The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Voi. XXXVII. Part BI. Beijing 2008 
One should note that the presented strip adjustment procedure 
mainly aims at improving the alignment between the strips and 
this does not necessarily mean improving the alignment of the 
adjusted strips relative to the ground coordinate system. In other 
words, one of the strips is chosen to be as a reference strip and 
the remaining strips are aligned relative to that strip, which is 
not bias free. 
5. CONCLUSIONS 
The direct acquisition of a high density and accurate 3D point 
cloud has made LiDAR systems the preferred technology for 
the generation of topographic data to satisfy the needs of 
several applications (e.g., digital surface model creation, digital 
terrain model generation, orthophoto production, 3D city 
modeling, and forest mapping). The non-transparent and 
sometimes empirical calibration procedures, however, might 
lead to consistent discrepancies between conjugate surface 
elements in overlapping strips. This paper presented a 
procedure to improve the compatibility among overlapping 
strips. First, the impact of systematic errors in the bore-sighting 
parameters on the derived point cloud was investigated. Then, a 
semi-automated approach for the extraction and matching of 
conjugate linear features in overlapping strips was introduced. 
The extracted linear features are represented by a set of non 
conjugate points. The established transformation function and 
the matched primitives were used to estimate the necessary 
transformation parameters for the best co-alignment of the 
LiDAR strips. The non-correspondence of the selected points 
along the linear features is compensated for by artificially 
expanding their variance-covariance matrices along the line 
direction. Other than the co-alignment of overlapping strips, the 
developed procedure can be used to infer the presence of 
systematic errors in the data acquisition system. For an 
accurately calibrated LiDAR system, no shifts and rotations are 
needed to improve the compatibility of overlapping strips. 
Deviations from zero shifts and rotation can be used for the 
quality control the LiDAR system and derived data. 
The performance of the proposed procedure was evaluated 
using real dataset. The experimental results revealed that the 
strip adjustment would improve the strips’ compatibility and as 
a consequence the further processing of the data such as 
filtering and segmentation. In conclusion, one should note that 
the best way to improve the compatibility among overlapping 
strips is by implementing a rigorous calibration procedure. 
Future research will focus on relating the detected discrepancies 
between overlapping strips to the system biases. Moreover, we 
will be using the estimated transformation parameters to 
remove the bias effect from the point cloud. 
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ACKNOWLEDGEMENT 
We would like to thank the GEOIDE (GEOmatics for Informed 
DEcisions) Network of Centers of Excellence of Canada for 
their partial financial support of this research (SII#43). The 
authors are also indebted to the LACTEC - Institute of 
Technology for the Development - for providing the LIDAR 
data and the valuable feedback. 
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