4668663
doi
10.5281/zenodo.4668663
oai:zenodo.org:4668663
user-gisruk_2021
Gong, Zhaoya
University of Bristol and The Alan Turing Institute
Tranos, Emmanouil
University of Bristol and The Alan Turing Institute
Detecting urban structure through inter-city human interactions in China
Willis, George
University of Birmingham
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
<p>We combine novel inter-city human interaction data with traditional node attribute data to explore<br>
how the Chinese urban network is structured, and how this is associated with the economic<br>
performance of cities in an increasingly urbanising China. We then employ well-established<br>
unsupervised machine learning algorithms to cluster the Chinese cities based on these network<br>
variables and create urban typologies based on mid-term migration patterns. We identify 7 clusters of<br>
cities with shared network characteristics and contrast their economic performances based on more<br>
traditional data. The most disconnected, peripheral cities are also shrinking with a negative population<br>
difference, but are not necessarily the weakest economically, with a reliance on primary industry.</p>
Zenodo
2021-04-07
info:eu-repo/semantics/conferencePaper
4668662
user-gisruk_2021
1617798437.139332
707169
md5:348ed8a3345f38e28ff91b5ece005cb9
https://zenodo.org/records/4668663/files/GISRUK2021_paper_61.pdf
public
10.5281/zenodo.4668662
isVersionOf
doi