Identifying Complex Junctions in a Road Network

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.

Automated summary

Automated generalization of road network data is challenging due to the complexity of identifying complex junctions, which do not have regular geometric boundaries and are scale-dependent. Existing methods using geometric and topological statistics to characterize and identify complex junctions are error-prone, scale-dependent, and lack generality. This study overcomes these challenges by clarifying the topological boundaries of complex junctions, leading to a more accurate identification method that ensures the integrity of the junctions and simplifies them effectively.