Forecast of Domestic and International Air Demand Based on Big Data for the Improvement of Passenger Terminal Services in Urban Area Airport

Abstract

Background/Objectives: As the air traffic users continues to increase, the problem of improving the service of passenger terminal is earnest. An accurate air demand forecast was performed to cultivate a systematic airport infrastructure.

Methods/Statistical analysis: Based on big data, the research was performed the long-term air demand forecast for domestic and international flights, and afterwards, the research and existing research reports suitable for respective characteristic were reviewed and analyzed to supplement the necessary parts.

Findings: In case of air demand, the demand for domestic and international flights was predicted by 2045, using big data and performance values in demand deduction formula. The air demand forecast was performed largely by passengers, cargo and flight, and the air demand was derived by dividing into inland areas and Jeju area for domestic flights, and by basic demand and high growth demand for international flights.

Improvements/Applications: The reduction of population and a differentiated service improvement plan that can cope with new transportation method is needed in order to enhance the value of the future aviation industry sector. 

Keywords: Airport Infrastructure, Big Data, Air Demand Forecast, Domestic Flights, International Flights