A method for automatic airport operation counts using crowd-sourced ADS-B data

Abstract

Airports are tasked with counting and reporting their operations at least yearly. The counts are used at the local and national level to schedule maintenance, for research, and to receive funds, making their accuracy important. Historically, methods for counting operations at non-towered airports have relied on additional equipment at the airport or statistical estimates. In this work, we introduce a method to use crowd-sourced Automatic Dependent Surveillance – Broadcast (ADS-B) data from the OpenSky network to automatically count airport operations and report it separated by takeoffs and landings. We use two airports as case studies – Tulsa International Airport (TUL) and Purdue University Airport (LAF) – and compare the estimated operation counts from the ADS-B data algorithm to numbers reported through the Federal Aviation Administration’s (FAA) Air Traffic Activity Data System (ATADS).

Keywords

• airport operation counts
• ADS-B
• OpenSky
• non-towered airports
• crowd-sourced data
• airport count models