Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 715-720, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/715/2016/
doi:10.5194/isprs-archives-XLI-B2-715-2016
 
09 Jun 2016
ROAD NETWORK EXTRACTION FROM DSM BY MATHEMATICAL MORPHOLOGY AND REASONING
Yan Li1, Jianliang Wu1, Lin Zhu2, and Kikuo Tachibana2 1International Institute for Earth System Science, Nanjing University, China
2Research & Development HQ, PASCO Corporation, Japan
Keywords: Road extraction, Digital Surface Model, Morphology Abstract. The objective of this research is the automatic extraction of the road network in a scene of the urban area from a high resolution digital surface model (DSM). Automatic road extraction and modeling from remote sensed data has been studied for more than one decade. The methods vary greatly due to the differences of data types, regions, resolutions et al. An advanced automatic road network extraction scheme is proposed to address the issues of tedium steps on segmentation, recognition and grouping. It is on the basis of a geometric road model which describes a multiple-level structure. The 0-dimension element is intersection. The 1-dimension elements are central line and side. The 2-dimension element is plane, which is generated from the 1-dimension elements. The key feature of the presented approach is the cross validation for the three road elements which goes through the entire procedure of their extraction. The advantage of our model and method is that linear elements of the road can be derived directly, without any complex, non-robust connection hypothesis. An example of Japanese scene is presented to display the procedure and the performance of the approach.
Conference paper (PDF, 1599 KB)


Citation: Li, Y., Wu, J., Zhu, L., and Tachibana, K.: ROAD NETWORK EXTRACTION FROM DSM BY MATHEMATICAL MORPHOLOGY AND REASONING, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 715-720, doi:10.5194/isprs-archives-XLI-B2-715-2016, 2016.

BibTeX EndNote Reference Manager XML