Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 683–686, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-683-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 683–686, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-683-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  18 Oct 2019

18 Oct 2019

IMPACT OF GAP FILLING ON QUALITY OF ROAD NETWORKS

M. Maboudi1, J. Amini2, and M. Gerke1 M. Maboudi et al.
  • 1Institute of Geodesy and Photogrammetry, Technische Universität Braunschweig, Germany
  • 2School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran

Keywords: Road network, Gap filling, Topology, Quality assessment, Tensor voting

Abstract. High quality and updated road network maps provide important information for many domains. Many small segments appear on the road surface in VHR images. Most road extraction systems have problem in extraction of these small segments and usually they appear as gaps in the final extracted road networks. However, most approaches skip filling these gaps. This is on account of the fact that usually overall length of the missing parts of the road extraction results is very short relative to the total length of the whole road network. This leads to an indiscernible impact of filling these gaps on geometrical quality criteria. In this paper, using two different VHR satellite datasets and a gap-filling approach which is based on tensor voting, we show that utilizing an effective road gap filling can result in a quite tangible topological improvement in the final road network which is highly demanded in many applications.