Designing an airport pavement is a complex engineering task. Thus, one of the first steps is to create scenarios for the operation of the airport. In this sense, the use of data analysis techniques can extract insights for this phase. Among the various parameters that characterize a runway, the most relevant is the structural capacity of the pavement and the length. For aviation, the standard for indicating the resistance of pavement is its Pavement Classification Number (PCN). Therefore, an application was developed in Python programming language, having as inputs the PCN and the runway length. Outputs are the aircraft supported by the pavement and the routes served (coverage). The development of this study follows the steps: a collection of real raw data about airports and aircrafts, data processing and cleaning, model development, model testing and application, result analysis, visualization, and final report. To test the model, the Viseu Aerodrome, located in the Center of Portugal region, was used. Several combinations have been created for PCN and runway length. Of all scenarios, three of them stood out, namely: maintain current characteristics (PCN 6 and length of 1160 m); an intermediate (PCN 23 and length of 1800 m); and a more robust scenario (PCN 83 and length of 2500 m). Finally, in the first scenario, it was possible to serve mainland Portugal, Spain, and a small portion of southern France. However, the operation was limited to small aircraft of up to 20 passengers. In the intermediate scenario, it was possible to serve much of the Schengen space with aircraft of up to 70 passengers. For the robust scenario, all Schengen space was served, with aircraft of up to 200 passengers. Therefore, based on two simple parameters, such as PCN and runway length, it was possible to visualize the coverage of an airport.

Airport; Pavement Design; Data Analysis