14. Summary
1
• Aggregate of flights length and stops duration seems to follow an
exponential law.
2
• Flights number more heterogeneous than stops number
• Strong linear correlation in flights-stops number, almost 2 to 1.
• Stops time more heterogeneous than Flights time.
• No linear correlation between flights-stops time.
3
• Very narrow distribution in average velocity. (Homogeneous)
• Almost uniform distribution in ballistic factor. (Heterogeneous)
15. Future work
1
• Test exponential fit and power-law fit in current distributions.
• Investigate the linear relation between flight number and stops number.
2
• Look at the structure of the flights and stops sequence. Autocorrelation?
3
• Duration of the stops with respect to previous flight duration.
4
• Compare social variables (such as age, gender, group) with respect to
mobility variables (such as tortuosity, velocity, number of flights, etc.)
