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

PLoS One. 2018 Jul 31;13(7):e0201458. doi: 10.1371/journal.pone.0201458. eCollection 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Female
  • Human Migration*
  • Humans
  • Male
  • Rural Population*

Grants and funding

This study was supported by grants from the National Natural Science Foundation of China (http://www.nsfc.gov.cn, grant 41421001, 41771418), the Key Research Program of Frontier Science, Chinese Academy of Sciences (http://www.cas.cn, grant QYZDY-SSW-DQC007) and the National Science and Technology Key Project (http://www.most.gov.cn, grant 2016YFB0502301). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There are no patents, products in development or marketed products to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.