Full text: Technical Commission III (B3)

  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
2. For the road extraction, the thickness of the layer and 
layer's step size is very important. In order to get 
better result, we need a dynamic thickness and step 
size generation method. 
3. ACKNOWLEDGEWMENT 
Work described in this paper was funded by 973 Program 
(2011CB707102); National Natural Science Foundation of 
China (40901220, 41001302); Fok Ying Tong Education 
Foundation (122025). 
4. REFERENCES 
[1] Liang Gong, 2010.Automated Road Extraction from 
LiDAR Data Based on Intensity and Aerial Photo, Image and 
Signal Processing (CISP), 2010 3rd International Congress on 
pp. 2130 - 2133 
[2] Guofeng Wang, Yunling Zhang, 2011.3D Road 
Information Extraction from LiDAR Data Fused with 
Aerial-Images, Spatial Data Mining and Geographical 
Knowledge Services (ICSDM), 2011 IEEE International 
Conference on, pp. 362 - 366 
[3] Jong-Suk Yoon, Jung-Il Shin, 2008.ASSESSING THE 
POSSIBILITY OF LAND-COVER CLASSIFICATION 
USING LIDAR INTENSITY DATA, Geoscience and Remote 
Sensing Letters, IEEE, Volume: 5 Issue:4,pp. 801 - 805 
[4] Garland M., Heckbert P. S., 1997. Surface simplification 
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[5] Samadzadegan F., Hahn M.,2009. Automatic Road 
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[6]Garland M., Zhou Y., 2005. Quadric-based simplification 
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[7]Lee C. H., Varshney A., Jacobs D., 2005. Mesh saliency, 
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[8]Surazhsky V., Gotsman C. 2005. A qualitative comparison 
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SimpStudy-final.pdf (Preprint). 
[9]Wood, J. D., 1996. The geomorphological characterisation 
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[10]Simon C., Peter K., Franz R., 2004. The Automatic 
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South Wales, Australia, 
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[11]Farhad S.,Michael H.,behnaz B.,2009. Automatic Road 
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[12]Liang G., Yongsheng Z., Zhengguo L., 2010.Quanfu B. 
Automated Road Extraction from LiDAR Data Based on 
Intensity and Aerial Photo, International Congress on Image 
and Signal Processing 2010 3rd, pp.2130-2133. 
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