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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
  
  
  
  
  
  
  
  
  
60 
50 l-4———— ———— ——————————— ese: 
40 
30 i 4 
10 mA |o -., 
A | n i A E 
0 Fe y, uw À 
D C Le = Oo D — 
eue ea 5 RE m ux 
gv # $ o 2 = =; 
u = X LC 
m Typelerrors 4 Type llerrors 
Figure 8. Comparison of the reliability factors for the site 2. 
The errors Type-1 and Type-II are shown in % for 
each of the considered filtration algorithms 
4.3 The algorithm modification — intensity of the first and 
last reflection 
In our algorithm the filtration errors appeared in the first place 
on the forest fields.Therefore/a special effort was made to 
analyze some additional data collected during the laser 
scanning. The intensities of the first and the last returned 
impulses were compared for the area of the selected small test 
fields of the site 2. Also the spatial distance between those two 
impulses was calculated. It was noticed that for over 45% that 
distance was smaller than 0.5 m. (see Fig. 9). 
  
percent 
  
  
0 5 10 15 20 25 30 
distance 
Figure 9. Histogram of first-last impulse distances for forest 
area. 
Unfortunately, there was not discovered any precise correlation 
between the distance of the first-last impulse and the category 
of reflecting surface (bare earth or object). Only for the first-last 
impulse distance exceeding 15 m (Fig. 10)., we can with high 
probability assume, that the last impulse was really reflected by 
the bare earth. 
  
N 
we 
LL] bare earth. |] 
Bl object 
percent 
  
  
distance 
Figure 10. The relationship between the firs-last impulse 
distance, and the type of surface (bare earth, object) for forest 
area 
In the next step of our research, there was analyzed the 
relationship between the intensity of impulse reflection and the 
type of reflecting surface. It was expected that the surface type 
(object — trees or bare earth) can be recognized by the intensity 
of reflected impulse. In the investigated case the intensity value 
of returned pulses ranged from zero to 190 relative units (see 
Fig. 11). Only for the intensity value greater than 190 relative 
units (Fig. 11) the points reflecting the last impulse can be 
qualified, with a high probability, as a bare earth. 
[1 bare earth 
BH object 
  
T T T 
percent 
  
  
  
  
  
ü 1 m 1 0 1 fl L L 
0 50 100 150 200 20 300 350 400 450 500 
intensity 
Figure 11. The relationship between the last impulse intensity 
for the bare-earth and object reflecting surfaces for 
forest area. 
5. CONCLUSION 
In this paper a FFT based method of filtering of airborne laser 
scanner data has been presented. The method is directly derived 
from the signal processing theory. It is so, because we introduce 
the laser points location as an independent variable, and we 
treat the terrain and the terrain features represented in a discrete 
form (DEM), as a discrete signal that records the elevation 
variations for data points in a x- y location. 
The results from presented algorithm were compared with both 
reference data and with filtering results of eight methods 
reported to ISPRS test. Our experimental results reveal that 
quality of derived DTM is quite high. This algorithm allows for 
separation of the urbanized areas with high reliability. However 
filtering of forest areas has been the most difficult problem.