• DocumentCode
    576500
  • Title

    The analysis on the accuracy of DEM retrieval by the ground lidar point cloud data extraction methods in mountain forest areas

  • Author

    Xiang, Haibing ; Cao, Chunxiang ; Jia, Huicong ; Xu, Min ; Myneni, Ranga B.

  • Author_Institution
    State Key Lab. of Remote Sensing Sci., Inst. of Remote Sensing Applic., Beijing, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    6067
  • Lastpage
    6070
  • Abstract
    LiDAR data contains the elevation and brightness information of land surface, vegetation cover and construction. Ground filtering and interpolation method are the key for extracting the DEM accuracy based on the point clouds. This paper takes Zhangye City, Gansu Province in western mountainous areas as the study area, based on the point clouds of 0.7 points/m2, uses 5 m * 5 m grid screening method and the lowest Thiessen polygon point screening method to extract the ground point. Ordinary kriging interpolation method was used to retrieve Digital Elevation Model (DEM). Referring to the elevations of 1466 sample points, we analysed the accuracy for extracting DEM by the two selected methods of extracting ground point. The results showed that the DEM extracting accuracy by the near lowest point screening method is better than the grid screening method.
  • Keywords
    digital elevation models; forestry; interpolation; optical radar; remote sensing by laser beam; statistical analysis; terrain mapping; vegetation mapping; China; DEM retrieval accuracy analysis; Gansu Province; Thiessen polygon point screening method; Zhangye City; digital elevation model; grid screening method; ground filtering method; ground lidar point cloud data extraction methods; ground point extraction method; kriging interpolation method; land surface brightness; land surface information; mountain forest areas; vegetation cover; western mountainous areas; Accuracy; Filtering; Filtering algorithms; Interpolation; Laser radar; Remote sensing; Vegetation mapping; Airborne LiDAR; Ground point; TIN; Thienssen; forest; mountain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6352223
  • Filename
    6352223