International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B1, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
  
y7 0.0352x- 1.7816 
d 
  
  
y7 0.0304x - 1.7895 
Figure 2. Basic idea of Chow-Test 
SSR2: residual sum of squares in range A 
SSR : residual sum of squares in whole range 
nl : number of data in range A 
n2 : number of data in range B 
k :number of explanatory variable 
Here, the following hypotheses are set. 
Null hypothesis HO 
: pavement condition of range A and range B is equal 
Alternative hypothesis H1 
: pavement condition of range A and range B is different 
F-value is computed by result of regression analysis and in the 
case that the hypothesis is rejected using a level of significance 
of 0.05, it is considered that that pavement of road is damaged. 
Also, the level of damage of surface condition is evaluated by 
F-value and the rate of the number of rejected points. 
4. CASE STUDY 
4.1 Outline of Case Study 
The evaluation model proposed in this research is applied for 
actual road pavement. 3D point clouds from MMS are measured 
and pavement condition is evaluated by Chow-test using 
collections of data for road pavement managed by local 
government. Furthermore, the results between Chow-test and 
existing method of pavement condition survey were compared 
and the validity of evaluation method proposed in this research 
was assessed. 
The target road for evaluation has length of 6km managed by 
local government and that road is semi- highway which had one 
lane for one direction. That road was constructed 30 years over 
ago and the damaged pavement sections were repaired by 
cutting overlay and replacement. Also, the road surface was dug 
up for construction, such as a gas pipe and burial of a sewer 
pipeline, and many marks of the construction were noticed 
88 
existing. The irregularity points of pavement are attributed to 
not only deterioration but marks of the construction. 
The pavement condition survey in Japan evaluates the condition 
by Maintenance Condition Index (MCI)) and integrates the 
evaluation result of cracking, rutting and IRI. This MCI varies 
in the range from 10 to 0. The larger value of MCI indicates that 
the condition is better. This case study compares the results 
between Chow-test using 3D point clouds and MCI. 
4.2 Result of analysis 
The results of Chow-test for arbitrary pavement section are 
shown in Figure 3 - Figure 5. These figures indicate F-value and 
coordinate value (XZ) of 3D point clouds. The horizontal axis 
shows the cross direction of road and the vertical axis shows the 
coordinate of Z and F-value. The section in Figure 3 has one 
point where is dented on surface and the F-value of that point 
shows large. In the case of Figure 4, the bump points are in 
some points on surface and F-values are also dispersed to 
horizontal direction. On the other hand, in the section in Figure 
5, there is one point which has extremely the large number of F- 
value. That means there is a localized damaged point. 
Figure 6 makes a comparison between MCI evaluated by 
pavement condition survey and the result by Chow-test. It is 
impossible to analyze the correlation directly between MCI and 
F-value due to difference of evaluation section range 
(evaluation length of pavement condition survey is 50m). For 
this reason, the whole tendency is represented by illustrating an 
evaluation result. 
The upper part of Figure 6 indicates the maximum of F-value 
and the lower part indicates the rate of points which has bump 
on surface. There is no clear relationship between the maximum 
of F-value and MCI because MCI represents the average 
condition of pavement section, not localized damaged point. On 
the other hand, in the lower figure which shows the relation 
between the rates of points, has bump on surface and MCI, the 
evaluation result of Chow-test is consistent with MCI. From the 
above results, it can be said that the methodology proposed in 
this study makes it possible to evaluate pavement conditions by 
considering not only macro (average) but micro (localized) 
level. This indicated the possibility to evaluate the localized 
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