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dc.contributor.authorJianbo Lai
dc.contributor.authorJinghu Pan
dc.date.accessioned2022-01-30T20:15:49Z
dc.date.available2022-01-30T20:15:49Z
dc.date.issued2020
dc.identifier.other%28ASCE%29UP.1943-5444.0000581.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4266781
dc.description.abstractWith the advent of the Internet era, network data have become an important carrier characterizing residents' geography behavior. Tencent Migration big data can fully, dynamically, immediately, and visually record a population migration trajectory with location-based service (LBS) technology. Through the Tencent Migration data platform, data on daily population floating among 346 cities in China during the 2018 Spring Festival travel rush (SFTR) are obtained. The characteristics and spatial pattern of population flow among cities are analyzed from the perspectives of the population flow distribution level, hierarchical aggregation of the distributed network system, population flow spatial patterns, and network characteristics. Three-hundred forty-six cities were divided into nine communities. The results are as follows: the net inflow routes of the population in the three periods all show a diamond-shaped skeleton supported by a cross-shaped one. The population distribution centers are mainly concentrated in the four major urban agglomerations. The clear hierarchical structure and level distinction of population distribution centers can be identified, and there is a positive correlation between the level of city administrative and the influence of population floating. Population flows of most cities are in a relatively balanced state. The degree of urban network nodes is the power-law distribution, so the network is scale free, and the network has small-world characteristic. It provides a new perspective for the study of population mobility and urban network.
dc.publisherASCE
dc.titleChina's City Network Structural Characteristics Based on Population Flow during Spring Festival Travel Rush: Empirical Analysis of “Tencent Migration” Big Data
dc.typeJournal Paper
dc.journal.volume146
dc.journal.issue2
dc.journal.titleJournal of Urban Planning and Development
dc.identifier.doi10.1061/(ASCE)UP.1943-5444.0000581
dc.page04020018
dc.treeJournal of Urban Planning and Development:;2020:;Volume ( 146 ):;issue: 002
dc.contenttypeFulltext


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