On Airport Unmanned Aircraft System Operations

Aerial image of airport showing how UAS might be used
Aerial View of Potential On-airport Applications for Small Unmanned Aircraft Systems

The proliferation of interest in and use of Unmanned Aircraft Systems (UAS), or drones, has led to significant policy and regulatory adaptations to integrate these platforms into the airport environment. As the technology and its use continues to mature, the FAA is committed to conducting research and providing policy and guidance to ensure the safe operation of UAS on-airports.

For questions about UAS registration, airspace authorization, waivers, law enforcement resources and more, visit www.faa.gov/uas/.

Airports Unmanned Aircraft System Contacts
Office Contacts
FAA Airports Emerging Entrants Division Mike Branum, Program Manager
FAA Technical Center

Garrison Canter, UAS Research Lead

Michael DiPilato, Airport Research Specialist

Airports Regional Contacts Alaskan
Central (IA, KS, MO, NE)
Eastern (DC, DE, MD, NJ, NY, PA, VA, WV)
Great Lakes (IL, IN, MI, MN, ND, OH, SD, WI)
New England (CT, ME, MA, NH, RI, VT)
Northwest Mountain (CO, ID, MT, OR, UT, WA, WY)
Southern (AL, FL, GA, KY, MS, NC, PR, SC, TN, VI)
Southwest (AR, LA, NM, OK, TX)
Western-Pacific (AZ, CA, HI, NV, GU, AS, MH)

Additional Information


    UAS Guidance & Resources

    Regulations and Policy

    On or Near Airport

    Airspace Authorizations

    Related Research and Articles

      ARFF Live Monitoring

      Obstacle Data Collection

      • Evaluation of Unmanned Aircraft Systems for Airport Obstacle Data Collection
        UAS obstacle data collection was conducted at five airports using a variety of UAS platforms, camera payloads, and data collection parameters. These data sets were processed using two types of aerial triangulation (AT) software and analyzed using three-dimensional (3D) stereoscopic analysis techniques. The UAS data sets were evaluated based on their image quality, completeness, and accuracy relative to current FAA standards. The accuracies of UAS-derived obstacle measurements were evaluated by comparing them with data sets collected using field survey techniques and aerial surveys utilizing manned aircraft. The results of both FAA and NGS review of the data found that UAS aerial imagery, in conjunction with 3D stereo analysis, is capable of collecting obstacle measurement data that meets current FAA Advisory Circulars 150/5300-17 and 150/5300-18 accuracy standards. The Office of Airports is currently evaluating the integration of the findings within the report into current policy and standard practice for obstacle data reporting.

      Pavement Inspections

      • Assessment of Small Unmanned Aircraft Systems for Pavement Inspections
        Pavement inspections play an integral role in ensuring airport safety. The FAA Airport Technology Research and Development (ATR) branch performed research to assess the integration of small Unmanned Aircraft Systems (sUAS) into an airport’s Pavement Management Program (PMP). To conduct sUAS-based pavement inspections, the research team tested across five different airports between 2020 and 2022. The objective was to provide a repeatable set of processes and procedures for data collection, analysis, and reporting for sUAS-based pavement inspections. This report presents sUAS data collection parameters, data processing techniques, and data analysis, as well as workflows associated with each inspection. A summary of distresses identifiable via sUAS is also provided.
      • Practical Lessons Learned from Planning, Collecting, Processing, and Analyzing Small Unmanned Aircraft System Data for Airfield Pavement Inspection (FAA)
        A small unmanned aircraft system (sUAS) or drone has proven to be a valuable tool for civil infrastructure inspection, highway inspection, unpaved road inspection, bridge inspection, construction work progress monitoring, and other applications. Additionally, several proof-of-concept studies showed that sUAS could be helpful for airfield pavement distress detection. This report documents a comprehensive study that evaluated the usefulness of sUAS-collected data in detection and rating both asphalt concrete and Portland cement concrete pavement distresses.
      • Small Unmanned Aircraft System for Pavement Inspection: Task 4—Execute the Field Demonstration Plan and Analyze the Collected Data (FAA)
        The primary objectives of this research project are to develop recommended processes and procedures for using small unmanned/uncrewed aircraft system (sUAS) to complement current methods of airport Pavement Management Program (PMP) inspections and to evaluate various types of sUAS platforms and sensors that will lead to recommended minimum specifications required for consistently safe, reliable, and effective sUAS-assisted airport PMP inspections.
      • Small Unmanned Aircraft System for Pavement Inspection
        The use of small Unmanned Aircraft Systems (sUAS) has attracted attention as an option for performing cost-effective and efficient pavement inspections. In this study, the research team deployed several sUAS at six airports in Michigan, Illinois, Iowa, and New Jersey. Different data types were processed and analyzed to assess their usefulness in airfield pavement distress detection and rating. The research team’s analysis showed that a combination of high-resolution orthophotos, digital elevation models derived from photogrammetry, and thermal data can be used to identify certain pavement distresses. However, the current technology does not yet fully offer the capability to detect and rate some low-severity distresses (alkali-silica reaction, corner spalling, joint spalling, joint seal damage, depression, raveling, swell, and weathering). This research did help establish guidelines for sUAS operations for pavement inspection, such as deployment of smaller sUAS for fast red, green, blue (RGB) data collection; deployment of a larger platform for very high-resolution data collection; having a minimum of three people on the data collection team; and the use of ground control points to ensure high-quality orthophotos. In the future, more sUAS platforms and sensors can be evaluated, and tools for automated pavement inspection may be developed using sUAS data.

      Wildlife Dispersal

      • Investigating nocturnal UAS treatments in an applied context to prevent gulls from nesting on rooftops
        Ring-billed (Larus delawarensis) and herring (L. argentatus) gulls are numerous and widespread in North America. These gulls rank among the top 9 species for risk of bird-aircraft collisions (hereafter strikes). The ubiquitous presence of gulls in urban coastal environments, including rooftop nesting behavior, are factors impacting strike risk. The purpose of this research was to assess gull response to a small uncrewed aircraft system (UAS) in hazing flights at night during the nest-building phase. 
      • Testing a Key Assumption of Using Drones as Frightening Devices: Do Birds Perceive Drones as Risky?
        Wildlife managers have recently suggested the use of unmanned aircraft systems or drones as nonlethal hazing tools to deter birds from areas of human-wildlife conflict. The research goal was to establish the degree to which the perception of risk by birds would vary between common drone platforms relative to a predator model when flown at different approach types.
      • Responses of Turkey Vultures to Unmanned Aircraft Systems Vary by Platform
        A challenge that conservation practitioners face is manipulating behavior of nuisance species. The turkey vulture (Cathartes aura) can cause substantial damage to aircraft if struck. The goal of this study was to assess vulture responses to unmanned aircraft systems (UAS) for use as a possible dispersal tool.

      Airport Cooperative Research Program (ACRP)

      Last updated: Wednesday, September 27, 2023