Identifying Important Spatial Structures in Cities Based on Graphwave – Taking Shanghai as an Example

With the advancement and development of urbanization in China, human activities are closely related to the changes in the internal structure and external layout of the city. The human migration model reflects the internal structure of the city to some extent. In two places where the city is far apart, the layout is very similar, and people's activities may also have certain similarities. Inspired by Graphwave, the city's spatial network was constructed using data from human travel. It was found that the city's more important and potentially influential areas of urban functioning. This paper uses the data of Shanghai Mobike and taxis to build a network, identifies the similarity nodes in the city, uses the POI data set to verify the final data, and explains its important geographical significance. Experiments show that similarity nodes are mostly distributed in schools and communities, and are relatively close to transportation hubs.