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
fDate :
June 29 2011-July 1 2011
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;
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
DOI :
10.1109/ICSDM.2011.5969071