• Title/Summary/Keyword: Digital Surface Model

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Development of Digital Surface Model and Feature Extraction by Integrating Laser Scanner and CCD sensor

  • Nagai, Masahiko;Shibasaki, Ryosuke;Zhao, Huijing;Manandhar, Dinesh
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.859-861
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    • 2003
  • In order to present a space in details, it is indispensable to acquire 3D shape and texture simultaneously from the same platform. 3D shape is acquired by Laser Scanner as point cloud data, and texture is acquired by CCD sensor. Positioning data is acquired by IMU (Inertial Measurement Unit). All the sensors and equipments are assembled on a hand-trolley. In this research, a method of integrating the 3D shape and texture for automated construction of Digital Surface Model is developed. This Digital Surface Model is applied for efficient feature extraction. More detailed extraction is possible , because 3D Digital Surface Model has both 3D shape and texture information.

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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.

Construction of 3D Geospatial Information for Development and Safety Management of Open-pit Mine (노천광산 개발 및 안전관리를 위한 3차원 지형정보 구축 및 정확도 분석)

  • Park, Joon Kyu;Jung, Kap Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.1
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    • pp.43-48
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    • 2020
  • Open pit mines for limestone mining require rapid development of technologies and efforts to prevent safety accidents due to rapid deterioration of the slope due to deforestation and rapid changes in the topography. Accurate three-dimensional spatial information on the terrain should be the basis for reducing environmental degradation and safe development of open pit mines. Therefore, this study constructed spatial information about open pit mine using UAV(Unmanned Aerial Vehicle) and analyzed its utility. images and 3D laser scan data were acquired using UAV, and digital surface model, digital elevation model and ortho image were generated through data processing. DSM(Digital Surface Model) and ortho image were constructed using image obtained from UAV. Trees were removed using 3D laser scan data and numerical elevation models were produced. As a result of the accuracy analysis compared with the check points, the accuracy of the digital surface model and the digital elevation model was about 11cm and 8cm, respectively. The use of three-dimensional geospatial information in the mineral resource development field will greatly contribute to effective mine management and prevention of safety accidents.

DSM GENERATION FROM IKONOS STEREO IMAGERY

  • Rau, Jiann-Yeou;Chen, Liang-Chien;Chang, Chih-Li
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.57-59
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    • 2003
  • Digital surface model generation from IKONOS stereo imagery is a new challenge in photogrammetric community, especially when the satellite company does not provide the raw data as well as their ancillary ephemeris data. In this paper we utilized an estimated relief displacement azimuth and the nominal collection elevation data included in the metadata file to correct the relief displacement of GCPs, together with a linear transformation for geometric modeling of IKONOS imagery. Space intersection is performed by the trigonometric intersection assuming a parallel projection of IKONOS imagery due to its small FOV and frame size. In the experiment, less than 2-meters of RMSE in orbit modeling is achieved denoting the potential positioning accuracy of the IKONOS stereo imagery.

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3D Surface Model Generation of Micro Structure by Self Calibration of The SEM Image (SEM 영상의 자체검정에 의한 미세구조물의 3차원 표면모델 생성)

  • 이효성;박형동
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2003.04a
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    • pp.151-159
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    • 2003
  • This study presents method for self-calibration of the SEM(Scanning Electron Microscope) stereo image using the standard microprobe with same grid pattern and using parallel and central perspective projection equation. Result showed that parallel projection method is more suitable for standard microprobe. The maximum error of 3D coordinates acquired by this method did not exceed 5 $\mu\textrm{m}$, and DSM(Digital Surface Model) for three dimensional measurement of the rock sample was generated by the digital photogrammetry. This result can be used for quantification of micro scale change of shape and analysis of the micro morphology of rock due to weathering.

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Quality Assessment of Digital Surface Model Vertical Position Accuracies by Ground Control Point Location (지상기준점 선점 위치에 따른 DSM 높이 정확도 분석)

  • Lee, Jong Phil
    • Journal of Cadastre & Land InformatiX
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    • v.51 no.1
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    • pp.125-136
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    • 2021
  • Recently, Unmanned Aerial Vehicle utilization and image processing technology for remote sensing have diversified remarkably with Orthophoto and Digital Surface Model. In particular, It uses more application fields such as spatial information analysis and hazardous areas as well as land surveying. This study analyses the accuracy of the coordinate on Orthophoto and DSM height on slope area with high and low differences by using UAV images. As the result of this study, in the case of GCP on 2D orthophoto, the location error was not produced significantly. The vertical position of the DSM showed the highest accuracy when the height difference between GCPs is under 30m(RMSEZ=0.07m). The location of the GCPs was divided into approximately 10m, 20m, 30m, and 40m with analysis for each of the eight points of GCP and inspection points in general. This study expects that producing both horizontal accuracy of Orthophoto and vertical accuracy of DSM using UAV on the sloped area which similar to this research area will help in spatial information fields.

Extraction of 3D Objects Around Roads Using MMS LiDAR Data (MMS LiDAR 자료를 이용한 도로 주변 3차원 객체 추출)

  • CHOUNG, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.1
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    • pp.152-161
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    • 2017
  • Making precise 3D maps using Mobile Mapping System (MMS) sensors are essential for the development of self-driving cars. This paper conducts research on the extraction of 3D objects around the roads using the point cloud acquired by the MMS Light Detection and Ranging (LiDAR) sensor through the following steps. First, the digital surface model (DSM) is generated using MMS LiDAR data, and then the slope map is generated from the DSM. Next, the 3D objects around the roads are identified using the slope information. Finally, 97% of the 3D objects around the roads are extracted using the morphological filtering technique. This research contributes a plan for the application of automated driving technology by extracting the 3D objects around the roads using spatial information data acquired by the MMS sensor.

Utilization Evaluation of Digital Surface Model by UAV for Reconnaissance Survey of Construction Project (건설공사 현황측량을 위한 UAV DSM의 활용성 평가)

  • Park, Joon-Kyu;Um, Dae-Yong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.3
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    • pp.155-160
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    • 2018
  • The unmanned aerial vehicle (UAV) is used in various fields, such as land surveying, facility management, and disaster monitoring and restoration because it has low operational costs, fast data acquisition, and can generate a digital surface model (DSM). Recently, the UAV has been applied to process management in construction projects. Construction projects are widely distributed not only in urban areas but also in mountainous areas and rural areas where people are rarely in traffic or in vehicles. Projects range from a few hundred meters to several kilometers long. In order to perform a reconnaissance survey, a surveying method using a global positioning system (GPS) or a total station has mainly been used. However, these methods have a disadvantage in that a lot of time is required for data acquisition. This study's purpose is to evaluate the usability of a UAV DSM for surveying a construction area. Data was acquired using the UAV and a three-dimensional (3D) laser scanner, and the DSM of the construction site was created through data processing. The UAV DSM showed accuracy to within 30 cm based on the 3D laser scanner data, and a process comparison between the two work methods was able to present the usability of the UAV DSM in the field of construction surveying. Future utilization of the UAV DSM is expected to greatly improve the efficiency of work in construction projects.

Three-Dimensional Positional Accuracy Analysis of UAV Imagery Using Ground Control Points Acquired from Multisource Geospatial Data (다종 공간정보로부터 취득한 지상기준점을 활용한 UAV 영상의 3차원 위치 정확도 비교 분석)

  • Park, Soyeon;Choi, Yoonjo;Bae, Junsu;Hong, Seunghwan;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
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    • v.36 no.5_3
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    • pp.1013-1025
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    • 2020
  • Unmanned Aerial Vehicle (UAV) platform is being widely used in disaster monitoring and smart city, having the advantage of being able to quickly acquire images in small areas at a low cost. Ground Control Points (GCPs) for positioning UAV images are essential to acquire cm-level accuracy when producing UAV-based orthoimages and Digital Surface Model (DSM). However, the on-site acquisition of GCPs takes considerable manpower and time. This research aims to provide an efficient and accurate way to replace the on-site GNSS surveying with three different sources of geospatial data. The three geospatial data used in this study is as follows; 1) 25 cm aerial orthoimages, and Digital Elevation Model (DEM) based on 1:1000 digital topographic map, 2) point cloud data acquired by Mobile Mapping System (MMS), and 3) hybrid point cloud data created by merging MMS data with UAV data. For each dataset a three-dimensional positional accuracy analysis of UAV-based orthoimage and DSM was performed by comparing differences in three-dimensional coordinates of independent check point obtained with those of the RTK-GNSS survey. The result shows the third case, in which MMS data and UAV data combined, to be the most accurate, showing an RMSE accuracy of 8.9 cm in horizontal and 24.5 cm in vertical, respectively. In addition, it has been shown that the distribution of geospatial GCPs has more sensitive on the vertical accuracy than on horizontal accuracy.

Land cover classification using LiDAR intensity data and neural network

  • Minh, Nguyen Quang;Hien, La Phu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.4
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    • pp.429-438
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    • 2011
  • LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.