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 
Data acquisition was performed by using Leica's ALS60 sensor 
with WDM6S, mounted onboard a Cessna aircraft. WDM65 
records the complete waveform of the reflection from the 
surface intercepting the laser footprint. The full waveform data 
was collected as 256 samples (à) 1ns. Field of View (FOV) of 
the scanner was set at 28 degrees, scan rate was set at 33.7 Hz 
and laser pulse rate used was 54000 Hz. The data acquisition 
was conducted by flying the aircraft at an altitude of 2491 m 
from the mean sea level. The terrain height of the area varied 
from 439 m to 790 m. The average point density of the 
transmitted pulse was 1point/sq.m. 
A computer program was developed to generate georeferenced 
point data from the full waveform return pulses. The point 
cloud generation algorithm implemented in our approach is 
explained below with an illustration of a typical case. 
(1) Discrete return pulse (black square dot) and the 
corresponding waveform data for the laser pulse are depicted in 
Figure 2 (top). The blue dots in the top image in Figure 2 are 
full waveform data plotted against time. As seen in the figure, 
the full waveform data are generally embedded with noise 
generated from the variety of sources. Hence, a 12 order Finite- 
duration Impulse Response (FIR) zero-phase digital filter 
technique was applied to smooth the waveform and to reduce 
the noise for the further analysis. For a 12 order FIR fiiter 
(Figure 3), the output is a weighted sum of the current and a 
finite number of previous values of the input as described in 
equation 1. 
y(n) 2 x(n)x h(0) - x( n -1)x h(1) ---- x(n-12)x h(12) (1) 
The red curve in Figure 2 (top) is the smooth waveform data 
obtained after the processing. The smooth waveform obtained 
from this technique preserves peak position, pulse width and 
skew of the laser reflection (Wong and Antoniou, 1994). 
(2) After the waveform smoothening, the next step is to 
distinguish the noise from the actual return intensity. For that 
purpose, we selected a threshold and assumed all the reflection 
below the given threshold as noise and excluded those values 
for further processing. This is a very straight forward approach 
and computationally very efficient. Two threshold values of 
intensity 16 and 17 were tested. When the threshold was set at 
16, in some cases the points below ground level under the tree 
canopies were also generated. However with threshold 17, the 
last return peak of the waveform corresponds very well with the 
ground position level, under the tree canopies. Hence for the 
surveyed region, all the waveform return intensity below 17 
was assumed noise and considered their intensity to be 0. 
(3) In the third step, the number of peaks and the location of the 
peaks in the smooth waveform data were, at first, estimated by 
finding the local maxima in the smooth waveform. Then an 
algorithm based on the Expectation Maximization (EM) 
(Persson et.al., 2005) was applied to correct the positions and 
number of the peaks by Gaussian decomposition. The crosshair 
symbols at the peak of the Gaussian bumps in Figure 2 (top) are 
the corrected peak positions estimated by the EM algorithm. 
(4) Finally, the correctly estimated peak positions were 
georeferenced to create a point cloud data. 
506 
The bottom image in Figure 2 shows the discrete LIDAR pulses 
(green dots), obtained during September, overlaid on a 
Triangulated Irregular Network (TIN) of a bare ground 
constructed from the discrete LiDAR pulses obtained during 
December. The red dots in the image are the position data 
obtained by georeferencing the Gaussian peaks of the smooth 
waveform data, depicted by the cross hair symbols in the Figure 
2 (top image). From the figure it is clear that, for the particular 
laser pulse, the discrete return could record only one reflection 
from the top canopy layer however the proposed algorithm 
could detect 3 reflections of which the first one corresponds to 
the same discrete return and the last one corresponds to the 
ground level. 
  
Intensity 
  
145163" 185 205 225 
Time (ns) 
  
E Smooth Curve : Waveform data X GaussianPeak ® Discrete | 
  
  
Figure 2. Top: Discrete return pulse (black square dot), raw 
full waveform data (blue dots), smoothened waveform (red 
curve) and Gaussian peaks (crosshair symbols). Bottom: 
Discrete return pulses (green dots), full waveform return 
pulses (red dots) constructed from the Gaussian peaks 
depicted in the top image