The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B3h. Beijing 2008 
583 
methodology is to provide an automatic way to construct spatial 
road network which can compatible with both FCD and multi 
spectral imagery. 
In conclusion, FCD can help to construct spatial road network 
with multi spectral remote sensing imagery. The short cycle 
period and wide coverage of multi spectral remote sensing 
imagery make the update of spatial road network more rapidly 
and the cost of update less, which is vital to build the intelligent 
transportation system. Especially in urban areas where spatial 
road network is changing rapidly over time and the traffic 
situation is always complicated, this methodology can offer an 
automatic way to maintain the spatial road network database. In 
the future work, the convenient way to get the pre-processed 
imagery will be studied and the robustness of this methodology 
will be analyzed. 
ACKNOWLEDGEMENTS 
The work described in this paper was supported by National 
Natural Science Foundation of China (Project No.40501061) 
and Hi-tech Research and Development Program of China 
(Project No. 2007AA12Z178). The author would like to thank 
the data provided by SUTSS (Shenzhen Urban Transport 
Simulation System) project in China. The author would like to 
thank Prof. C. Liu from Tongji University of China for his 
comment and suggestion which helped to improve this paper. 
REFERENCES 
Anselin, L., 1995, Local Indicators of Spatial Association — 
LISA. Geographical Analysis 27: 93-115. 
Dal Poz, A.P., Zanin, R.B., do Vale, G.M., 2006, Automated 
extraction of road network from medium- and high-resolution 
images, Pattern Recognition and Image Analysis, v 16, n 2, 
April-June 2006, p 239-48 
David HA., 1956, On the application of statistics to an 
elementarytheorem in probability. Biometrica 43:85-91 
Fan Y.M, Liu C., 2006, Computation and Matching of Road 
Segment Velocity With Floating Car Data Based on Road 
Network, The 14th International Conference on 
GEOINFORMATICS, 2006, Proceedings of SPIE - The 
International Society for Optical Engineering, v 6418, 
Geoinformatics 2006: GNSS and Integrated Geospatial 
Applications, 2006, p 641811 
Fan Y.M., 2007, Computation of spatial road network and 
transportation information publication based on WebGIS and 
Floating Car Data, Tongji University Press, 2007 
Fouladvand, M.E., Darooneh, A.H., 2005, Statistical analysis of 
floating-car data: An empirical study, European Physical 
Journal B, v 47, n 2, September, 2005, p 319-328 
Getis, A., Ord, JK., 1996, Local Spatial Statistics: An 
Overview. In: Longley P, Batty M. , editors. Spatial analysis: 
modeling in a GIS environment. Geoinformation International', 
Cambridge: 1996. pp. 261-277. 
Kemer, Boris, Prof. Dr., Rehbom, Hubert, Dr., 2001, Method to 
determine the traffic situation in a road network Assignee: 
DaimlerChrysler AG Publication Number: EP1154389 
Publication date: 11/14/2001 Kind: APPLICATION WITH 
SEARCH REPORT 
Kemer, B.S., Demir, C., Herrtwich, R.G., Klenov, S.L., 
Rehbom, H., Aleksic, M., Haug, A., 2005, Traffic state 
detection with floating car data in road networks, IEEE 
Conference on Intelligent Transportation Systems, Proceedings, 
ITSC, v 2005, ITSC'05: 2005 IEEE Intelligent Conference on 
Transportation Systems, Proceedings, 2005, p 700-705 
Kwella, B., Lehmann, H., 2000, Floating car data analysis of 
urban road networks, Computer Aided Systems Theory - 
EUROCAST’99. Selection of Papers from the 7th International 
Workshop on Computer Aided Systems Theory. Proceedings 
(Lecture Notes in Computer Science Vol. 1798), 2000, p 357-67 
Moran, P.A.P., 1950, Notes on continuous stochastic 
phenomena, Biometrika 37, 1950 , pp. 17-23. 
Peteri, R., Celle, J., Ranchin, T., 2003, Detection and extraction 
of road networks from high resolution satellite images, 
Proceedings 2003 International Conference on Image 
Processing (Cat. No.03CH37429), 2003, p 1-301-4 vol.l 
Schafer, R.-P., Strauch, D., Kelpin, R., 2001, A floating-car 
data detection approach of traffic congestions, Modelling and 
Simulation 2001. 15th European Simulation Multiconference 
2001. ESM'2001, 2001, p 958-60 
Shackelford, A.K., Davis, C.H., 2003, Urban road network 
extraction from high-resolution multispectral data, 2nd 
GRSS/ISPRS Joint Workshop on Remote Sensing and Data 
Fusion over Urban Areas. URBAN 2003 (Cat. No.03EX646), 
2003,p 142-6 
Skourikhine, Alexei N., 2005, Road network extraction from 
digital imagery, Proceedings of SPIE - The International 
Society for Optical Engineering, v 5916, Mathematical Methods 
in Pattern and Image Analysis, 2005, p 1-9 
Smartt, Brian E., 2006, Methods and systems for deducing road 
geometry and connectivity, Assignee: CircumNav Networks, 
Inc. Publication Number: US20060155464 Publication date: 
07/13/2006 Kind: Utility Patent Application 
Turksma S., 2000, The Various Uses of Floating Car Data, 
Road Transport Information and Control, Conference 
Publication No.472. 
Zhu, C., Shi, W., Pesaresi, M., Liu, L., Chen, X., King, B., 
2005, The recognition of road network from high-resolution 
satellite remotely sensed data using image morphological 
characteristics, International Journal of Remote Sensing, v 26, n 
24, Dec 1, 2005, p 5493-5508