• DocumentCode
    2527567
  • Title

    Dense point cloud extraction from UAV captured images in forest area

  • Author

    Tao, Wang ; Lei, Yan ; Mooney, Peter

  • Author_Institution
    Beijing Key Lab. of Spatial Inf. Integration & Its Applic., Peking Univ., Beijing, China
  • fYear
    2011
  • fDate
    June 29 2011-July 1 2011
  • Firstpage
    389
  • Lastpage
    392
  • Abstract
    LIDAR (Light Detection And Ranging) is widely used in forestry applications to obtain information about tree density, composition, change, etc. An advantage of LIDAR is its ability to get this information in a 3D structure. However, the density of LIDAR data is low, the acquisition of LIDAR data is often very expensive, and it is difficult to be utilised in small areas. In this article we present an alternative to LIDAR by using a UAV (Unmanned Aerial Vehicle) to acquire high resolution images of the forest. Using the dense match method a dense point cloud can be generated. Our analysis shows that this method can provide a good alternative to using LIDAR in situations such as these.
  • Keywords
    forestry; geophysical signal processing; remotely operated vehicles; vegetation mapping; 3D information; UAV captured images; dense point cloud extraction; forest area; forest change; forest composition; forestry applications; high resolution forest images; lidar data acquisition; lidar data density; light detection and ranging; tree density; unmanned aerial vehicle; Cameras; Clouds; Computational modeling; Data models; Feature extraction; Laser radar; Three dimensional displays; Dense Match; Forest; Point Cloud; SFM; UAV;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on
  • Conference_Location
    Fuzhou
  • Print_ISBN
    978-1-4244-8352-5
  • Type

    conf

  • DOI
    10.1109/ICSDM.2011.5969071
  • Filename
    5969071