• Title/Summary/Keyword: 수치표면모델

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SGM Performance Improvement of Stereo Satellite Image with Classified Image and Edge Image (분류영상과 에지영상을 이용한 입체 위성영상의 SGM 성능개선)

  • Lee, Hyoseong;Park, Byungwook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.6
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    • pp.655-661
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    • 2020
  • SGM (Semi Global Matching) can be used to find all the conjugate points between stereo images. Therefore, it enables high-density DSM (Digital Surface Model) production from high-resolution satellite images. However, water, shadows, and occlusion areas cause mismatching of the surrounding points in this method. Particularly, in buildings with large-parallax and elongated-shapes such as a Korean style apartment, it is difficult to reconstruct the 3D building even if the SGM method is applied to a high-resolution 50cm satellite image. This study proposed and performed the SGM technique with a classified image and an edge image from the IKONOS-2 satellite stereo-image with a 1m resolution to produce DSM. It was compared with the DSMs from the general SGM and the high-density ABM (Area Based Matching) matching of ERDAS software. The results of the apartment DSM by the proposed method were the best in the test area. As a result, despite the image having a resolution of 1m, the outline of the building DSM could be expressed more clearly than the existing method.

Normalized Digital Surface Model Extraction and Slope Parameter Determination through Region Growing of UAV Data (무인항공기 데이터의 영역 확장법 적용을 통한 정규수치표면모델 추출 및 경사도 파라미터 설정)

  • Yeom, Junho;Lee, Wonhee;Kim, Taeheon;Han, Youkyung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.6
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    • pp.499-506
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    • 2019
  • NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.

3D Road Modeling using LIDAR Data and a Digital Map (라이다데이터와 수치지도를 이용한 도로의 3차원 모델링)

  • Kim, Seong-Joon;Lee, Im-Pyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.2
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    • pp.165-173
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    • 2008
  • This study aims at generating automatically three dimensional geometric models of roads using LIDAR data and a digital map. The main processes in the proposed method are (1) generating a polygon encompassing a road region using a road layer from the digital map, (2) extracting LIDAR points within the road region using the polygon, (3) organizing the points into surface patches and grouping the patches into surface clusters, (4) searching the road surface clusters and generating the surface model from the points linked to the clusters, (5) refining the boundary using a digital map. By applying the proposed method to real data, we successfully generated the linear and surface information of the roads.

Numerical Simulation of Surface Tension-Dominant Multiphase Flows by Using Volume-Capturing Method and Unstructured Grid System (비정렬격자계와 체적포착법을 사용한 표면장력이 지배적인 다상유동 수치해석)

  • Myong, Hyon-Kook
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.35 no.7
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    • pp.723-733
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    • 2011
  • A numerical method of the CSF(Continuum Surface Force) model is presented for the calculation of the surface tension force and implemented in an in-house solution code(PowerCFD). The present method(code) employs an unstructured cell-centered method based on a conservative pressure-based finite-volume method with volume capturing method(CICSAM) in a volume of fluid(VOF) scheme for phase interface capturing. The application of the present method to a 2-D liquid drop problem is illustrated by an equilibrium and nonequilibrium oscillating drop calculation. It is found that the present method simulates efficiently and accurately surface tension-dominant multiphase flows.

Generating Raster DSM from Airborne Laser Scanned Data Using Parallel Processing and Virtual Grid (병렬처리와 가상격자를 이용한 대용량 항공 레이저 스캔 자료의 정규격자 수치표면모델 생성)

  • Han, Soo-Hee;Heo, Joon;Kim, Sung-Sam;Kim, Sung-Hoon
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2008.06a
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    • pp.318-321
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    • 2008
  • 본 연구에서는 대용량의 항공 레이저 스캔 포인트 자료로부터 정규 격자 형태의 수치 표면 모델을 고속으로 생성하기 위하여 가상격자와 병렬처리를 기반으로 한 자료 처리 기법을 제안하였다. 수십$\sim$수백 평방 킬로미터 영역에 대하여 항공 레이저 스캔을 중복적으로 수행할 경우 포인트 수는 수억$\sim$수십억에 이르며 이를 일반적인 시스템에서 처리하는 데에는 한계가 존재한다. 이에 본 연구에서는 병렬처리를 위해 구성한 피씨 클러스터 상에서 자료를 분산시켜 가상격자를 이용하여 처리하는 방식을 제안하였다. 즉, 마스터 노드는 포인트 자료를 읽어 들여 포인트의 평면 좌표 값에 따라 슬래이브 노드로 전송하고 각 슬래이브 노드에서는 전송받은 포인트를 가상 격자에 저장한 후 보간(interpolation)을 수행한다. 보간 방식으로는 IDW(Inverse Distance Weightin)을 사용하였으며 제안한 방식의 효율성을 평가하기 위하여 사용된 슬래이브 노드 수에 대한 처리 시간을 측정하였다.

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Semantic Classification of DSM Using Convolutional Neural Network Based Deep Learning (합성곱 신경망 기반의 딥러닝에 의한 수치표면모델의 객체분류)

  • Lee, Dae Geon;Cho, Eun Ji;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.6
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    • pp.435-444
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    • 2019
  • Recently, DL (Deep Learning) has been rapidly applied in various fields. In particular, classification and object recognition from images are major tasks in computer vision. Most of the DL utilizing imagery is primarily based on the CNN (Convolutional Neural Network) and improving performance of the DL model is main issue. While most CNNs are involve with images for training data, this paper aims to classify and recognize objects using DSM (Digital Surface Model), and slope and aspect information derived from the DSM instead of images. The DSM data sets used in the experiment were established by DGPF (German Society for Photogrammetry, Remote Sensing and Geoinformatics) and provided by ISPRS (International Society for Photogrammetry and Remote Sensing). The CNN-based SegNet model, that is evaluated as having excellent efficiency and performance, was used to train the data sets. In addition, this paper proposed a scheme for training data generation efficiently from the limited number of data. The results demonstrated DSM and derived data could be feasible for semantic classification with desirable accuracy using DL.

Development of Mean Stand Height Module Using Image-Based Point Cloud and FUSION S/W (영상 기반 3차원 점군과 FUSION S/W 기반의 임분고 분석 모듈 개발)

  • KIM, Kyoung-Min
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.4
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    • pp.169-185
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    • 2016
  • Recently mean stand height has been added as new attribute to forest type maps, but it is often too costly and time consuming to manually measure 9,100,000 points from countrywide stereo aerial photos. In addition, tree heights are frequently measured around tombs and forest edges, which are poor representations of the interior tree stand. This work proposes an estimation of mean stand height using an image-based point cloud, which was extracted from stereo aerial photo with FUSION S/W. Then, a digital terrain model was created by filtering the DSM point cloud and subtracting the DTM from DSM, resulting in nDSM, which represents object heights (buildings, trees, etc.). The RMSE was calculated to compare differences in tree heights between those observed and extracted from the nDSM. The resulting RMSE of average total plot height was 0.96 m. Individual tree heights of the whole study site area were extracted using the USDA Forest Service's FUSION S/W. Finally, mean stand height was produced by averaging individual tree heights in a stand polygon of the forest type map. In order to automate the mean stand height extraction using photogrammetric methods, a module was developed as an ArcGIS add-in toolbox.

Updating of Digital Map using Digital Image and LIDAR (디지털 영상과 LIDAR 자료를 이용한 수치지도 갱신)

  • Yun, Bu-Yeol;Hong, Jung-Soo
    • Journal of the Korean Geophysical Society
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    • v.9 no.2
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    • pp.87-97
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    • 2006
  • LIDAR(Light Detection and Ranging) is a new technology for obtaining DEM(Digital Elevation Model)ewith high density and high point acuracy. As LIDAR emerged, DEM could be developed in the earthsurface more efficiently and more economically, compared to the conventional aerial photogrametry.In this study, a digital camera is simultaneously used in combined LIDAR surveying, and acquired digitial image and DEM produce digital orthoimage. In this process, methods of combining sensor andorthoimage, GCPs determined by GPS surveying are used. Two digital orthoimage are produced; onewith a few GCP and the other without them. The produced maps can be used to corect or revised1:1,000 or 1:5,000 scale maps acordingly.

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NOVEL CNC GRINDING PROCESS CONTROL FOR NANOMETRIC SURFACE ROUGHNESS FOR ASPHERIC SPACE OPTICAL SURFACES (우주망원경용 비구면 반사경 표면조도 향상을 위한 진화형 수치제어 연삭공정 모델)

  • 한정열;김석환;김건희;김대욱;김주환
    • Journal of Astronomy and Space Sciences
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    • v.21 no.2
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    • pp.141-152
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    • 2004
  • Optics fabrication process for precision space optical parts includes bound abrasive grinding, loose abrasive lapping and polishing. The traditional bound abrasive grinding with bronze bond cupped diamond wheel leaves the machine marks of about $20{mu}m$ rms in height and the subsurface damage of about 1 ${mu}m$ rms in height to be removed by subsequent loose abrasive lapping. We explored an efficient quantitative control of precision CNC grinding. The machining parameters such as grain size, work-piece rotation speed and feed rate were altered while grinding the work-piece surfaces of 20-100 mm in diameter. The input grinding variables and the resulting surface quality data were used to build grinding prediction models using empirical and multi-variable regression analysis. The effectiveness of such grinding prediction models was then examined by running a series of precision CNC grinding operation with a set of controlled input variables and predicted output surface quality indicators. The experiment achieved the predictability down to ${pm}20$ nm in height and the surface roughness down to 36 nm in height. This study contributed to improvement of the process efficiency reaching directly the polishing and figuring process without the need for the loose abrasive lapping stage.

Numerical Simulation of Radar Backscattering from Oil Spills on Sea Surface for L-band SAR (기름이 유출된 바다 표면의 L-밴드 전파 산란에 대한 수치해석적 연구)

  • Park, Seong-Min;Yang, Chan-Su;Oh, Yi-Sok
    • Korean Journal of Remote Sensing
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    • v.26 no.1
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    • pp.21-27
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    • 2010
  • This paper presents a numerical simulation of the radar backscattering from oil spills on ocean surface. At first, a one-dimensionally rough sea surface is numerically generated for a given wind speed at HEBEI SPIRIT accident. Then, an oil-spilled sea surface is represented with a two-layered medium, which is generated by adding a thin low-dielectric oil layer on the randomly-rough highdielectric sea surface. The backscattering coefficients of various oil-spilled sea surfaces are obtained using the Method of Moments and Monte Carlo technique for various surface roughness, oil-layer thicknesses, frequencies, polarizations and incidence angles. The numerical method is verified with theoretical models for simple structures. The reduction of the backscattering coefficients due to the lowdielectric oil-layers on sea surfaces has been analyzed. These numerical results will help to detect any oil spills on sea surfaces, and consequently, to classify SAR images.