Title : 
Research on different slicing methods of acquiring LAI from terrestrial laser scanner data
         
        
            Author : 
Zhu, Zhen ; Zhang, Wuming ; Zhu, Ling ; Zhao, Jing
         
        
            Author_Institution : 
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
         
        
        
            fDate : 
June 29 2011-July 1 2011
         
        
        
        
            Abstract : 
It has been possible to acquire precise point clouds of surface features using terrestrial laser technology. And it has been a research hot spot to figure up the LAI of a single tree combined point clouds of the tree with gap fraction model. While calculating the LAI using gap fraction model, it is a general procedure to slice the acquired point clouds. Zenith slicing and vertical height slicing are two ways often used for this purpose. We used the point clouds of a single tree with gap fraction model to determine which slicing method is better to compute the LAI, and found: (1) the results of LAI are closely related with the different slicing methods and slicing thickness; (2) the results of LAI apparently deviate from the ground truth when the slicing thickness is very big or very small; (3) the results of LAI are closer to the LAI of field measurements while the slicing thickness is smaller within the appropriate slicing range; (4) within the appropriate slicing range, the vertical height slicing is better than the zenith slicing.
         
        
            Keywords : 
data acquisition; remote sensing by laser beam; vegetation; LAI; gap fraction model; precise point clouds; slicing methods; slicing thickness; surface features; terrestrial laser scanner data; tree; vertical height slicing; zenith slicing; Area measurement; Clouds; Laser modes; Measurement by laser beam; Remote sensing; Shape; Vegetation; Gap fraction model; LAI; point clouds; slicing methods; terrestrial laser scanner;
         
        
        
        
            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.2011.5969050