Volume XLI-B2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 715-720, 2016
https://doi.org/10.5194/isprs-archives-XLI-B2-715-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 715-720, 2016
https://doi.org/10.5194/isprs-archives-XLI-B2-715-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  09 Jun 2016

09 Jun 2016

ROAD NETWORK EXTRACTION FROM DSM BY MATHEMATICAL MORPHOLOGY AND REASONING

Yan Li1, Jianliang Wu1, Lin Zhu2, and Kikuo Tachibana2 Yan Li et al.
  • 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.