A new Voronoi diagram-based approach for matching multi-scale road networks

Jianhua Wu (), Yu Zhao (), Mengjuan Yu (), Xiaoxiang Zou (), Jiaqi Xiong () and Xiang Hu ()
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Jianhua Wu: Jiangxi Normal University
Yu Zhao: Jiangxi Normal University
Mengjuan Yu: Pudong New Area Big Data Management Center
Xiaoxiang Zou: Jiangxi Institute of Natural Resources Surveying, Mapping and Monitoring
Jiaqi Xiong: Jiangxi Normal University
Xiang Hu: Jiangxi Normal University

Journal of Geographical Systems, 2023, vol. 25, issue 2, No 6, 265-289

Abstract: Abstract Object matching is a key technology for map conflation, data updating, and data quality assessment. This article proposed a new Voronoi diagram-based approach for matching multi-scale road networks (VAMRN). Using this method, we first created Voronoi diagrams of the road network using the strategy of discretizing road lines into points and adding dense points to special road intersection segments. Then, we used the Voronoi diagram of road segment to find matching candidates. Finally, we obtained matching results by judging the geometric similarity metrics we designed and a heuristic combination optimization strategy. The experimental results demonstrated that the VAMRN outperformed two existing methods in generality and matching quality. The F-measures of VAMRN were 18.4, 29.6, 3.8, and 7.6% higher than the buffer growing method, and 4.5, 2.8, 1.8, and 6.1% higher than the probabilistic relaxation method. And the time performance is improved by more than 90% over the probabilistic relaxation method.

Keywords: Voronoi diagram; Identical roads; Road update; Road network matching; Data integration (search for similar items in EconPapers)
JEL-codes: C60 C61 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10109-023-00409-w

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