Title :
Reflectance modelling using terrestrial LiDAR intensity data
Author :
Angus F. C. Errington;Brian L. F. Daku;Arnfinn F. Prugger
Author_Institution :
Dept. of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A9
Abstract :
With the increasing use of Terrestrial Laser Scanners (TLSs) to sense various environments it becomes increasingly necessary to develop automated processing techniques to deal with the large amount of data generated. To aid in the automatic processing, researchers have recently been turning to the use of “intensity” data returned by TLSs as an additional source of information. Ideally a value that is independent of distance and incidence angle, and that instead is related to the surface properties being scanned is desired. For diffuse surfaces this value is termed the reflectance. A method for modelling the reflectance of a diffuse surface using returned intensity, angle of incidence and range obtained from TLSs is presented. The model is applied to two different TLS instruments, a Faro Focus3D and Riegl VZ-400. A model is parametrized for each instrument using data obtained in an underground potash mine. For the Riegl instrument the model is verified using a data set obtained above ground, in a grass playing field. The standard deviation of error is 0.064 or 6.4%. For the Faro instrument the model is obtained using only a subset of the acquired data set and verified with the remainder. The standard deviation for the Faro model is 0.061 or 6.1%.
Keywords :
"Mathematical model","Data models","Atmospheric modeling","Instruments","Laser radar","Standards","Data mining"
Conference_Titel :
Imaging Systems and Techniques (IST), 2015 IEEE International Conference on
DOI :
10.1109/IST.2015.7294464