단위 공동주택단지가 본 연구의 대상지로 선정되었고, 표본 추출시 건물유형과 건물배치유형을 고려한 다단계 표집방법(multistage sampling)이 사용되었다. 설문면답방법(modified structured survey)에 의해 646명의 처리 가능한 응답이 수거되었다. 인과모형 검증의 첫 단계로서 다 수의 설문문항을 원래 관심있는 소수의 변수로 정선, 추출하기 위한 방법 으로 요인분석이 사용되었다. 요인분석으로부터 정선, 추출된 변수를 이용 해서 본 연구의 가설모형이 정립되고, 그 모형을 검증하기 위한 방법으로 경로분석이 사용되었다. 분석결과를 요약해 볼 때, 건물유형과 건물배치유 형 모두가 거주자의 지각, 인식, 태도 등의 적절한 매개변수들을 통해 거주 자의 주거만족에 유의한 영향을 미치는 것으로 나타났다. 건물유형은 일반 적으로 저층주거에서 고충주거로 바뀌면서, 거주자의 주거만족에 부정적인 영향을 미치고 있음이 확인되었고, 고층주거가 거주자에게 주는 시각적 단 조로움, 과밀감, 그리고 주차장을 포함한 옥외공간 이용상의 불편들과 또 그들로 인한 낮은 안전성 및 경관에 대한 불만족 등이 그 이유로서 밝혀졌 다. 건물배치유형의 경우, U자형의 배치유형이 선형배치유형에 비해 과밀 감 해소, 시각적 명료성 향상, 그리고 옥외공간 이용상의 편리 등 및 또 그 에 따른 경관에 대한 만족의 향상 때문에 거주자의 주거만족을 높이는 데 유리한 것으로 나타났다. 주거와 관련된 설계 및 계획분야를 위한 여러 다 양한 제안들이 본 연구에서 제시되고, 추후 관련 연구들을 위한 가능성들 도 토의되었다. 그 유용성 때문에, 아직 많은 이론적, 방법론적, 그리고 분 석상의 문제에도 불구하고, 객관적 환경지표들과 이용자들의 만족을 포함 한 다양한 주관적 변수들과의 관계를 경험적으로 밝히려는 시도가 계속되 어야 할 것으로 사료된다.

  • PDF