With the complexity of spatial object matching between multi-source and multi-scale road networks is increasing, road network space target matching method encountered different levels of bottleneck in precision and accuracy. This paper proposes a road network matching method based on the stable spatial hierarchical structure, this method has both global and local features, it can overcome the mismatch caused by excessive dependence on local morphological structure as similarity criterion, and the matching result can also be found by fast convergence. The experimental results show that this paper combines particle swarm optimization for road network matching, it has obvious advantages in regions with similar local structures and significant global structural differences, the matching accuracy and optimization efficiency are improved obviously.
[1]
Zhu Li,et al.
A Road Matching Method Based on Complex Networks
,
2016
.
[2]
Meng Zhang,et al.
Methods and Implementations of Road-Network Matching
,
2009
.
[3]
Wang Hu,et al.
Research and implementation of parallel particle swarm optimization based on CUDA
,
2013
.
[4]
Qingquan Li,et al.
Generating hierarchical strokes from urban street networks based on spatial pattern recognition
,
2011,
Int. J. Geogr. Inf. Sci..
[5]
Francisco Javier Ariza-López,et al.
Digital map conflation: a review of the process and a proposal for classification
,
2011,
Int. J. Geogr. Inf. Sci..