The expanding global air network provides rapid and wide-reaching connections all around the world impacting human movement patterns that result in socioeconomic, environmental and epidemiological implications. Previous studies have been limited by the lack of information on flow, and had to rely on small samples or just passenger capacities on scheduled routes. This study describes the construction of an open-access modeled passenger flow matrix for all the airports with a host city-population more than 100,000 and within two transfers of air travel from various public available transportation datasets. Node and route characteristics, centrality measurement, city population, and local area GDP are utilized as covariates in a general gravity model framework to estimate the air transportation flows. Possible passenger flows between 1560 airport nodes on 2,016,208 routes have been predicted based on a log linear model with random effects controlled on origin airport and destination airport. Results show that 78% of the prediction falls in to the same scale of the observed value. The airports nodes characteristics and projected passengers on air travel routes will be published at www.vbd-air.com/data.
If you want to access the data, please send an email including your name, position and institution to email@example.com, with the title as "Request Annual Prediction Data"
New! Monthly prediction data for direct flight is available, please send an email including your name, position and institution to firstname.lastname@example.org, with the title as "Request Monthly Prediction Data for Direct Flight"
Recommended Citations are as follows:
Mao, L., Wu, X., Tatem, A., Huang, Z. (2015) Modeling monthly flows of global air travel passengers: an open-access data resource. Journal of Transport Geography 48: 52-60. (doi:10.1016/j.jtrangeo.2015.08.017)
Huang, Z., Wu, X., Garcia, A.J., Fik, T.J., Tatem, A.J., 2013. An open-access modeled passenger flow matrix for the global air network in 2010. PLoS ONE 8, e64317.
Further information can be found in the original article here. If you have any questions or concerns, please email Zhuojie Huang .
This data is generated by a modelling process and we are not responsible for the accuarcy of navigation. The usage of this data is limited for research and it is not allowed for other commercial usages.