Pattern and Influencing Factors of Urban Spatial Connection in Wuhan Metropolitan Area from the Perspective of Flow Space
Entering the stage of high-quality development,metropolitan areas,as a key link in the national new-type urbanization strategic pattern,have become an important spatial unit leading the regional development.This study takes Wuhan metropolitan area(WMA)as the research area.Based on the multi-source big data such as the mobile phone signaling and the Baidu index,this study explores the urban spatial connection pattern and influencing factors of WMA by using the factor movement model,the SOM neural network classification model,and the QAP regression analysis.The results show that:1)The spatial pattern formed by the flow of various elements in WMA is a multi-center structure,and the internal flow intensity is varied between different cities.2)SOM neural network classification model shows that the cities of WMA will be divided into four levels according to their current urban spatial connections and there will be huge gaps between different levels.3)The variances in the urban development level and the informatization level have a significantly negative impact on the intensity of factor movements among different cities,while the difference of city size and openness degree has a significantly positive impact,which jointly affects the formation of urban spatial linkage pattern in metropolitan areas.According to the above,it puts forward suggestions for optimizing of the spatial linkage pattern of the Wuhan metropolitan area.
factor movementpopulation flowmulti-source big datamobile signalingSOM neural network classification modelspatial connection patternWuhan metropolitan area
万方数据
维普
