Restricted accessResearch articleFirst published online 2025-4
Airport Cooperative Research Program Graduate Research Award 11-04: Geographic Information System Application to Unmanned Traffic Management within the National Airspace System
To adapt to the exponential growth of unmanned aircraft systems (UAS) and advanced air mobility, it is critical to understand the spatial patterns and interactions of National Airspace System (NAS) participants and the needs of the aviation community to improve on data-driven risk management decisions. Overall, NAS unmanned traffic management lacks a centralized system for collating, analyzing, and visualizing UAS and crewed aircraft data. This research provides perspectives into how geographic information systems (GIS) can be utilized to improve on risk management strategies through quantitative and qualitative analysis. The objectives and scope of this paper include information on the literature review conducted, data preparation, and a geospatial analysis of two 24 h periods of automatic dependent surveillance-broadcast (ADS-B) data in the vicinities of Purdue University Airport and Indianapolis International Airport, as well as a multilayered analysis of both ADS-B and DJI small UAS (sUAS) radio frequency (RF) data within a 2 h time period based on an AerialArmor.com watchlist UAS “high flyer” for Savanna/Hilton Head International Airport and surrounding area. This research demonstrates how GIS can be utilized for the Federal Aviation Administration Airman Database data, ADS-B data, DJI sUAS RF data, and confirmation of UAS airspace incursions; however, there are current limitations and constraints based on data coverage and quality. A GIS, coupled with advancements in computer processing, has the potential to address many of the issues related to congested airspace and integration of UAS through participation/collaboration amongst government, industry partners, and educational institutions.
LercelD. J.HupyJ. P.Exploring the Use of Geographic Information Systems to Identify Spatial Patterns of Remote UAS Pilots and Possible National Airspace Risk. Safety, Vol. 9, No. 1, 2023, p. 18. https://doi.org/10.3390/safety9010018
6.
Federal Aviation Administration (FAA). Next Generation Air Transportation System (NextGen), 2023. https://www.faa.gov/nextgen. Accessed June 01, 2023.
LercelD.HupyJ.Developing a Competency Learning Model for Students of Unmanned Aerial Systems. Collegiate Aviation Review International, Vol. 38, No. 2, 2020, pp. 12–33. https://doi.org/10.22488/okstate.20.100212
SchäferM.StrohmeierM.LendersV.MartinovicI.WilhelmM.Bringing Up OpenSky: A Large-Scale ADS-B Sensor Network for Research. IPSN-14 Proc., 13th International Symposium on Information Processing in Sensor Networks, Berlin, Germany, 2014, pp. 83–94.
15.
Federal Aviation Administration (FAA). Airport Data and Information Portal, FAA FORM 5010-1 Downloads, 2023. https://adip.faa.gov/agis/public/#/public. Accessed June 08, 2023.
LiY.ZhangY.WangL.GuanX.Research on Potential Ground Risk Regions of Aircraft Crashes Based on ADS-B Flight Tracking Data and GIS. Journal of Transportation Safety & Security, Vol. 14, No. 1, 2020, pp. 152–176. https://doi.org/10.1080/19439962.2020.1754981
WallaceR.KiernanK.HaritosT.RobbinsJ.D’souzaG. (2018). Evaluating Small UAS Near Midair Collision Risk Using Aeroscope and ADS-B. International Journal of Aviation, Aeronautics, and Aerospace, Vol. 5, No. 4, 2018, 1–31. https://doi.org/10.15394/ijaaa.2018.1268
24.
WallaceR. J.KiernanK. M.HaritosT.RobbinsJ.LoffiJ. M.Evaluating Small UAS Operations and National Airspace System Interference Using Aeroscope. Journal of Aviation Technology and Engineering, Vol. 8, No. 2, 2019, pp. 24–39. https://doi.org/10.7771/2159-6670.1189
25.
JacobJ.MitchellT.LoffiJ.VanceM.WallaceR.Airborne Visual Detection of Small Unmanned Aircraft Systems with and without ADS-B. 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS), 2018, pp. 749–756. https://doi.org/10.1109/plans.2018.8373450
26.
WallaceR.LoffiJ.HollimanJ.MetscherD.RogersT.Evaluating LAANC Utilization & Compliance for Small Unmanned Aircraft Systems in Controlled Airspace. International Journal of Aviation, Aeronautics, and Aerospace, Vol. 7, No. 2, 2020, pp. 1–23. https://doi.org/10.15394/ijaaa.2020.1453
27.
VanceS.WallaceR.LoffiJ.JacobJ.DunlapJ.MitchellT. (2017). Detecting and Assessing Collision Potential of Aircraft and Small Unmanned Aircraft Systems (SUAS) by Visual Observers. International Journal of Aviation, Aeronautics, and Aerospace, Vol. 4, No. 4, 2017, pp. 1–23. https://doi.org/10.15394/ijaaa.2017.1188
28.
LoffiJ. M.VanceS. M.JacobJ.DunlapJ. C.MitchellT. A.JohnsonD. C.Pilot Visual Detection of Small Unmanned Aircraft on Final Approach During Nighttime Conditions. International Journal of Aviation, Aeronautics, and Aerospace, Vol. 8, No. 1, 2021, pp. 1–28. https://doi.org/10.15394/ijaaa.2021.1568
29.
WallaceR. J.KiernanK. M.RobbinsJ.HaritosT.Small Unmanned Aircraft System Operator Compliance with Visual Line of Sight Requirements. International Journal of Aviation, Aeronautics, and Aerospace, Vol. 6, No. 2, 2019, pp. 1–20. https://doi.org/10.15394/ijaaa.2019.1327
30.
WallaceR. J.LoffiJ. M.VanceS. M.JacobJ.DunlapJ. C.MitchellT. A.Pilot Visual Detection of Small Unmanned Aircraft Systems (SUAS) Equipped with Strobe Lighting. Journal of Aviation Technology and Engineering, Vol. 7, No. 2, 2018, pp. 57–66. https://doi.org/10.7771/2159-6670.1177
WallaceR.WinterS.RiceS.KovarD.LeeS.Three Case Studies on Small Uncrewed Aerial Systems Near Midair Collisions with Aircraft: An Evidence-Based Approach for Using Objective Uncrewed Aerial Systems Detection Technology. SAE International Journal of Aerospace, Vol. 16, No. 3, 2023, pp. 263–278. https://doi.org/10.4271/01-16-03-0023
