ASSESSMENT OF SENSOR CHARACTERISTICS OF AN AIRBORNE LASER SCANNER USING GEOMETRIC REFERENCE TARGETS

In order to get an experimental insight on the characteristics of a modern airborne laser scanning system, we carry out a set of experiments using geometrical targets on an air strip and use different flying heights. Sensor noise and relative accuracy is evaluated through 4 cardboard tables, being plain and homogeneously reflecting. The standard deviation of all laser returns from such a target decreases with lower flying altitude, as well as positional offsets computed tend to increase with flying altitude. The positional error along track is smaller than across track, probably due to different point spacing in these two directions. Target size and reflectance effects are assessed using wooden slats of different widths and colors. The effect of reflectance on target visibility is much larger than the effect of target size, which is in agreement to theoretical findings. Effective footprint size is attempted to be determined by slats with high reflectance forming a star. The difference between geometric (computed only by beam divergence) and effective footprint size increases with measurement distance, with the effective diameter being smaller than the geometric one.

[1]  Guoqing Sun,et al.  Modeling lidar returns from forest canopies , 2000, IEEE Trans. Geosci. Remote. Sens..

[2]  C. Brenner,et al.  ISPRS 2005 : Vol. XXXVI Comm. 3 W19 proceedings of the ISPRS workshop laser scanning 2005, 12 - 15 September, Enschede ITC, The Netherlands , 2005 .

[3]  K. Itten,et al.  LIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management , 2004 .

[4]  Claus Brenner,et al.  Extraction of buildings and trees in urban environments , 1999 .

[5]  Aloysius Wehr,et al.  Airborne laser scanning—an introduction and overview , 1999 .

[6]  K. Kraus,et al.  Determination of terrain models in wooded areas with airborne laser scanner data , 1998 .

[7]  C. Brenner Building reconstruction from images and laser scanning , 2005 .

[8]  P. Reiss,et al.  Laser scanning—surveying and mapping agencies are using a new technique for the derivation of digital terrain models , 1999 .

[9]  W. Cohen,et al.  Lidar Remote Sensing for Ecosystem Studies , 2002 .

[10]  Emmanuel P. Baltsavias,et al.  Airborne laser scanning: basic relations and formulas , 1999 .

[11]  E. Næsset Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data , 2002 .

[12]  R. Hill,et al.  Quantifying canopy height underestimation by laser pulse penetration in small-footprint airborne laser scanning data , 2003 .

[13]  Mikko Inkinen,et al.  A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners , 2001, IEEE Trans. Geosci. Remote. Sens..

[14]  Wenge Ni-Meister,et al.  Modeling lidar waveforms in heterogeneous and discrete canopies , 2001, IEEE Trans. Geosci. Remote. Sens..

[15]  M. Roggero Airborne laser scanning: clustering in raw data , 2001 .