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International Archives of the Photogrammetry, Remote Sensin 
g and Spatial Information Sciences, Volume XXXIX-B4, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
! Width K | No. of Identification 
Sites (m) Del (m) | Levels Tana tolerance 
sampl11 2.1 0.6 | 1.6 7 0.4 0.5 
[samplik | 2.6 |06|40| 6 | 07 0.5 
samp12 0.9 0.6 | 2.0 7 0.7 0.5 
samp21 09 | 06} 20 7 0.7 0.5 
samp22 0.9 06] 20 7 0.7 0.5 
samp22k | 1.5 | 0.6 | 16 7 1.2 05 
samp23 09 | 06120 7 12 0.5 
samp24 09 1:06 :20 7 1.2 0.5 
samp3 1 09 | 06) 20 7 0.7 0.5 
samp41 09 | 06 | 20 7 1.8 0.5 
samp42 09 1:0.6 |. 2.0 7 0.7 0.5 
samp51 09 | 06 } 20 7 0.7 0.5 
sampSlk | 2.0 | 0.6 | 2.4 7 0.7 0.1 
samp52 09 | 06.20 7 0.7 0.5 
samp52k | 40 | 0.5 | 3.0 6 0.7 0.8 
samp53 09 .].0.6.1.2.0 7 0.7 0.5 
samp53k | 32 1.5 | 2.4 7 3.0 0.5 
samp54 27 102] 24 7 0.4 0.5 
samp61 09 {06 20 7 0.7 0.5 
samp71 09 (06 20 7 0.7 0.5 
  
  
  
  
  
City vs. Forest 
100% 
80% - 
0% 
  
  
# City: Sample 11-42 
# Forest: Sample 51-71 
  
  
  
  
  
  
  
  
  
  
Table 2. Parameters used in the proposed MTF method 
Since the 15 sample sites are divided into three groups, a 
comparison is shown in Figure 4. Group 2 sites shows the 
lowest errors and highest accuracy rate and kappa coefficient, 
which means that the MTF method can handle Group 1 sites 
better than the other two groups, this number is also good 
enough to compare with filters compared by ISPRS (Sithole and 
Vosselman, 2003). The performance of the MTF method on 
Group 2 is average. However, the performance on Group 3 
shows a very low Kappa coefficient because of the high Type II 
errors. Group 3 sites contain features like steep slope and high 
percentage of terrain points. Therefore, the MTF method 
probably has flaw on process this type of areas. 
p 
100% 
80% - 
30, 4— — 
  
Groups 
  
# Group 1: Sample 11, 
24, 41, 54 
8 Group 2: Sample 12, 
21,22 23,31, 42 
  
Group 3: Sample 51, 
52,53,61,71 
  
  
Figure 5. Average values of Type I, Type II errors, Accuracy 
and Kappa sorted by City Sites and Forest Sites 
The MTF is based on layering, which is a global analysis of the 
data height value. Therefore, the terrain points’ portion of all 
points can affect the result. Figure 6 demonstrates the MTF 
performance based on different terrain point percentage. It 
seems along with the growth of the percentage, the errors 
especially Type II error become higher, while the accuracy and 
kappa become lower. But it needs to be noticed that there is 
only one sample for the terrain point percentage smaller than 
40%, and the sample which have higher than 80% terrain points 
are all in the Group 3. Therefore, the uncertainty of this feature 
still requires further discussion. 
  
Terrain point percentage 
  
  
  
100% #< 40% : Samp42 
80% 
60% #40%-60%: Samp 
40% La 4154 
0 :: 0- o: »amp 
poss 21,22,24,51 
0% #> 80%: Samp 
kg P 52,53,61,71 
&° «S $ S 23,61, 
A sj m "S 
SS «S S 
v 
  
  
  
Figure 4. Average values of Type I, Type II errors, Accuracy 
and Kappa sorted by three groups 
The ISPRS dataset is originally sorted as city sites and forest 
Sites, the performance of the MTF method on city sites and 
forest site are shown in Figure 5. It is obvious that the 
performance on city site is better since it has lower Type I, Il 
errors and higher accuracy and kappa. The steep slope and the 
dense vegetation coverage might be the reason why the MTF 
method has an unsatisfactory result on forest sites. The forest 
Sites are basically overlapping with the Group 3 sites. The high 
Type II error is probably from the buildings on the slope which 
Is a difficulty mentioned by Sithole and Vosselman (2003). It is 
also the key to improve the value of the Kappa coefficient. 
Figure 6. Average values of Type I, Type II errors, Accuracy 
and Kappa sorted by percentage of terrain point 
In order to know which feature of the data has more influence to 
the result, the average standard deviations of the previous three 
types of sortation are calculated as shown in Figure 7. The chart 
shows that they are all in the same range of each characteristic; 
however, the group sortation has the lowest average standard 
deviation among the three types of sortation. 
  
  
Average Standard Deviations 
  
  
20% 
15% # Groups 
a | N & City/Forest 
0% el * Terrain percent 
  
  
  
  
Figure 7. Average values of Standard Deviations of Type I, 
Type II errors, Accuracy and Kappa in three types of sortation 
347