Linking Traffic Volume to Economic Development Index Using Big Data and Gravity Models

Authors: TIMOTHY PRESTBY*, University of Wisconsin-Madison, Song Gao, Project Supervisor , Yunlei Liang, Assistant Researcher, Yuhao Kang, Assistant Researcher, Bin Li, Assistant Researcher
Topics: Geographic Information Science and Systems, Transportation Geography, Economic Geography
Keywords: Big data, Economics, Transportation
Session Type: Guided Poster
Day: 4/3/2019
Start / End Time: 2:35 PM / 4:15 PM
Room: Roosevelt 3.5, Marriott, Exhibition Level
Presentation File: Download

Previous research suggests that China’s transportation infrastructure affects economic development. Our study presents a novel idea that the economic development is also affected by the attraction between two cities in terms of travel radii and magnitude. To connect these concepts, the measure of traffic flow is used and incorporated into a gravity model to quantify the attraction of cities. This data can then be correlated with a city’s GDP to guide economic policies. Using root-means square and chi square tests, high correlations of the observed and estimated GDP were obtained. Results also showed that cities with higher GDPs have higher attraction. Planners can use these results to create informed plans for cities with varying levels of development. Further, we found that freight truck traffic volume is less dependent on the GDP compared to cars/buses. Freight trucks are still influenced by a city’s attraction, but the level of attraction does not depend so much on GDP. This makes sense since most freight trucks will travel to a variety of cities taking raw materials, commercial goods, etc. from a mix of urban and rural areas. Lastly, the highest GDPs, traffic volumes, and therefore attraction are located in Xi’an, Xianyang, Weinan, and Yan’an.

Abstract Information

This abstract is already part of a session. View the session here.

To access contact information login