International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
From the visual analysis, we can see that the DTM constructed 
during winter from the discrete return pulses was very smooth. 
However, still there were some topographically complex areas 
where the ground penetration was not enough to create a 
smooth DTM (blue circle). The smooth DTM could be obtained 
even at those places by using full waveform return pulses. 
Naturally, the ground point detected from the full waveform 
return pulses obtained during winter created the smoothest and 
the most accurate DTM. 
4. CONCLUSION 
The results showed that the technique used for the full 
waveform exploitation has effectively increased the ground 
penetration by 50 % and 20%, respectively, during autumn and 
winter in the mixed forest hilly region compared to the discrete 
return pulses. 
The accuracy evaluation of LiDAR derived terrain data showed 
that, in the hilly regions, where the ground elevation changes 
considerably within a short horizontal distance, increase in 
ground point detection, due to the full waveform point cloud 
during autumn significantly improved the accuracy of DTM 
estimation. The results showed that, during leaf on condition, 
by implementing the proposed full waveform exploitation 
technique, better estimation of bio mass together with accurate 
DTM generation could be achieved concurrently compared to 
the discrete LiDAR pulses. 
During winter, when the deciduous trees shed their leaves, the 
vertical accuracy of DTM constructed from discrete LIDAR and 
full waveform LiDAR was very similar. However, still there 
were some topographically complex areas where the ground 
penetration due to discrete LIDAR pulses alone was not enough 
to create a smooth DTM. Still at those places, smoother DTM 
was obtained by using full waveform return pulses. 
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Acknowledgements 
The authors would like to thank Japan forestry agency's digital 
forest information development project for supporting this 
research.