Abstract
Automated generalization of road network data is of great concern to the map generalization community because of the importance of road data and the difficulty involved. Complex junctions are where roads meet and join in a complicated way and identifying them is a key issue in road network generalization. In addition to their structural complexity, complex junctions don’t have regular geometric boundary and their representation in spatial data is scale-dependent. All these together make them hard to identify. Existing methods use geometric and topological statistics to characterize and identify them, and are thus error-prone, scale-dependent and lack generality. More significantly, they cannot ensure the integrity of complex junctions. This study overcomes the obstacles by clarifying the topological boundary of a complex junction, which provides the basis for straightforward identification of them. Test results show the proposed method can find and isolate complex junctions in a road network with their integrity and is able to handle different road representations. The integral identification achieved can help to guarantee connectivity among roads when simplifying complex junctions, and greatly facilitate the geometric and semantic simplification of them.
Highlights
Map generalization is a special variant of spatial modelling, which involves deriving a less detailed spatial representation from a detailed one and was traditionally performed manually by cartographers [1]
This paper presented a neat solution to the problem of identifying complex junctions
In addition to preserving the integrity of complex junctions, the proposed method is free from the troublesome threshold-setting, able to deal with different representations of roads, and efficient
Summary
Map generalization is a special variant of spatial modelling, which involves deriving a less detailed spatial representation from a detailed one and was traditionally performed manually by cartographers [1]. Unlike simple planar junctions, such as crossings and T-junctions where major roads directly intersect by themselves, complex junctions can be planar ones with slip roads for smooth turning and can be grade-separated interchanges with ramps for bridging gaps in height What is more, they can be very complex in structure and twisted in shape. Savino et al [23,26] noticed node density did not work in some cases They used statistics of redundant circles (or loops in topological terms) to characterize different forms of complex junctions and tried to detect them by searching for such circles in a road network.
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