Abstract
Identifying corresponding objects from geospatial databases at different levels of detail is crucial, especially in multi-scale road network matching, which is the prerequisite of data conflation, updating and quality assessment. `Stroke' has a considerable effect on automatic road network generalization, and is essential in the road network matching process. In road network generalization, topological relationships may change, and some roads may be deleted. In this paper, we propose a combined stroke-based matching approach of road networks considering the constraints of cartographic generalization for road networks under different scales. In the entire stroke matching, we utilize the modified Hausdorff distance for geometric similarity. We consider the topological differences in the structural similarity calculation and propose a new weight calculation method. Partial stroke matching can further identify the corresponding roads with changes and updates in different scales. We also propose a method of roundabout detection and matching. The proposed approach could not only match road networks with a small scale difference, but also road networks with a large scale difference. And it can successfully identify the M:N, M:1, 1:1, 1/M:1/N, and 1/M:1 matching relationships. The effectiveness of the proposed approach is verified by experimental results.
Highlights
A large amount of multi-source geographical data has been made available by public and private organisations with the development of spatial data collection methods and processing techniques [1]
A combined matching approach of road networks is proposed in this paper, the partial stroke matching method is based on segment decomposition to handle the changed roads and rules of road network generalization are considered in the similarity calculation
The results indicate that the proposed algorithm has a strong capability to adapt to the inconsistent connections of strokes and changes of multi-scale data
Summary
A large amount of multi-source geographical data has been made available by public and private organisations with the development of spatial data collection methods and processing techniques [1]. Operations of cartographic generalization for roads, such as selective omission, simplification and node combination, produce a further abstract road network, such that some geometric and topologic details of a small-scale dataset may be simplified from the large-scale dataset. We consider the constraints of cartographic generalization during the matching process. Based on all the abovementioned constraints, a combined matching approach of road networks is proposed. We can establish as many correspondences between road networks at different levels of detail (LoDs) as possible. This approach aims to present a robust and universal method for road network matching among multi-scale datasets.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
