Is this project an undergraduate, graduate, or faculty project?
Undergraduate
group
What campus are you from?
Daytona Beach
Authors' Class Standing
Rodrigo Dieguez, Junior Joao Souza Dias Garcia, Professor
Lead Presenter's Name
Rodrigo Dieguez
Faculty Mentor Name
Joao Souza Dias Garcia
Abstract
This study presents an exploratory analysis of Embry-Riddle Aeronautical University (ERAU) flight training operations at Daytona Beach International Airport (DAB) using ADS-B data from the OpenSky Network. The analysis focuses on ERAU's 2023 operations, investigating patterns and trends across multiple dimensions, including temporal variables (seasons, months, days of the week, and flight blocks), geographic positions, and fleet types. By examining these variables, the study identifies variations in air traffic density, geographic preferences, and fleet utilization throughout the year. A key focus of this research is measuring airspace usage near DAB and analyzing aircraft flow during peak and off-peak hours. Data preprocessing was conducted using Python, and advanced visualizations were created in Tableau to provide insights into ERAU's airspace utilization. This research not only contributes to optimizing flight operations but also enhances analytical capabilities for addressing broader aviation challenges using ADS-B data.
Did this research project receive funding support from the Office of Undergraduate Research.
Yes, Collaborative Grant
Exploring ERAU Fleet Airspace Utilization Using ADS-B Data
This study presents an exploratory analysis of Embry-Riddle Aeronautical University (ERAU) flight training operations at Daytona Beach International Airport (DAB) using ADS-B data from the OpenSky Network. The analysis focuses on ERAU's 2023 operations, investigating patterns and trends across multiple dimensions, including temporal variables (seasons, months, days of the week, and flight blocks), geographic positions, and fleet types. By examining these variables, the study identifies variations in air traffic density, geographic preferences, and fleet utilization throughout the year. A key focus of this research is measuring airspace usage near DAB and analyzing aircraft flow during peak and off-peak hours. Data preprocessing was conducted using Python, and advanced visualizations were created in Tableau to provide insights into ERAU's airspace utilization. This research not only contributes to optimizing flight operations but also enhances analytical capabilities for addressing broader aviation challenges using ADS-B data.