Population migration across the Qinghai-Tibet Plateau: Spatiotemporal patterns and driving factors
文献类型:期刊论文
作者 | Wang Nan1,2; Wang Huimeng1,2; Du Yunyan1,2; Yi Jiawei1,2; Liu Zhang1,2; Tu Wenna1,2 |
刊名 | JOURNAL OF GEOGRAPHICAL SCIENCES
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出版日期 | 2021-02-01 |
卷号 | 31期号:2页码:195-214 |
关键词 | Qinghai-Tibet Plateau population migration migration big data flow radiation model spatiotemporal interaction mode |
ISSN号 | 1009-637X |
DOI | 10.1007/s11442-021-1842-z |
通讯作者 | Yi Jiawei(yijw@lreis.ac.cn) |
英文摘要 | Developing a comprehensive understanding of inter-city interactions is crucial for regional planning. We therefore examined spatiotemporal patterns of population migration across the Qinghai-Tibet Plateau (QTP) using migration big data from Tencent for the period between 2015 and 2019. We initially used decomposition and breakpoint detection methods to examine time-series migration data and to identify the two seasons with the strongest and weakest population migration levels, between June 18th and August 18th and between October 8th and February 15th, respectively. Population migration within the former period was 2.03 times that seen in the latter. We then used a variety of network analysis methods to examine population flow directions as well as the importance of each individual city in migration. The two capital cities on the QTP, Lhasa and Xining, form centers for population migration and are also transfer hubs through which migrants from other cities off the plateau enter and leave this region. Data show that these two cities contribute more than 35% of total population migration. The majority of migrants tend to move within the province, particularly during the weakest migration season. We also utilized interactive relationship force and radiation models to examine the interaction strength and the radiating energy of each individual city. Results show that Lhasa and Xining exhibit the strongest interactions with other cities and have the largest radiating energies. Indeed, the radiating energy of the QTP cities correlates with their gross domestic product (GDP) (Pearson correlation coefficient: 0.754 in the weakest migration season, WMS versus 0.737 in the strongest migration season, SMS), while changes in radiating energy correlate with the tourism-related revenue (Pearson correlation coefficient: 0.685). These outcomes suggest that level of economic development and level of tourism are the two most important factors driving the QTP population migration. The results of this analysis provide critical clarification guidance regarding huge QTP development differences. |
资助项目 | National Natural Science Foundation of China[41590845] ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China[2017YFB0503605] ; National Key Research and Development Program of China[2017YFC1503003] |
WOS研究方向 | Physical Geography |
语种 | 英语 |
WOS记录号 | WOS:000635936200002 |
出版者 | SCIENCE PRESS |
资助机构 | National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/161966] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Yi Jiawei |
作者单位 | 1.Univ Chinese Acad Sci, Coll Resource & Environm, Beijing 100049, Peoples R China 2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
推荐引用方式 GB/T 7714 | Wang Nan,Wang Huimeng,Du Yunyan,et al. Population migration across the Qinghai-Tibet Plateau: Spatiotemporal patterns and driving factors[J]. JOURNAL OF GEOGRAPHICAL SCIENCES,2021,31(2):195-214. |
APA | Wang Nan,Wang Huimeng,Du Yunyan,Yi Jiawei,Liu Zhang,&Tu Wenna.(2021).Population migration across the Qinghai-Tibet Plateau: Spatiotemporal patterns and driving factors.JOURNAL OF GEOGRAPHICAL SCIENCES,31(2),195-214. |
MLA | Wang Nan,et al."Population migration across the Qinghai-Tibet Plateau: Spatiotemporal patterns and driving factors".JOURNAL OF GEOGRAPHICAL SCIENCES 31.2(2021):195-214. |
入库方式: OAI收割
来源:地理科学与资源研究所
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