The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
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Figure 10 Relation between RRMS and standard deviation of 
RRMS of impervious surface area and the imperviousness 
factor combined into 10 groups, PAN 
Figure 11 Relation between RRMS and standard deviation of 
RRMS of impervious surface area and the imperviousness 
factor combined into 10 groups, RGB 
6. CONCLUSIONS 
According measurements experiment and statistical analysis the 
following conclusions could be drawn out: 
1. Accuracy of manual photointerpretation of panchromatic 
IKONOS was describe by: 
mean relative area error (RRMS): 22%, 
average bias: 16%, 
mean reproducibility: 13%. 
2. Accuracy of manual photointerpretation of IKONOS 
PANSHARP was describe by: 
mean relative area error (RRMS): 13%, 
mean bias: 3%, 
mean reproducibility: 9%. 
In our experiment, panchromatic IKONOS allowed for the 
impervious surface interpretation with less accuracy in compare 
to the colour IKONOS PAN-SHARP. 
Accuracy of photointerpretation influences on the value of 
imperviousness factor, calculated in 30m grid and later on 
applying it, as a reference in Landsat classification. In our 
experiment, we obtained also less accuracy for panchromatic 
image than for colour one: 
PAN - mean RMS of imperviousness factor: 18%, 
mean bias: -10%, 
RGB - mean RMS of imperviousness factor: 12%, 
mean bias: -4%. 
Accuracy obtained from IKONOS RGB is comparable to the 
results published by Deguchi and Sugio (1994). Results from 
panchromatic images were significant worse then obtained from 
the colour images. Some explanation might be the spectral 
range of panchromatic channel of IKONOS covering also infra 
red, vegetations on the PAN image is bright and might be 
misrecognised as a bright concrete cover (or against). Generally, 
colour image contains more information useful for impervious 
surface recognition. 
ACKNOWLEDGMENTS 
This research was done in frame of the project “Multitemporal 
remote sensing imagery based evaluation of spatial changes of 
land-use and landscape functions for landscape planning 
activities support”; (N526029 32/2621) financed by the Polish 
Ministry of Science and Higher Education. 
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