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Road density is a useful index widely employed in the analysis of ecological effects, road network planning, delimitation of urban areas and road network generalization. The evaluation of generalization result is a key issue in the field of automated map generalization. This paper proposes a road density partition method for the evaluation of road selection. The method first creates the Voronoi diagram of road intersections and endpoints, and then uses the Getis-ord Gi* statistic to identify the statistically significant (at the confidence level of 95%) spatial clusters of high values and low values of Voronoi cells' areas. Finally, the method merges the neighboring Voronoi cells corresponding to those clusters. The road network of Wuhan at the levels of 15, 13 and 11 of the Google Maps was used as experimental data to evaluate the road network selection result of the proposed method. The experiment result showed that the road density partitioning with the proposed method generally well reflects the road network density in each area and contrast between different areas before and after road selection. Meanwhile, the proposed method was proved to be superior to the grid density method.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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