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An estimate of rural exodus in China using location-aware data.

Authors :
Ting Ma
Rui Lu
Na Zhao
Shih-Lung Shaw
Source :
PLoS ONE, Vol 13, Iss 7, p e0201458 (2018)
Publication Year :
2018
Publisher :
Public Library of Science (PLoS), 2018.

Abstract

The rapidly developing economy and growing urbanization in China have created the largest rural-to-urban migration in human history. Thus, a comprehensive understanding of the pattern of rural flight and its prevalence and magnitude over the country is increasingly important for sociological and political concerns. Because of the limited availability of internal migration data, which was derived previously from the decennial population census and small-scale household survey, we could not obtain timely and consistent observations for rural depopulation dynamics across the whole country. In this study, we use aggregate location-aware data collected from mobile location requests in the largest Chinese social media platform during the period of the 2016 Chinese New Year to conduct a nationwide estimate of rural depopulation in China (in terms of the grid cell-level prevalence and the magnitude) based on the world's largest travel period. Our results suggest a widespread rural flight likely occurring in 60.2% (36.5%-81.0%, lower-upper estimate) of rural lands at the grid cell-level and covering ~1.55 (1.48-1.94) million villages and hamlets, most of China's rural settlement sites. Moreover, we find clear regional variations in the magnitude and spatial extent of the estimated rural depopulation. These variations are likely connected to regional differences in the size of the source population, largely because of the nationwide prevalence of rural flight in today's China. Our estimate can provide insights into related investigations of China's rural depopulation and the potential of increasingly available crowd-sourced data for demographic studies.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
13
Issue :
7
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.30dfe80c63a44088a16cd86493883265
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0201458