Spatiotemporal Exploration of Chinese Spring Festival Population Flow Patterns and Their Determinants Based on Spatial Interaction Model
Bibliographic Data
| ID | 22032034 |
|---|---|
| Authors | Tao Zhou (0000-0003-1295-8331, Southwest Jiaotong University), Bo Huang (0000-0001-6073-432X, Chinese University of Hong Kong, corresponding author), Xiaoqian Liu (0000-0003-4886-7837, Southwest Jiaotong University), Guangqin He (0000-0001-8120-0140, Southwest Jiaotong University), Qiang Gou (0000-0002-5737-6039, Southwest Jiaotong University), Zhihui Huang (0000-0003-1834-3207, Southwest Jiaotong University), Cheng Xie (0000-0002-1564-9166, Southwest Jiaotong University) |
| Year | 2020 |
| Volume | 9 |
| Issue | 11 |
| Pages | 670 |
| Publication date | 2020-11-12 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi9110670 |
| OpenAlex | W3101624975 |
| Language | EN |
| Citations received | 11 |
| References cited | 39 |
Large-scale population flow reshapes the economic landscape and is affected by unbalanced urban development. The exploration of migration patterns and their determinants is therefore crucial to reveal unbalanced urban development. However, low-resolution migration datasets and insufficient consideration of interactive differences have limited such exploration. Accordingly, based on 2019 Chinese Spring Festival travel-related big data from the AMAP platform, we used social network analysis (SNA) methods to accurately reveal population flow patterns. Then, with consideration of the spatial heterogeneity of interactive patterns, we used spatially weighted interactive models (SWIMs), which were improved by the incorporation of weightings into the global Poisson gravity model, to efficiently quantify the effect of socioeconomic factors on migration patterns. These SWIMs generated the local characteristics of the interactions and quantified results that were more regionally consistent than those generated by other spatial interaction models. The migration patterns had a spatially vertical structure, with the city development level being highly consistent with the flow intensity; for example, the first-level developments of Beijing, Shanghai, Chengdu, Guangzhou, Shenzhen, and Chongqing occupied a core position. A spatially horizontal structure was also formed, comprising 16 closely related city communities. Moreover, the quantified impact results indicated that migration pattern variation was significantly related to the population, value-added primary and secondary industry, the average wage, foreign capital, pension insurance, and certain aspects of unbalanced urban development. These findings can help policymakers to guide population migration, rationally allocate industrial infrastructure, and balance urban development
Beijing · Business · Cartography · China · Civil engineering · Economic geography · Geography · Gravity model of trade · Population · Spatial ecology · Urban planning · Demography · Engineering · Human Mobility and Location-Based Analysis · Migration, Aging, and Tourism Studies · Urban Transport and Accessibility · Ecology
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| Citations per year | 2.2 |
|---|---|
| Citation span | 2021 - 2026 (6) |
| Highly cited | No |