A method for automatic airport operation counts using crowd-sourced ADS-B data
| Autor: | Nicoletta Fala, Christos Falas, Anastasios Falas |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Aviation, Vol 26, Iss 4 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1648-7788 1822-4180 |
| DOI: | 10.3846/aviation.2022.18025 |
| Popis: | 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). |
| Databáze: | Directory of Open Access Journals |
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