International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W10
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 1127–1134, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-1127-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 1127–1134, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-1127-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  08 Feb 2020

08 Feb 2020

VECTOR AND RASTER DATA LAYERED FUSION AND 3D VISUALIZATION

Y. S. Huang1, G. Q. Zhou1, T. Yue1, H. B. Yan1, W. X. Zhang1, X. Bao1, Q. Y. Pan1, and J. S. Ni2 Y. S. Huang et al.
  • 1Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi 541004, China
  • 2Spatial Data Service Center ,China Aerospace Science and Industry Corporation, No.8 Fucheng Road, Haidian District , Beijing 100048, China

Keywords: Partial Fusion,Vector Raster Fusion,Morton Code, Oracle Database, Data Organization, 3D Visualization

Abstract. Although contemporary geospatial science has made great progress, spatial data fusion of vector and raster data is still a problem in the geoinformation science environment. In order to solve the problem, this paper proposes a method which merges vector and raster data. Firstly, the row and column numbers of the raster data, and the X, Y values of the vector data are represented by Morton code in the C++ environment, respectively. Secondly, we establish the the raster data table and the vector data table in the Oracle database to store the vector data and the raster data. Third, this paper uses the minimum selection bounding box method to extract the top data of the building model. Finally, we divide the vector and raster data into four steps to obtain the fusion data table, and we call the fusion data in the database for 3D visualization. This method compresses the size of data of the original data, and simultaneously divides the data into three levels, which not only solves the problem of data duplication storage and unorganized storage, but also can realize vector data storage and the raster data storage in the same database at the same time. Thus, the fusion original orthophoto data contains the gray values of building roofs and the elevation data, which can improve the availability of vector data and the raster data in the 3D Visualization application.