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作 者:YE Xinyue GONG Junfang LI Shengwen
机构地区:[1]Department of Landscape Architecture and Urban Planning Texas A&M University,College Station,TX 77843 USA [2]School of Geography and Information Engineering,China University of Geosciences,Wuhan 430074,China [3]Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources,Shenzhen 518034,China
出 处:《Chinese Geographical Science》2021年第1期14-26,共13页中国地理科学(英文版)
基 金:Under the auspices of National Natural Science Foundation of China(No.41801378,42071382);the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources(No.KF-2019-04-033)。
摘 要:The connectedness between cities has become one of the most widely discussed topics in urban and regional research in the mobile and big data era. One problem identified is the asymmetric city connectivity, partially due to data availability. We present a data-driven approach based on location and toponym(place name) extracted from social media data, to assess the asymmetric connectivity between cities. The assumption is that a higher frequency of occurrences of the name of city i in posts located in city j would imply that the city i is more influential than other cities upon city j. In addition, we’ve developed a group of measurements such as the relatedness index, impact index, link strength index, dependence index, and structure similar index to characterize such interactions. This framework of connectivity measurements can also be used to support smart planning taking into account the evolving interplay among cities. The space-time structure of urban systems in China is examined as the case study.
关 键 词:asymmetric city connectivity social media urban system China
分 类 号:TU984[建筑科学—城市规划与设计] P281[天文地球—地图制图学与地理信息工程]
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