Airport Cooperative Research Program Graduate Research Award 11-04: Geographic Information System Application to Unmanned Traffic Management within the National Airspace System

Abstract

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.

Keywords

advanced air mobility air traffic management geographic information systems national airspace system unmanned aircraft systems unmanned traffic management

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