Abstract
Selective omission in a road network is necessary for road network generalization. There are two core problems for the selective omission of multi-scale road networks. One is how many roads we should select, and the other is which roads we should select. Existing multi-scale transformation models are preferably used to solve the first problem, but which roads to select is still under exploration. The second problem is closely related to the importance measurement of the roads in road networks. Some existing approaches use the geometric and structural characteristics of a road to measure the importance of the road. However, it is short of evaluations on the situation (aspects of network functionality and cartography) in which the composite indexes could be used to rank the road properly. This paper focuses on a comparative analysis on the composite indexes and finding a new composite index to define the importance of a road in view of network functionality. Eight composite indexes are used to define the importance of the roads in road networks. A new approach called road removing is proposed to indicate the correctness of the composite indexes. Three real road networks of different patterns are tested. The result shows that the length and the degree are the basis for evaluating the importance of a road. If the clustering coefficient is considered, the composite indexes have adverse effects on the sorting of high-rank roads. While the closeness is added, the sorting of low-rank road is unreasonable. If the length, degree and betweenness are considered all together, the composite indexes perform best in the sorting of roads.
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Acknowledgements
This work is jointly supported by the National Natural Science Foundation of China project (No.41101361 and 41471383) and the Fundamental Research Funds for the Central Universities (No.SWJTU11CX063).
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Wu, X., Zhang, H., Xu, Y., Yang, J. (2017). A Comparative Study of Various Properties to Measure the Road Hierarchy in Road Networks. In: Zhou, C., Su, F., Harvey, F., Xu, J. (eds) Spatial Data Handling in Big Data Era. Advances in Geographic Information Science. Springer, Singapore. https://doi.org/10.1007/978-981-10-4424-3_11
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DOI: https://doi.org/10.1007/978-981-10-4424-3_11
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