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Estimation of Regional Economic Development Indicator from Transportation Network Analytics.
Bin Li1, Song Gao2, Yunlei Liang3
1School of Automobile, Chang'an University, Xi'an, Shaanxi, 710064, China.
Scientific Reports
|February 16, 2020
Summary
China's booming economy is linked to highway transportation networks. Big data analysis reveals traffic patterns accurately predict regional economic development and inform planning.
Area of Science:
- Transportation Science
- Economic Geography
- Network Analysis
Background:
- Economic growth in China is increasingly linked to infrastructure development.
- Understanding the relationship between transportation and regional economics is crucial for planning.
Purpose of the Study:
- To analyze the connection between mid-distance land transport patterns and regional economic status in China.
- To leverage big data from highway toll systems for economic insights.
Main Methods:
- Complex network analysis of highway transportation networks.
- Computation of traffic flow features and correlation with economic indicators.
- Application of multi-linear regression and gravity models.
Main Results:
- Multi-linear regression models explained 89%–96% of cities' GDP variation.
- Gravity models revealed temporal changes in distance-decay effects on urban interactions.
- Transportation big data effectively indicated regional economic development status.
Conclusions:
- Highway transportation big data provides valuable insights into human mobility, production linkages, and logistics.
- This data can significantly aid regional management and economic planning.
- The study demonstrates the utility of transportation big data for assessing regional economic development.
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