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Title: Selective omission of road features based on mesh density for automatic map generalization
Authors: Chen, J
Hu, Y
Li, Z 
Zhao, R
Meng, L
Keywords: Map generalization
Mesh density
Network meshes
Road features
Road networks
Selection omission
Issue Date: 2009
Publisher: Taylor & Francis
Source: International journal of geographical information science, 2009, v. 23, no. 8, p. 1013-1032 How to cite?
Journal: International journal of geographical information science 
Abstract: Selection of roads is an intractable generalization operation due to the difficulty in retaining the density difference and connectivity of a road network. This paper proposes a novel approach of selective omission for roads based on mesh density. The density of a road network and its local variations are calculated using meshes as units. Since maps at different scales usually reveal different densities, different density thresholds for road networks are determined on the basis of theoretical analysis and empirical study of mesh densities on maps at different scales. The selection process starts with the identification of the meshes that have a density beyond the threshold. The mesh with the largest density is first treated. Its bounding road segments are ordered according to their relative importance. The least important segment is eliminated. The remaining segments are then merged with the adjacent mesh, thus forming a new mesh. The selection procedure is repeated until none of the meshes has a density beyond the threshold. Such a process of eliminating road segments and merging meshes can ensure the road network connectivity. In this study, the meshes are classified depending on the types of road segment. For the different mesh types, their density thresholds are set to be different, which can be used as an indicator for the preservation of the density difference. This proposed approach considers topological, geometric and semantic properties of the road network. It was applied to two sets of road networks, and the results of selection are convincing. This methodology has now been adopted for the updating of 1:50,000 maps of China.
ISSN: 1365-8816
EISSN: 1362-3087
DOI: 10.1080/13658810802070730
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