Application of Weighted PageRank Algorithm in Road Network Auto-selection

The auto-selection of road network is the core content of the road data generalization. Aiming at the shortage of current researches which ignores the effect from the neighbor node and the road density when calculating the road node importance degree. This paper proposes a method based on weighted PageRank algorithm. Firstly, the road stroke is generated and treated as the basic calculation unit. Then the road network is treated as a weighted directed graph that the road stroke as the node of the graph, as well as the road junctions are treated as the link between the nodes. The stroke length is selected as the link weight between two graph nodes. When the road graph is built up, the weighted PageRank algorithm is used to calculate the importance degree of the node which stands for the road importance degree and take the effect from the neighbor node into account. Next, thinking about the influence of the road density, the SpamRank method is selected. The SpamRank is just contrary to the PageRank and could be used to modify the importance degree exception caused by the road density. After revised by the SpamRank it will get the latest PageRank on which the road selection is based. Finally, using the Zhengzhou road data for experimental verification, the results show that this method can effectively maintain the original road connectedness and the whole structure compared with the network century method.