On Spatial Agglomeration And Polycentric Structure Of Urban Mobility

Human mobility pattern in urban space has always been core topic in urban study.Discovering and understanding the aggregation pattern and centrality of city residents' movement is of great significance to help with solving urban traffic congestion,controlling the spread of diseases and efficient urban planning,as residents' travel is import part of urban traffic.The recent availability of geospatial data from human movements and communications has provided new insights on understanding human mobility.More studies implements a data-driven approach by utilizing data mining techniques to reveal human mobility pattern embedded in travel data and explore the driving law behind human mobility.Equipped with complex network theory and methods,through data mining on travel data of residents in the Tokyo metropolitan area,this paper studies the spatial patterns of urban residents' mobility from two aspects as follows: the aggregation pattern of human mobility in urban space,specifically the spatial community structure of residents' mobility;the mobility centrality of urban space units.For the study on the spatial community structure of residents' mobility,spatially embedded mobility network has been established to model the residents' travel in urban space based on approach of space lattice segmentation.Community detection algorithm has been implement to reveal the spatial community structure of mobility in diverse travel mode and in single travel mode.Two different spatial aggregation patterns of mobility have been found: dispersed pattern in short-distance travel modes(Walk,Bike,Bus and Vehicle)and relatively more concentrated pattern in long-distance travel modes(Railway).Further explorations of quantifying the impact of travel mode on spatial community structure of mobility has found that the community structure of shortdistance travel mode contributes to maintain the local internal connections while longdistance travel modes play important role in connecting and merging the local community.The finding also provides a new insight on urban transportation planning as it is essential to build a friendly environment and facility for short-distance travel modes to enhance the local connections of space.For the study on the mobility centrality of urban space units,which measures the importance of space units on residents' mobility,more specifically the connection with others space units as a spatial bridge.Betweenness centrality measure in complex network has been first utilized to measure the significant hubs of spatial unit in global topology.Moreover,travel mode entropy has been used to describe the extent to which the diverse travel modes are effectively utilized in space unit,based on information entropy theory.Then,travel hub index(THI)has been proposed to measure the mobility centrality of space units based on travel modes entropy and travel flow.Through the robustness experiment on the mobility network,this paper finds that the proposed THI significantly affect the connection of nodes,which means the available choices of diverse routes in residents' travel.Combined with the spatial community structure of mobility,the global mobility hubs,intra-community hubs and inter-community hubs have been revealed by THI.Further analysis on the economic data in Tokyo metropolitan area explains that using the proposed THI to reveal mobility hubs is reliable.The methods of this paper which combines community structure and proposed THI is easily applied to other cities,which is of great significance to help city managers with understanding the urban residents' travel,traffic planning and administrative division.